Velocity Meter 4.21
🚀 Human-Centered AI Is the Next Competitive Edge
AI isn’t just getting smarter — it’s getting more human. From models that mimic human reasoning to tractors that “walk” vineyards, the future of AI is less about replacing people and more about enhancing how we think, work, and lead. This week, we explore how understanding the human side of AI — whether through cognitive psychology or frontline operations — is becoming the strategic unlock for competitive advantage.
Let’s dive in.

🌍 From Neural Nets to Cognitive Partners

Why the future of AI may look more like your brain than your tech stack
Artificial intelligence has always borrowed from the brain. But now, it’s returning to its roots in a deeper way — with psychology leading the next leap in AI capabilities.
Psychological principles like metacognition (thinking about thinking) and fluid intelligence (solving new problems without prior training) are guiding the development of more adaptive, explainable, and human-aligned AI. OpenAI’s recent advances in reasoning tests, and research from Microsoft and François Chollet, all reflect a pivot from pure scale to smarter design.
This shift matters because businesses increasingly rely on AI not just for speed, but for judgment. Whether it’s customer support bots navigating ambiguity or internal copilots suggesting strategic decisions, tomorrow’s AI systems will need to “think” more like us — and not just regurgitate patterns from the past.
There’s also a trust factor at play. As companies adopt AI across critical workflows, stakeholders will demand systems that explain themselves and make decisions in ways that feel intuitive — not black box. That’s where psychology comes in: it offers models for reasoning, learning, and even ethical decision-making.
💡 So what? Mid-market leaders don’t need a PhD in cognitive science — but they do need to ask the right questions when evaluating AI solutions:
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Does this model reason or just repeat?
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Can it explain why it made a recommendation?
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Is it built to generalize, or is it hard-coded?
🧠 Thought bubble: As AI starts to resemble the human mind more closely, the companies that thrive will be the ones that understand — and invest in — how machines think, not just what they say.

🏗️ AI Across Industries

🍇 Viticulture Gets a Tech Upgrade
Autonomous tractors, AI-powered irrigation valves, and crop-monitoring sensors are reshaping the wine industry — not by replacing labor, but by augmenting it. Napa vintner Tom Gamble is using AI to map his vineyard and optimize yields while cutting down fuel and water use. This is “precision farming” in action: smart, sustainable, and increasingly necessary in a climate-constrained world.
📌 Takeaway: Agriculture isn’t going post-human — it’s going post-manual. Mid-market agribusinesses should explore AI for operational sustainability and regulatory compliance.
🧠 Business Intelligence Isn’t Dead — It’s Reinventing Itself
Despite the hype, GenAI hasn’t killed BI platforms — it’s supercharging them. Forrester’s latest Wave report shows BI vendors are embedding large language models (LLMs) into tools for natural language querying, data cataloging, and unstructured data mining. The real differentiator? Not who uses LLMs — but how they’re integrated into workflows and governed.
📌 Takeaway: Don’t assume your current BI platform is future-ready. Audit how it’s adopting GenAI and whether it aligns with your industry’s data guardrails.
💼 Amazon’s AI Arms Race
Amazon is developing over 1,000 GenAI applications across shopping, media, healthcare, and logistics. CEO Andy Jassy calls AI a “once-in-a-lifetime reinvention of everything we know.” The takeaway? Every customer experience is up for disruption — and if you’re not proactively applying AI, you’re playing defense.
📌 Takeaway: Mid-market firms should watch how hyperscalers deploy GenAI — not to compete, but to identify new customer expectations and operational models.

📊 AI by the Numbers

📈 20% fewer errors — OpenAI’s o3 model reduces major mistakes in complex tasks by 20%, signaling a new level of reliability in agentic AI tools. (Source: OpenAI)
🧠 99.5% accuracy — The o4-mini model hit near-perfect scores on AIME 2025 when using a Python interpreter, proving small models can still be mighty. (Source: OpenAI)
🛠️ 10x development speed — DevOps-enabled AI workflows now allow for rapid prototyping and productionization of applications.(Source: Crunchbase)
📊 92% of companies — Intend to increase AI investment over the next three years, signaling accelerating enterprise momentum. (Source: Fortune)
⚠️ $5.5B sales hit — Nvidia faces this revenue loss from U.S. restrictions on AI chip exports to China. (Source: SiliconAngle)

📰 5 AI Headlines You Need to Know
🧠 OpenAI Debuts o3 & o4-Mini for Smarter, Tool-Savvy Reasoning
OpenAI’s newest models deliver more accurate, nuanced answers — with enhanced tool use and fewer mistakes across math, science, and business use cases.
💼 Salesforce Launches Einstein Copilot Studio for Custom Enterprise AI
The CRM giant introduced new tools to let companies build their own AI copilots — deeply integrated with Salesforce data and workflows.
🏦 Morgan Stanley Launches Internal AI Assistant Trained on Firm IP
The bank rolled out an AI tool tailored to employee workflows, offering personalized answers by drawing on proprietary research and internal knowledge.
🛡️ DoD Tests GenAI for Cyber Defense Simulation
The U.S. Department of Defense is experimenting with GenAI to simulate real-world cyberattacks, train analysts, and build AI-supported security protocols.
📉 Tariffs Slam Nvidia, AMD in U.S.-China AI Chip Crackdown
Export restrictions are costing Nvidia and AMD billions in revenue, accelerating onshore manufacturing, and reshaping global AI hardware supply chains.
⚡️ Final Take
As AI gets smarter, the question isn’t “what can it do?” — it’s “how well does it think?” The next wave of AI will look less like automation, and more like collaboration — augmenting human judgment, not replacing it. The leaders who win won’t just deploy tools. They’ll design systems that think with them.
📩 Stay Ahead with Velocity Road
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Velocity Meter 4.14
This week, we’re spotlighting a major evolution in how businesses—and even nonprofits—are beginning to deploy AI agents. These aren’t just chatbots or task automators; they’re increasingly autonomous collaborators capable of decision-making, coordination, and execution across digital workflows.
Whether it’s agents raising money for charity or handling customer requests across your org, the shift is clear: AI agents are getting real jobs.
For mid-market execs, this means rethinking your org charts and automation pipelines. Because soon, “team member” might also mean “trained model.”
Let’s dive in.

🌍 AI Agents Clock In—for a Cause
When most execs think about AI, they picture copilots: tools that help, but don’t lead. But what if AI could act on your behalf—autonomously navigating software, coordinating with others, even generating strategy in real time? That’s the promise behind AI agents, and a recent experiment from nonprofit Sage Future shows just how fast this future is arriving.
Sage Future placed four leading AI models into a virtual sandbox with a mission: raise money for a charity of their choice. The agents—powered by OpenAI’s GPT-4o and Anthropic’s Claude 3—weren’t given a script. They were told to figure it out.
Within days, they created social media accounts, coordinated via group chat, generated promotional materials, and chose to support Helen Keller International. They even held a poll to select their profile picture. Their final haul? A modest $257—raised mostly from human observers. But the point wasn’t the dollars. It was the agency.
These agents were capable of multi-step planning, cross-platform coordination, and iterative problem-solving. They researched charities, wrote persuasive content, and executed workflows across Gmail, X (formerly Twitter), and Google Docs. At times, they needed human nudges. But the takeaway is clear: the capabilities of agents are compounding fast.
“Today’s agents are just passing the threshold of being able to execute short strings of actions,” said Sage Future Director Adam Binksmith. “The internet might soon be full of AI agents bumping into each other with similar or conflicting goals.”
📌 Why this matters: Agent-based AI is moving from novelty to necessity. These digital teammates can triage support tickets, generate RFP responses, run dashboards, or even manage marketing operations. And the infrastructure—monitoring systems, APIs, agent frameworks—is catching up quickly. Organizations that start experimenting with agents today will be better positioned to scale intelligent automation tomorrow.

🏗️ AI Across Industries
🏥 Insurance: AI Is the New Risk Manager
Top insurers are using AI across underwriting, claims, sales, and IT to drive faster decisions, automate tasks, and boost customer satisfaction. According to BCG, these changes aren’t just about efficiency—they’re driving clear competitive advantage.
🔎 Takeaway: AI in legacy industries isn’t about transformation—it’s about survival.
🧱 Construction: From Reactive to Predictive
Machine learning is showing up on job sites to help project managers predict budget overruns, spot defects through drone vision, and reduce injury risks via wearable safety tech. ML is also enabling smarter task scheduling and resource allocation.
📌 Takeaway: ML is helping mid-market contractors control costs and timelines in an industry built on thin margins.
🧠 Marketing: From Siloed Teams to AI-Powered Pods
Forget the old silos. Today’s marketing teams are forming cross-functional pods where AI tools drive content, analytics, and even ethics. New roles like Prompt Engineering Specialist and AI Marketing Ethics Officer are redefining the org chart—and slashing agency spend by up to 60%.
📌 Takeaway: Rethink your marketing org now—or risk being outpaced by those who already have.
💸 Capital Markets: AI Becomes a $20B Bet
Andreessen Horowitz is raising a $20B AI mega-fund—one of the largest ever. It’s aimed at infrastructure-heavy AI ventures and comes with perks like access to GPU clusters for portfolio companies.
📌 Takeaway: Mid-market execs should track where AI capital flows—because today’s VC darlings are tomorrow’s must-have integrations.

📊 AI by the Numbers
🤖 $257 — Raised by autonomous AI agents in a one-week nonprofit experiment, showcasing early potential for agent-driven execution across web and social platforms. (TechCrunch)
💼 60% — Reduction in agency spend reported by a B2B firm after reorganizing marketing into AI-augmented pods. (Academy of Continuing Education)
🧠 91% — Data leaders who say cultural resistance—not tech limitations—is the biggest barrier to becoming AI-driven. (MIT)
📈 1,200% — Increase in traffic to U.S. banking sites from generative AI sources in using AI for financial services research. (Search Engine Land)
🛍️ 1,300% — Surge in traffic from generative AI to U.S. retail sites during the holiday season. (Search Engine Land)
📰 5 AI Headlines You Need to Know
🧩 Google rolls out agent-like “Gems” in Workspace Flows – New Gemini-powered “Gems” let users automate multi-step tasks across Docs, Sheets, and Gmail—no coding required.
🛍️ Generative AI use surges among consumers for online shopping – Adobe data shows a significant increase in traffic from generative AI to U.S. retail sites, indicating a growing consumer reliance on AI for online shopping activities
🔍 AI search predicted to become primary tool for most US users by 2027 – Forecasts indicate that AI will be the dominant search method for 90% of US citizens within two years, requiring businesses to adapt their visibility strategies.
🎬 Netflix is testing a new OpenAI-powered search – Think “funny but not dumb” or “quietly intense.”
🏢 WPP CEO emphasizes advanced AI capabilities amidst transformation – Mark Read, CEO of WPP, highlights the company’s significant investments and developments in AI through platforms like WPP Open.
⚡️ Final Take
This week made one thing clear: AI agents aren’t just clever copilots—they’re emerging as collaborators. From raising money for global health to rewriting org charts in marketing, autonomous AI is beginning to take real action in real-world contexts.
It’s easy to dismiss experiments like Sage Future’s $257 fundraiser as novelty. But don’t miss the signal in the noise. These agents created strategy, built content, and executed workflows—with minimal human intervention. That’s not a gimmick. That’s the future of knowledge work.
For mid-market leaders, the imperative is clear: start building the conditions now for agents to plug into your organization. That means identifying low-friction workflows, investing in oversight infrastructure, and upskilling your team to collaborate with—not just supervise—AI.
Because when “teammate” means transformer, your org won’t just scale. It will evolve.
📩 Let’s Build Your AI Operating System
Velocity Road helps mid-market firms turn AI hype into enterprise-ready capability. Whether you’re launching agents, training your workforce, or building automation blueprints, we’re your partner for practical AI deployment.
Weekly Velocity Meter 4.7
🔥 The Rise of the Digital Runway
AI isn’t just optimizing workflows anymore—it’s rewriting the creative process itself.
From fashion and film to internal IT and customer service, intelligent agents are stepping into roles once reserved for humans—not to replace imagination, but to redefine how it’s expressed, scaled, and monetized.
This week, we’re looking at how brands like H&M are turning code into content—and why synthetic media is just the tip of the iceberg. What happens when your top creative asset is… an algorithm?
Let’s dive in.

💡When the Model Is Code—H&M’s Digital Twins and the Future of Brand Storytelling
In a move that blurs the line between tech innovation and brand identity, H&M is introducing AI-generated digital twins of 30 real-life models to power upcoming marketing campaigns and social content. This isn’t a sci-fi gimmick—it’s a scalable, strategic effort to cut production costs, streamline creative workflows, and expand content velocity.
But there’s a twist: the models own the rights to their digital likenesses. This means their virtual selves can be licensed to other brands—yes, even competitors—potentially creating a new asset class for individual talent. It’s the influencer economy, but upgraded for the synthetic age.
🧵 Why this matters:
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Operational upside: AI-generated imagery reduces the need for physical shoots, travel, and manual post-production. For retail brands navigating tight margins, this unlocks major savings.
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Creative scale: Need a campaign tailored to a local market or seasonal vibe? Digital twins can be styled, posed, and placed anywhere—in seconds.
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Talent empowerment (or erosion?): While H&M’s licensing model offers an ethical baseline, the broader question looms: what happens to the photographers, stylists, and creative teams this tech may displace?
📣 For mid-market leaders, this is more than a fashion trend. It’s a signal that AI is moving upstream—from automation to imagination. Brand building, content ops, and customer experience are now fair game for intelligent agents and synthetic media.
👉 The opportunity: Adopt AI tools that amplify creativity, not just replace labor.
💡 Think of AI as your new creative intern—one who works 24/7 and iterates at scale. But don’t outsource judgment. As H&M demonstrates, the future belongs to companies that blend AI capability with human ethics—and build governance models that protect people, even as the pixels take over.

🏗️ AI Across Industries
🌐 Web Development Hits Warp Speed
In just five months, Netlify and Bolt powered the creation of over 1 million AI-generated websites. This signals a sea change in how businesses prototype, launch, and scale their digital presence—with far fewer bottlenecks.
👉 Takeaway: Embrace AI dev tools to move faster from idea to execution—especially for microsites, MVPs, and campaign landing pages.
🖥️ AI-Powered IT Support at American Express
Amex has rolled out a generative AI chatbot that clarifies IT issues, guides users step-by-step, and reduces escalations by 40%. Meanwhile, 85% of engineers using GitHub Copilot report high satisfaction.
👉 Takeaway: AI tools can dramatically reduce support burdens and improve internal experience—consider starting with chatbots in IT or HR help desks.
🎓 Claude Goes to School
Anthropic has launched a classroom-friendly version of its Claude chatbot to support education and critical thinking. Leaders at LSE describe this as a transformational moment for how students engage with ideas.
👉 Takeaway: Pilot AI tools not just in ops, but in L&D and employee enablement, where they can foster smarter, more agile teams.

📊 AI by the Numbers
🎬 $3B: Valuation of Runway AI, following a new funding round backed by Nvidia and Salesforce Ventures—highlighting the soaring investor appetite for AI video tech (Reuters).
💻 1M+: Number of AI-generated websites created via Netlify and Bolt in just five months—an eye-popping stat showcasing the speed of AI adoption in web development (Netlify).
🧑💻 40%: Drop in IT ticket escalations at American Express, thanks to an AI-powered internal chatbot that resolves issues interactively (VentureBeat).
🚀 85%+: Percentage of Amex engineers satisfied with GitHub Copilot, reinforcing the value of AI in developer productivity and workflow optimization (VentureBeat).
📈 5–15%: Expected uplift in marketing productivity through generative AI, as reported by McKinsey’s research into business AI impact (McKinsey).
📰 5 AI Headlines You Need to Know
🧠 SoftBank and OpenAI Announce Massive Startup Financing: In a historic move, SoftBank is backing an investment of up to $40 billion in OpenAI, marking the largest startup financing ever and highlighting the intense investor focus on leading AI companies.
🔍 Google Warns Scaled AI Content Will Be “An Issue” for Search: Google’s Danny Sullivan reiterates that the origin of scaled content (AI or human) is less important than its lack of originality and value to users.
🌏 GroupM Taps DeepSeek for Smarter Media Buying in China: GroupM partners with a Chinese LLM, DeepSeek, to improve targeting and efficiency in one of the world’s most complex ad markets.
📈 Amazon Introduces Nova Act, an AI Agent to Control Web Browsers: Amazon’s new AI agent, along with its SDK, signals a move towards more autonomous AI capable of performing online task
🍎 Apple Reportedly Developing AI “Doctors”: Sources say Apple is building generative health agents that could advise users based on data—hinting at a major push into AI-powered healthcare.
⚡️ Final Take
We’re entering an era where the most scalable creators aren’t human.
That’s not a threat—it’s a turning point. The companies that win won’t just use AI to do more work faster. They’ll use it to ask better questions, tell better stories, and build entirely new value chains.
The future isn’t automated. It’s augmented. And the clock’s already ticking.
📩 Ready to operationalize AI in your mid-sized business?
Let Velocity Road guide you from experimentation to execution. Whether you’re exploring agents, automation, or org-wide AI readiness, we’ll help you move fast—and move smart.
Weekly Velocity Meter 3.31
🔥 Welcome to this week’s Velocity Meter.
This week, AI took a step closer to running full marketing operations on its own — while also becoming smarter, more intuitive, and more embedded across industries.
We’re seeing real progress in the development of autonomous agents, advanced reasoning models, and creative content tools. These are signals of how AI is becoming more integrated into how businesses think, operate, and grow.
Let’s get into it.

🏢 The Rise of Autonomous Marketing: Are Your Campaigns Agent-Ready?
This week, Zeta Global launched its AI Agent Studio, enabling marketers to chain together generative agents to drive full-funnel performance. Meanwhile, Google’s Media Lab showcased how AI agents can now pull insights for briefs — no human search needed.
What’s emerging is more than automation — it’s orchestration. AI agents can now manage workflows like programmatic buying, audience segmentation, and even creative brief generation. For mid-market teams with limited resources, this could unlock speed, personalization, and scale once reserved for enterprise giants.
But adoption isn’t plug-and-play.
At the Adobe Summit, Hilary Cook emphasized that operational excellence is table stakes. Before unleashing autonomous AI, companies need clean processes, clear data flows, and defined roles.
And while agents can run the machine, humans still steer the ship. The “human in the loop” isn’t optional — it’s what ensures strategy, ethics, and brand voice stay aligned.
📌 Bottom line: Autonomous marketing is real — and rising fast. The companies that win will be the ones who treat AI as a team member, not just a tool.

🏗️ What AI Changed This Week
🤔 Next-Gen AI Reasoning Models Emerge:
Google unveiled Gemini 2.5, a new family of AI reasoning models designed to “think” before answering, achieving state-of-the-art performance on various benchmarks. This leap in AI intelligence, capable of handling complex prompts and large contexts, paves the way for more sophisticated AI applications across various business functions.
📌 Takeaway: Monitor the capabilities of these advanced reasoning models as they become more accessible, exploring potential applications in areas like data analysis, content generation, and customer support.
🎨 AI Fuels Creative Content Innovation
Beyond marketing automation, AI is revolutionizing creative content creation. Reve Image 1.0 has emerged as a top AI image generation model excelling in prompt adherence and text rendering. Midjourney is also exploring techniques to make LLMs write more creatively.
📌 Takeaway: Leverage these advancements to produce high-quality visual and textual content more efficiently, enhancing their branding and marketing materials without significant design overhead.
📚 AI Fluency = Competitive Advantage
As AI adoption accelerates, data and AI literacy are no longer optional skills but crucial for staying competitive. Initiatives like the OpenAI Academy aim to democratize AI knowledge.
📌 Takeaway: Invest in upskilling their workforce to understand and effectively collaborate with AI tools, ensuring they can be the “human in the loop” and drive responsible and strategic AI adoption.

📊 AI by the Numbers
🔍 90% → The forecasted percentage of US citizens expected to use AI search as their primary search tool by 2027. (Source: SEM Rush)
💰 $100 Billion → The estimated value gains for the insurance industry through AI-enabled customer experience. (Source: Qualtrics)
📈 19% → The percentage of B2B decision-makers already implementing generative AI use cases for buying and selling. (Source: McKinsey)
🚀 $60 Million → The amount raised by n8n, a fair-code pioneer in AI-powered workflow automation. (Source: TechCrunch)
📊 5x → The revenue increase n8n reported after pivoting its workflow automation platform to be more AI-friendly in 2022. (Source: TechCrunch)
📰 5 AI Headlines You Need to Know This Week
🧠 Bill Gates Says ‘We Won’t Need Humans For Most Things’ in 10 Years: Gates’ perspective on AI’s potential to automate most human tasks, including high-value services, underscores the long-term transformative impact of AI on the workforce and business operations.
🎨 Adobe Integrates AI Deeply Across Marketing Ecosystem: The Adobe Summit revealed that AI is now core to Adobe’s entire digital experience ecosystem, impacting content creation, audience segmentation, and personalization at scale.
🎨 Family Offices Increase Investments in AI within Private Markets: Ultra-wealthy family offices are significantly boosting their investments in AI in private markets, demonstrating a strong belief in AI’s potential for early-stage innovation and portfolio growth.
📚 OpenAI’s Sam Altman Warns of the Necessity to Learn AI: OpenAI CEO Sam Altman emphasized the critical need for individuals to learn and master AI tools, comparing it to the importance of coding skills in the past, as AI increasingly automates tasks like coding.
🔧 Nvidia Presents an AI-Centric Future at GTC Conference: Nvidia’s GTC conference highlighted its central role in the rapid evolution of AI, showcasing new AI chips and partnerships aimed at accelerating AI adoption across various industries, including robotics.
✅ TL;DR / Takeaways
The marketing landscape is evolving towards autonomous operations with the rise of sophisticated AI agents.
📌 Advanced AI reasoning models and innovative creative AI tools are unlocking new possibilities for mid-market businesses.
📌 Developing data and AI literacy within your organization is crucial for effectively leveraging these technological shifts.
📌 Focus on building a strong operational foundation to maximize the benefits of AI adoption.
The key to success lies in human-AI collaboration, where technology augments human capabilities for greater impact.
📩 Need Help Navigating AI?
At Velocity Road, we help middle-market companies seamlessly integrate AI into their operations—driving efficiency, scaling automation, and enabling smarter decision-making. Whether it’s strategy, implementation, or change management, we ensure AI delivers real business impact.
Let’s explore how AI can transform your business—schedule a consultation today!
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See you next week,
— The Velocity Road Team
Weekly Velocity Meter 3.24
🔥 Welcome to this week’s edition of Velocity Meter.
Companies aren’t just adopting new tools. They’re rebuilding how they work, rethinking how they lead, and reimagining what humans and machines can do together.
From autonomous agents making real business decisions to AI copilots built by employees themselves, the game has changed. And the companies playing to win? They’re shifting culture, structure, and strategy all at once.
Let’s dive into what’s happening this week.

🏢 AI Isn’t Eating Jobs—It’s Restructuring Organizations
This week’s shift? The rise of digital coworkers: autonomous AI agents embedded in operations, making real decisions—not just automating tasks.
📈 At Intuit, mission-based teams with embedded AI specialists have delivered an 8x increase in development velocity. More on that below.
🤖 At Colgate-Palmolive, employees build their own AI copilots—fostering buy-in and bypassing resistance.
🔐 At Visa, to meet employee demand for AI tools while ensuring data security, a secure RAG-powered chatbot retrieves regulatory data 1,000x faster, with citations.
But the transformation isn’t just technical—it’s cultural. McKinsey predicts the leading brands in 2025 will combine AI, immersive tech, and authentic social values. Turning AI into a megaphone for purpose.
💡Key Takeaway: The AI advantage no longer lies in choosing the right tool. It lies in how you design your people, processes, and platforms to use it.

🏗️ How AI is Shaping Industries
🪢 The Talent Tug-of-War: AI Proficiency and the Rise of Deepfakes
The job market is witnessing a significant shift towards AI proficiency. Companies are prioritizing AI integration, fundamentally changing skill demands. However, a concerning trend has also emerged: AI-powered deception in recruitment. A security startup nearly hired a non-existent backend engineer using an AI filter as an on-screen disguise in video interviews. This highlights the increasing sophistication of fake applicant scams and the need for robust verification protocols.
💡 Key Takeaway: While AI skills are in demand, companies must be vigilant against AI-driven recruitment fraud and refine their verification strategies.
🛡️ The Shadowy Side of AI and the Governance Imperative
As AI tools become more accessible, the rise of “shadow AI” – the use of AI by employees outside official IT frameworks – presents significant governance challenges. This uncontrolled dissemination of sensitive company data and the potential for inaccurate information can lead to poor decision-making. Organizations often unknowingly grapple with shadow AI, as employees leverage services like ChatGPT without corporate alignment. Establishing clear, acceptable use policies and technology controls is crucial.
💡 Key Takeaway: AI governance frameworks are essential to mitigate the risks associated with shadow AI, ensuring data integrity and compliance.
⚙️ The Perpetual AI Motion Machine
The buzzword? Continuous AI Transformation. It’s not a one-and-done deal; it’s about building a culture of perpetual adaptation and growth. Intuit, for example, has embraced three guiding principles around technology, people, and processes to fuel this ongoing innovation. Their strategies include rigorous technical reviews, embedding AI experts in cross-functional teams, and encouraging constructive conflict. This approach has led to tangible customer benefits, like small businesses getting paid faster through AI-powered invoice reminders in QuickBooks Online. These “mission-based teams” are driven by measuring customer benefit in real-world terms, contributing to both innovation and talent retention. Regular progress assessments ensure AI investments align with customer needs and market demands. This dynamic approach allows businesses to rapidly adapt to the ever-changing AI landscape.
💡 Key Takeaway: Building a culture of continuous AI innovation is crucial for maintaining competitive advantage. Regular technical reviews, cross-functional teams, and structured conflict resolution are key pillars.
🔋 Supercharging Productivity (But Watch Out for the Human Factor!)
Generative AI promises better, faster, easier, and cheaper workflows, with a potential $4.4 trillion in productivity growth. Early adopters are already seeing results in areas like supplier negotiations and equipment maintenance. A European automotive supplier achieved a 20-30% time saving while improving code quality using gen AI. However, realizing this potential requires more than just implementing the technology.
A recent survey reveals a significant disconnect between executives and employees, with half of company leaders acknowledging that AI is “tearing their company apart.” Employees harbor skepticism and frustration, often stemming from fears of job displacement and dissatisfaction with current AI tools. As May Habib, CEO of Writer, aptly put it, “Asking those employees to embrace AI is like ‘asking a turkey to vote for Thanksgiving.” Trust in AI is intrinsically linked to trust in leadership. Employees won’t trust AI if they don’t trust their leaders.
💡 Key Takeaway: While AI offers immense productivity gains, managing employee experience and building trust are critical for successful implementation. An “AI-leader combination” that involves employee discussions and transparent decision-making can effectively reduce anxiety.

📊 AI by the Numbers
🧑💼 72% → The percentage of small businesses feeling positive about how AI is empowering their operations (Source: Paychex)
💸 $3.8B → Capital raised by AI agent startups in 2024. Nearly triple the amount raise in 2023. (Source: CB Insights)
🧠 94% → The percentage of consumers who remain loyal to brands with genuine and transparent actions, a trend amplified by AI and other technologies. (Souce: McKinsey)
📄 45.2% → The proportion of all enterprise AI application transactions attributed to ChatGPT, despite it also being the most blocked AI tool (Source: SaaStr)
📉 50% → Unilever’s cost reduction in product shoots using digital twins (Source: Adweek)
💰 $90 million → The estimated annualized efficiencies Intuit expects from its AI investments within their customer success organization in the first half of the fiscal year alone. (Souce: HBR)
📰 5 AI Headlines You Need to Know This Week
⚡️ Execs Admit: AI Is Causing Culture Cracks: A new survey reveals that 50% of enterprise leaders feel AI is “tearing their company apart”—exposing a growing disconnect between top-down strategy and frontline adoption.
💡 Google Turns Gemini into a Creative Powerhouse: The new Canvas feature transforms Gemini from chatbot to full-fledged workspace—enabling live coding, document collaboration, and voice-guided walkthroughs.
🎥 xAI Acquires Hotshot to Fuel Video Intelligence: Elon Musk’s xAI snapped up video startup Hotshot, accelerating its move into multimodal AI—where text, image, and video understanding converge.
🛡️ AI Supercharges Insurance—but Legacy Tech Lingers: From risk modeling to fraud detection, AI is overhauling property and casualty insurance. But many players still struggle with outdated infrastructure.
🤝 AI Rewrites the Brand-Agency Playbook: Agencies are moving from executors to AI-powered strategists—using automation to personalize campaigns and free teams for higher-level thinking.
💻 Tech is Easy. 🤝 Trust is Hard.
AI fails when humans resist it. And they resist it when it feels imposed, not integrated.
The most successful transformations aren’t driven by smarter algorithms—they’re driven by smarter leadership. When employees trust the process—and their leaders—they don’t just adopt AI. They elevate it.
That’s your edge. Build trust first. The rest will follow.
“The toughest part of AI implementation? It’s not the tech. It’s managing how people experience change.”
— David Hilborn, West Monroe Partners
📩 Need Help Navigating AI?
At Velocity Road, we help middle-market companies seamlessly integrate AI into their operations—driving efficiency, scaling automation, and enabling smarter decision-making. Whether it’s strategy, implementation, or change management, we ensure AI delivers real business impact.
Let’s explore how AI can transform your business—schedule a consultation today!
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See you next week,
— The Velocity Road Team
Weekly Velocity Meter 3.17
🔥 Welcome to this week’s edition of Velocity Meter.
AI isn’t just a buzzword anymore—it’s a full-fledged revolution. From autonomous agents making decisions to AI-driven marketing strategies redefining customer engagement, industries are transforming at lightning speed.
Let’s dive into what’s happening this week.

🧠 AI Specialization—Choosing the Right Brain for the Job
Move over, one-size-fits-all AI. This week’s major development is the sheer proliferation and specialization of AI models. With companies rolling out specialized AI systems fine-tuned for distinct tasks.
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Meta’s latest Llama model is enhancing efficiency and excelling in math and knowledge-based tasks.
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Google’s Gemini Deep Research is refining how AI summarizes search results for instant insights.
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Cohere and other AI labs are pushing multimodal models that can process text, images, and complex reasoning.
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China’s Manus AI agent is making headlines as a potential leap toward Artificial General Intelligence (AGI).
❓ Why it matters: The AI explosion isn’t just about having more models—it’s about selecting the right one for your specific business challenges. From visual data analysis to multilingual processing and supply chain optimization, AI is becoming increasingly task-specific. See the full breakdown of models here.
💡 Key takeaway: Map your business needs to the evolving AI landscape. The right AI model can unlock efficiencies, insights, and competitive advantages that generic AI solutions might miss.

🏗️ Tracking AI’s Impact Across Industries
Whether it’s supercharging marketing strategies, optimizing financial decisions, or redefining customer experiences, AI is forcing every industry to adapt. The key to staying ahead? Knowing where AI is making the biggest impact—and how you can use it.
📢 Marketing & Advertising: AI is Taking Over Ad Buying
The days of guesswork in digital marketing are over. AI is now dominating ad planning and buying, automating nearly every step and making precision targeting a reality. Amazon’s AI is scanning customer reviews to craft hyper-personalized campaigns, while Target is using generative AI to spot social media trends in real time, cutting product launch cycles from months to weeks.
💡 What to do: If your marketing still relies on intuition over AI-driven insights, you’re already behind. Start exploring AI-powered tools for content creation, customer sentiment analysis, and campaign automation.
💰 Finance & Private Equity: AI as the New Investment Analyst
Private equity firms are integrating AI to automate due diligence, analyze financial models, and source new deals. AI-driven insights are fueling $200B in private market investments, with AI accelerating deal execution and portfolio management.
💡 What to do: AI isn’t just for tech firms—investment teams should explore AI tools for financial modeling, risk assessment, and deal flow management.
🛍️ Retail & Hospitality: AI is Reading Your Mind (Almost)
Customer experience is getting an AI facelift. Hotels are rolling out AI concierge systems that anticipate guest needs, while retailers are using generative AI to predict consumer behavior. AI-powered revenue management is helping hotels dynamically adjust room prices while also explaining pricing logic to build staff and guest trust.
💡 What to do: Businesses should integrate AI-powered customer engagement platforms that predict and personalize interactions to maximize sales and customer loyalty.
⚙️ AI Integration: The Playbook for Success
The World Economic Forum highlights the Discover-Decide-Deliver framework for integrating AI across businesses. Their guide shows how companies can use AI to accelerate decision-making, automate workflows, and drive efficiency. Meanwhile, MarketingProfs stresses that AI success starts with a strong data strategy—before AI can transform your business, your data needs to be structured, accessible, and reliable.
💡 What to do: Companies should audit their data quality and identify areas where AI can optimize processes, from legal contract automation to predictive analytics for customer behavior.
🧑🏫 Mastering AI: The Skills Gap is Growing
AI’s power is undeniable, but there’s a catch—it’s only as good as the people using it. Businesses are rushing to upskill employees, but a talent gap in AI education is growing fast. The ability to write better AI prompts, use “chain-of-thought” reasoning, and integrate AI into workflows is quickly becoming a make-or-break skill in every industry.
💡 What to do: If your team isn’t getting AI training, start now. Consider AI literacy programs or prompt engineering training to maximize productivity and output.
🔥 Bottom line: AI isn’t coming—it’s already here. The businesses that succeed will be the ones that adopt AI-driven decision-making, invest in AI-powered tools, and train their teams to work alongside AI effectively.
The question is: Are you ahead of the curve—or playing catch-up? 🚀

📊 AI’s Business Impact by the Numbers
⏱️ Research from the Federal Reserve Bank of St. Louis shows that generative AI boosts worker productivity by an average of 33% per hour of use, providing a clear measure of AI’s impact on output.
🫥 According to the AlixPartners Disruption Index, 35 percent of executives worry that overreliance on AI will reduce employees’ problem-solving skills, highlighting a key concern beyond mere productivity .
🎯 Target has demonstrated AI’s ability to accelerate business agility by reducing product launch cycles from 7 months to 8 weeks using generative AI for trend analysis.
📄 In legal operations, AI can achieve up to 60% faster processing times in Contract Lifecycle Management (CLM), showcasing its potential for significant back-office efficiency gains.
💰 ServiceNow’s $3 billion investment in AI startups exemplifies the tech industry’s strong strategic focus and financial backing of AI innovation in service management.
📰 5 AI Headlines You Need to Know This Week
⚡️ China’s Manus AI Sparks AGI Speculation: AI startup Butterfly Effect has launched Manus, an AI model with autonomous decision-making capabilities, raising discussions about Artificial General Intelligence (AGI).
💰 $26M Raised for AI-Powered Brand Agents: Firsthand, an AI startup, secured $26M to develop AI agents for brands and publishers, signaling major investment in AI-driven marketing.
🎯 Target’s AI-Powered Retail Innovation: The retailer is leveraging AI and social media insights to identify emerging trends faster, streamlining product development.
⏱️ AI Increases Workplace Productivity by 33%: A Federal Reserve study found that employees using generative AI see a 33% boost in productivity per hour, showing AI’s growing impact on workflows.
🐦 Bluesky CEO on AI & Decentralization: Bluesky’s CEO, Jay Graber, envisions a decentralized digital landscape, prioritizing user control over AI-generated content.
✨ AI Is a Tool—Not a Replacement for Human Innovation
As AI continues to advance, the smartest businesses won’t just automate tasks—they’ll blend AI with human creativity and strategy. The companies that win in the AI era will be those that:
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Adopt AI strategically—not just for efficiency, but for true business transformation.
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Prioritize AI literacy across leadership and teams.
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Balance automation with human ingenuity—AI can process data, but it can’t replace empathy, intuition, and brand authenticity.
The AI-driven future is unfolding fast. Are you ready to ride the wave?
📩 Need Help Navigating AI?
At Velocity Road, we help middle-market companies seamlessly integrate AI into their operations—driving efficiency, scaling automation, and enabling smarter decision-making. Whether it’s strategy, implementation, or change management, we ensure AI delivers real business impact.
Let’s explore how AI can transform your business—schedule a consultation today!
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See you next week,
— The Velocity Road Team
Weekly Velocity Meter 3.10
🔥 Welcome to this week’s edition of Velocity Meter.
AI isn’t slowing down—it’s evolving at warp speed. Autonomous agents are getting smarter, enterprises are making big bets, and the competition to stay ahead is fiercer than ever. The question isn’t if AI will reshape your business—it’s how fast you’re adapting.
Let’s dive into what’s happening this week.

🤖 AI Agents Are Going Rogue (in a Good Way?)
Forget chatbots that just answer questions. This week, the spotlight’s on AI agents that can actually do stuff on their own. Salesforce dropped Agentforce 2dx, letting AI agents autonomously manage tasks across enterprise systems. Think less human prompting, more AI-driven doing. Not to be outdone, OpenAI is reportedly eyeing a hefty $20,000/month price tag for their specialized AI agents, signaling some serious enterprise-level power. And if you’re thinking of building your own AI army? Frameworks like LangGraph, Autogen, and Crew AI are making it easier to create custom agents for everything from sales leads to investment decisions.
❓ Why it matters: This shift towards autonomous AI agents could seriously crank up efficiency and automate complex workflows. But it also raises questions about integration, employee training (more on that below!), and who’s in charge when the AI takes the wheel.
💡 Key takeaway: Start thinking about where autonomous AI agents could streamline your operations. Keep an eye on pricing models and the platforms making agent deployment easier.

🏗️ Tracking AI’s Impact Across Industries
✨ Personalization Gets Supercharged with AI
Remember when personalization meant putting someone’s name in an email? Those were the good old days. Now, AI is taking personalization to a whole new level. Kaltura launched TV Genie, an AI-powered tool that hyper-personalizes entertainment experiences for streaming services. Imagine Netflix knowing your exact mood and recommending the perfect show – that’s the vibe. In marketing, brands like Coca-Cola and Ducati are using generative AI to create deeply customized campaigns that resonate with individual consumers. Even something as crucial as hospitality reputation management is getting an AI makeover, with tools analyzing guest sentiment in real-time.
❓ Why it matters: Consumers expect tailored experiences. AI-driven personalization can boost engagement, loyalty, and ultimately, the bottom line.
💡 Key takeaway: Explore how AI can personalize your customer interactions, from marketing to product recommendations. Remember that trust and data privacy are key when wielding this level of personalization.
🧑💻 Skill Up or Get Left Behind: The AI Talent Scramble
All this fancy AI tech needs someone to understand and manage it. Turns out, there’s a bit of a disconnect between how confident leaders are in their AI training and how prepared employees actually feel. We’re seeing the emergence of new job titles like “generative AI management consultant,” proving that AI implementation is becoming a specialized skill. Even tech giants like Salesforce are heavily investing in reskilling their massive workforce on agentic AI. And in more traditional industries like food and beverage, the need for specialized AI competence is increasingly clear.
❓ Why it matters: Without a skilled workforce, even the coolest AI tools will gather digital dust. Bridging the AI skills gap is crucial for successful adoption and realizing ROI.
💡 Key takeaway: Assess your organization’s AI readiness and invest in training programs. Consider how new AI-focused roles might fit into your structure.

📊 AI’s Business Impact by the Numbers
From massive efficiency gains to fresh creative workflows, these numbers tell the story of a tech revolution that’s reshaping business.
📢 170% increase in job postings mentioning generative AI from January 2024 to January 2025
🏦 80% of CFOs in middle-market companies are driving AI integration in financial processes.
🚨 58% of businesses adopting AI cite competitive pressure as their primary motivator
🎨 83% of creative professionals are already leveraging generative AI tools in their work.
💰 $90 million estimated efficiencies Intuit expects from its AI investments.
👉 Case Study Spotlight: Leading gown distributor Amarra achieved a 40% reduction in overstocking, cut content creation time by 60%, and is handling 70% of customer inquiries through their AI-powered solutions.
📰 5 AI Headlines You Need to Know This Week
📌 Opera is now the first major browser with built-in AI agentic browsing, letting the browser handle tasks for you. Talk about convenience (and maybe a little bit creepy?).
📌 WPP is doubling down on AI, investing in Stability AI to boost its generative AI capabilities for marketing and advertising.
📌 Reddit shared insights on how brands can effectively adopt AI in marketing based on community feedback, emphasizing utility and transparency.
📌 Yum Brands‘ Taco Bell is showing off “Byte by Yum,” an AI tool to help fast-food managers with tasks like scheduling and inventory.
📌 A study found that 58% of businesses using AI are motivated by “pressure from competitors“, highlighting the fear of missing out in the AI race.
The Human Touch Still Matters, Folks ❤️
Amid all the AI hype, it’s crucial to remember that brand is still everything. While AI can automate tasks and personalize experiences, it can’t fully replicate human emotion, trust, and connection.
🌟 The smart move? Leverage AI as an ally for automation, not a replacement for human creativity.
❤️ So, go ahead, embrace the AI revolution, but don’t forget the human touch that truly builds lasting relationships.
📩 Need Help Navigating AI?
At Velocity Road, we help middle-market companies seamlessly integrate AI into their operations—driving efficiency, scaling automation, and enabling smarter decision-making. Whether it’s strategy, implementation, or change management, we ensure AI delivers real business impact.
Let’s explore how AI can transform your business—schedule a consultation today!
📩 Did a friend forward this to you? Sign up here to get The Velocity Meter straight to your inbox!
See you next week,
— The Velocity Road Team
Weekly Velocity Meter 3.3
🔥 Welcome to this week’s edition of Velocity Meter.
AI is no longer just automating tasks—it’s becoming a digital workforce. From Salesforce and Slack embedding AI teammates to Workday onboarding “digital employees,” businesses are redefining how work gets done.
This week, we explore AI’s growing role in market research, customer service, and enterprise operations. As AI transforms from tool to team member, mastering human-AI collaboration will be key to staying competitive.
Let’s dive in.
THE BIG SHIFT
🔄 AI Agents – The Workforce Disruptor
The workplace is undergoing a radical transformation, and it’s not just about remote work anymore. AI agents—autonomous digital workers capable of handling everything from customer service to sales coaching—are taking on increasingly complex tasks, often without human intervention.
⚡️ The Acceleration:
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Salesforce and Slack are pushing AI agents into mainstream enterprise use, redefining how teams collaborate.
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Startups like Sierra are securing massive funding to build AI-driven workforce solutions, signaling a shift in how companies think about human roles.
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OpenAI expects a third of its projected 2025 revenue to come from enterprise automation tools.
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Workday is integrating AI agents as “digital employees,” onboarding them just like human workers.
⚠️ The Challenge:
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AI agents are inconsistent. Unlike traditional software, they don’t always perform the same way every time.
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Workers are unsure how to collaborate with AI. Will they replace employees, or will they truly be an extension of human teams?
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Human interactions in the workplace may decline as AI takes over communication-heavy roles.
✅ The Fix:
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Treat AI agents as team members, not just tools—define their roles and measure their performance.
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Establish governance frameworks to ensure AI operates within ethical and operational boundaries.
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Train employees to work alongside AI, so they understand when and how to leverage digital co-workers.
💡 Bottom Line: AI isn’t just a productivity booster—it’s becoming an integral part of the workforce. The companies that figure out how to manage AI-human collaboration will gain a competitive edge.
VELOCITY TRENDS
🏗️ Tracking AI’s Impact Across Industries
🗣️ AI is Transforming Consumer Research via Voice
Suzy has launched Suzy Speaks, an AI-powered voice methodology for gathering consumer insights. This innovative approach uses AI-moderated conversations to capture rich qualitative data at a quantitative scale, moving beyond traditional rigid questionnaires.
🔹 How AI is Revolutionizing Conversational Research:
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AI moderation allows for more natural and organic consumer feedback.
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It provides deeper insights that might be missed through traditional survey methods.
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This trend democratizes market research by making it more accessible and cost-effective.
💡 Takeaway: Voice-driven AI is set to revolutionize market research by enabling more authentic and scalable collection of consumer insights.
📖 Source: Trend Hunter
📞 AI Phone Agents are Automating Customer Service
Vida has introduced an AI phone agent designed to transform customer interactions by providing 24/7 availability and seamless call handling. This technology helps businesses manage high call volumes, prevent missed opportunities, and improve overall customer service.
🔹 Benefits of AI Phone Agents:
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They can automate routine tasks like appointment scheduling and follow-ups.
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The platform offers customizable call flows and multi-language support.
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Performance analytics provide actionable insights for refining customer service strategies.
💡 Takeaway: AI-powered phone agents are emerging as a crucial tool for businesses to enhance customer service efficiency and satisfaction by automating call handling and providing continuous availability.
📖 Source: Martech Zone
🛍️ AI Agents and Human Insight are Set to Transform the Shopping Experience
E-commerce is poised for a major shift with the integration of AI agents. These models, combining LLMs and multi-modal processing, will offer unprecedented personalization and operational efficiency, scaling like human assistants but without limitations.
🔹 How AI Agents Will Enhance E-commerce:
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They will create a more frictionless front-end user experience.
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AI agents will contribute to hyper-efficient back-end operations.
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Continuous human oversight (‘humans-in-the-loop’) is crucial for aligning AI agents with brand values.
💡 Takeaway: AI agents are expected to revolutionize the e-commerce shopping experience by providing highly personalized interactions and streamlining operational processes.
📖 Source: Total Retail
VELOCITY STATS
#️⃣ AI’s Business Impact by the Numbers
AI isn’t just being adopted—it’s becoming the backbone of modern business strategy. The question is no longer if AI will reshape industries but how fast companies can adapt before they’re left behind. The latest data reveals just how deeply AI is embedding itself into operations, from workforce productivity to marketing efficiency.
📈 75% of knowledge workers now use generative AI (GenAI) in their workflows, highlighting its widespread adoption (Forbes)
💻 AI integration at Salesforce has increased software engineering output by 30% (Slashdot)
📢 90% of marketers plan to increase AI integration by 2025, reinforcing AI as a must-have tool for competitive businesses (MarTech Series)
⏳ AI-fluent professionals save an average of 25.2 hours per week, demonstrating major efficiency gains (Digital Information World)
📝 Marketers using AI save an average of 12.5 hours per week, improving productivity and workflow automation (HubSpot)
🧠 Thought bubble: We’re reaching the AI tipping point—where resistance is no longer just a strategic misstep, but a direct hit to competitiveness. Companies delaying AI adoption aren’t just missing out on incremental gains; they’re actively ceding market share to those moving faster.
IN THE NEWS
📰 5 AI Headlines You Need to Know
📌 Anthropic CEO Predicts Superintelligent AI by Next Year: Dario Amodei, co-founder and CEO of AI startup Anthropic, predicts that superintelligent AI, capable of surpassing human intelligence in most fields, could emerge as soon as next year. Anthropic aims to create AI that transforms society by automating complex tasks, akin to the impact of the industrial revolution.
📖 Source: The Times
📌 Amazon’s Alexa AI Overhaul: Amazon’s Senior Vice President of Devices and Services, Panos Panay, discussed the significant overhaul of Alexa with the launch of Alexa Plus. The new AI-powered assistant aims to improve user interaction beyond simple commands to more complex, multi-step tasks, reflecting a strategic shift to enhance natural language processing capabilities.
📖 Source: The Verge
📌 Ad Verification Firms Target Mid-Market Advertisers with AI: Ad verification companies like Integral Ad Science are investing in AI to attract mid-market advertisers. By enhancing automation and self-serve capabilities, they aim to provide better performance metrics and support for companies generating between $200,000 and $1 million in revenue.
📖 Source: Digiday
📌 A.I. Start-Up Anthropic Closes Deal That Values It at $61.5 Billion. The announcement follows new fund-raising efforts from rivals like OpenAI, which is set to close a deal that values the company at $300 billion, and Elon Musk’s xAI.
📖 Source: NY Times
📌 Cities embrace traditional and generative AI to become future-ready. Cities around the world are racing to adopt AI to drive productivity and efficiency and boost their economies, according to a global study of 250 cities conducted by ServiceNow and Deloitte, in collaboration with ThoughtLab, a leading provider of thought leadership research
📖 Source: Financial Post
FINAL TAKE
📈 The Urgency of AI Adoption: A CMO’s Perspective.
As a seasoned marketing innovator, Shiv Singh makes a compelling case that AI is currently underhyped, especially within the marketing world. His message is direct and pertinent for businesses across all sectors: those who want to remain relevant must adapt quickly and wholeheartedly embrace AI tools.
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Singh stresses the critical need for marketers and business leaders to move beyond mere curiosity and actively integrate AI into their strategies and operations.
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The potential benefits of AI are vast, but realizing them requires a proactive approach and a willingness to evolve traditional ways of working.
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The alternative to embracing AI is stark: Singh warns that companies failing to do so risk being left behind in an increasingly AI-driven marketplace.
💡 Takeaway: The time for cautious observation is over. To ensure future success and maintain a competitive edge, businesses must heed Shiv Singh’s call to action and prioritize the adoption and integration of AI technologies now.
📖 Source: No Brainer Podcast
📩 Need Help Navigating AI?
At Velocity Road, we help middle-market companies seamlessly integrate AI into their operations—driving efficiency, scaling automation, and enabling smarter decision-making. Whether it’s strategy, implementation, or change management, we ensure AI delivers real business impact.
Let’s explore how AI can transform your business—schedule a consultation today!
📩 Did a friend forward this to you? Sign up here to get The Velocity Meter straight to your inbox!
See you next week,
— The Velocity Road Team
Shadow AI: Navigating the Hidden Risks in the Middle Market
While the promise of Artificial Intelligence (AI) is enthralling, especially for middle market companies striving to innovate and remain competitive, there exists an undercurrent that could potentially sidetrack even the most meticulous organizations. This concept is known as Shadow AI, a burgeoning concern that arises from the unmonitored and unofficial use of AI tools and solutions within enterprises. AI, when properly managed, offers unprecedented efficiencies and insights; however, when employees or departments initiate AI projects without strategic oversight, risks can proliferate swiftly. For middle market CEOs, who often wear multiple hats within their organizations, the undetected skepticism towards unapproved AI tools might lead to data leakages, security vulnerabilities, compliance issues, and misaligned strategic objectives. The scope of this piece is to illuminate the somewhat invisible yet impactful presence of Shadow AI, decoding its implications, delineating its potential risks, and providing actionable insights for executives to guard against its repercussions. Engaging with this emerging challenge strategically allows mid-market organizations to harness AI’s potential effectively while ensuring alignment with organizational goals and safeguarding critical data. As we explore these themes, our focus will remain on equipping leaders with the essential knowledge to confront and manage Shadow AI, thus enabling them to steer their organizations confidently through these enigmatic waters.
Unveiling Shadow AI
Shadow AI refers to the unsanctioned use of artificial intelligence tools within an organization, often bypassing official channels and oversight. These hidden implementations are typically characterized by their operation outside the sanctioned IT frameworks and security protocols.
In middle market companies, shadow AI can manifest in various ways. Teams or departments might independently integrate AI solutions without consulting IT or management. This can occur out of a desire to increase efficiency or due to frustration with the speed of official AI deployment. Employees may use unauthorized AI tools to automate tasks or gain insights, relying on readily available online platforms or software to meet immediate needs.
Common scenarios include marketing departments using AI-driven analytics tools to track customer behavior or HR teams deploying AI to filter resumes. These initiatives, while well-intentioned, proceed without a comprehensive understanding of potential risks, such as data security breaches or compliance violations.
CEOs should be vigilant for early signs of shadow AI, such as sudden improvements in department-level productivity, unexplained changes in workflows, or increased data usage without corresponding IT projects. Regular audits and fostering open dialogue between departments and IT can help identify these implementations before they become problematic.
Shadow AI thrives in organizations lacking a coherent AI strategy. When there is no clear vision or roadmap for AI adoption, departments may take the initiative independently, believing they will fill the void left by leadership. This underscores the importance of having a detailed AI roadmap that guides adoption and aligns it with business goals, as explained in this AI roadmap resource.
The primary distinction between shadow AI and officially sanctioned AI initiatives is the level of visibility and control. Official AI projects are typically subject to governance frameworks, including data privacy, ethical guidelines, and compliance checks. In contrast, shadow AI operates in the shadows, without such oversight, leading to potential misalignments with the company’s strategy and values.
Addressing shadow AI requires a proactive approach, involving transparent communication, robust oversight mechanisms, and a comprehensive AI strategy that incorporates both top-down and bottom-up advancements.
The Risks Lurking in the Shadows
Shadow AI represents the unsanctioned use of artificial intelligence tools within organizations, often bypassing official protocols. This clandestine adoption introduces a host of risks for mid-market companies. One of the most pressing issues is data breaches. Employees might utilize AI tools without ensuring proper data security, leading to potential leaks of sensitive information. Unauthorized AI projects can inadvertently expose customer data, resulting in significant reputational damage and legal liabilities.
Failure to sanitize data before processing can also lead to a loss of valuable insights. Unsanitized datasets filled with inaccuracies, duplicates, or irrelevant information can skew AI outputs, leading to erroneous business insights that misguide decision-making processes. Understanding how to build AI-ready systems is crucial here and more about this can be explored here.
Compliance violations are another area where shadow AI poses a threat. Regulatory frameworks govern data usage, and non-compliance can result in hefty fines. Unauthorized AI projects often overlook these regulations, making businesses vulnerable to legal action.
Financial implications of shadow AI are profound. Without formal oversight, resources are wasted on redundant or ineffective projects that yield little return on investment. This lack of project management results in financial inefficiencies and can divert funds from more strategic initiatives. The absence of alignment with broader corporate strategies means that shadow AI initiatives often do not capture the economies of scale that could be achieved through coordinated approaches.
Real-world examples highlight the impact of shadow AI. A mid-market retail firm attempted to implement AI-based customer analysis without consulting their IT department. The project led to a significant data breach, costing the company millions in fines and loss of consumer trust. Another example involved a logistics company that initiated an AI-driven supply chain optimization project without upper management’s knowledge. The result was a misalignment with existing systems, leading to operational disruptions and increased costs.
To navigate these risks, mid-market CEOs must diligently identify and manage unsanctioned AI activities. Establishing clear AI governance and fostering a culture of transparency can mitigate these threats and pave the way for secure AI adoption.
Strategies to Illuminate the Shadows
To combat the risks of Shadow AI, mid-market CEOs must prioritize transparency and collaboration across their organizations. Start by instituting comprehensive policies that mandate the documentation of all AI initiatives. This visibility ensures that no project remains in the shadows, potentially violating compliance or straying from strategic goals.
Establish cross-departmental committees to oversee AI adoption. These committees should include representatives from IT, legal, compliance, and business units. Such diversity ensures multiple perspectives in assessing AI’s impact and risks. Moreover, implementing an AI governance framework can streamline these efforts. This framework should define roles, responsibilities, and reporting structures to enhance accountability.
Building a culture of transparency is equally essential. Encourage open discussions about AI projects within the company. Regular town hall meetings and workshops can demystify AI for non-technical staff and invite input from all employees. This inclusive environment not only identifies hidden risks but also harnesses diverse ideas for innovation.
Effective communication between IT and other departments is critical. Set clear protocols for how technical teams should interact with business stakeholders. Translating technical jargon into relatable business impacts can bridge gaps in understanding. Furthermore, establish regular check-ins between teams to monitor progress and challenges, preventing any potential divergence in AI deployment strategies.
Consistent training programs for employees can also play a vital role. These programs should focus on AI literacy and ethics, enabling staff to recognize and address potential threats. By integrating feedback loops into training, organizations can continuously update their learning modules based on real-world experiences.
Finally, CEOs should be aware of their organization’s data integrity. Poor data quality can exacerbate Shadow AI risks, as explored in this guide on building AI-ready systems. Ensuring data is accurate and reliable means AI models can provide trustworthy insights, strengthening their alignment with corporate goals.
In conclusion, while Shadow AI poses challenges, a strategic approach to visibility and collaboration can mitigate these risks. By fostering transparency and ensuring comprehensive governance, mid-market CEOs can harness AI’s potential while safeguarding their business’s integrity.
Crafting a Proactive AI Strategy
Developing a comprehensive AI strategy is crucial for aligning AI initiatives with corporate goals and preventing the rise of shadow AI. Unchecked, shadow AI projects can lead to operational inefficiencies, security vulnerabilities, and ethical breaches. A well-crafted strategy helps ensure AI implementations serve business objectives responsibly and effectively.
To begin, assess your organization’s current technological capabilities and resources. This evaluation should encompass your data infrastructure, talent pool, and existing AI tools. Understanding the baseline allows for realistic goal-setting and identifies gaps that necessitate immediate attention. In parallel, assess organizational readiness by analyzing cultural receptiveness and potential resistance points to AI adoption.
Establishing clear AI priorities is essential. Identify projects that offer the greatest value and align with your enterprise’s strategic goals. Whether optimizing supply chain processes, enhancing customer interactions, or improving decision-making, concentrate on initiatives that drive competitive advantage. Resources like this AI roadmap guide provide further insights into effective AI scaling.
Involving key stakeholders from the outset strengthens the strategy’s adoption and impact. Gather a diverse group of leaders from various departments, including IT, operations, legal, and compliance. This inclusive approach ensures that diverse perspectives are incorporated, accounting for all potential risks and benefits. Moreover, regular stakeholder engagement fosters a sense of ownership and accountability across teams.
Furthermore, establish clear guidelines and governance structures to manage AI ethics and compliance. This framework should detail data privacy protocols, model transparency standards, and accountability measures. Continuous training and awareness programs help sustain an organization-wide understanding of AI ethics, reducing the risk of unauthorized or unethical AI usage.
By meticulously planning and executing an AI strategy, mid-market companies can harness AI’s potential while mitigating risks. A proactive approach not only shields organizations from the pitfalls of shadow AI but also empowers them to leverage AI innovations responsibly, achieving sustainable success.
Final words
Navigating the landscape of AI within the middle market can seem daunting, with Shadow AI presenting a set of hidden challenges that require astute management and oversight. By systematically illuminating the potential risks posed by unauthorized AI usage, middle market leaders can ensure their organizations capitalize on AI’s full potential while maintaining security, compliance, and strategic alignment. Unlocking the potential of AI involves more than just deploying technology; it requires a diligent strategic approach that encompasses governance, transparency, and a deep understanding of company-wide AI aspirations. As these businesses move forward, they are encouraged to leverage the power of strategic partners and expert advisors to integrate AI in a way that is both innovative and safeguarded against unforeseen pitfalls. Remember, managing the hidden risks of Shadow AI not only protects your company in the present but sets a strong foundation for future growth and success in a rapidly evolving technological landscape.
Ready to accelerate your AI journey? Velocity Road helps companies like yours navigate AI adoption with clear strategy and execution. Let’s talk about how we can drive impact together. Schedule a consultation today.
Learn more: http://www.velocityroad.wpenginepowered.com
About us
Velocity Road is a cutting-edge AI consulting firm specializing in enterprise transformation through strategic AI adoption and workflow automation. Our team helps mid-market and private equity-backed companies navigate the complexities of AI, optimizing operations, enhancing productivity, and driving measurable business impact. By integrating AI-powered solutions, developing custom automation agents, and delivering tailored training programs, we ensure organizations unlock the full potential of artificial intelligence. Whether streamlining processes, identifying high-value AI use cases, or building scalable AI roadmaps, Velocity Road provides the expertise and strategic guidance needed to stay competitive in an increasingly AI-driven world.
Harnessing Automation: A Strategy for Middle-Market Profitability
With increasing competition and tightening margins, middle-market CEOs face the challenge of maintaining profitability. Automation presents a viable solution, offering efficiency gains, cost reductions, and an overall boost in productivity. As private equity investors support these CEOs, understanding how automation can be effectively implemented becomes crucial. By leveraging suitable automation technologies, middle-market companies can unlock significant value, ensuring optimal resource utilization while enhancing service delivery. We will explore how private equity-backed companies can strategically apply automation to drive profitability, evaluate the key areas for automation, and offer insights into crafting a seamless transition journey towards an automated future.
Identifying Key Areas for Automation
Middle-market CEOs must strategically pinpoint where automation will have the most substantial impact. First, assessing repetitive processes across departments is essential. These tasks often involve manual data entry, reporting, or customer support activities. Automating such processes can significantly reduce human errors and enhance consistency in outputs. By mapping these processes, companies can identify where automation brings precision and time efficiency.
Next, high-volume tasks are prime candidates for automation. These include areas like supply chain management, inventory control, and transaction processing. In these cases, automation can scale operations without corresponding increases in labor costs. This scalability leads to greater flexibility in responding to market demands and can dramatically improve turnaround times.
Data-rich environments are also ripe for automation. These environments often include financial modeling, forecasting, and performance metrics evaluation. Automation technologies like artificial intelligence and machine learning can analyze vast datasets faster and more accurately than manual methods. Implementing these technologies offers actionable insights and predictive analysis, allowing better strategic decision-making.
Conducting comprehensive audits is vital for identifying these areas. These audits should evaluate the efficiency of current processes, assess technological capabilities, and determine potential cost savings. Engaging third-party consultants can bring an unbiased perspective and expert insights into the audit process. Additionally, leveraging interdisciplinary teams within the company can help in identifying nuanced and overlooked areas suitable for automation.
Automating these key areas results in direct and indirect benefits. Companies can lower operational costs, increase productivity, and free up human resources for creative problem-solving and strategic activities. Improved service delivery becomes a reality as processes run smoothly without human-induced delays. Moreover, automation allows for better compliance tracking and error monitoring, reducing risks of regulatory setbacks.
For middle-market enterprises, starting small can lead to incremental successes that build confidence in automation. As seen in resources like how mid-market companies can identify their best AI opportunities, such approaches help in gradually scaling automation initiatives. Ensuring readiness for AI and automation while aligning with business goals can position companies for long-term profitability.
Implementing Automation: Tools and Techniques
Robotic process automation (RPA) stands out as an essential tool for mid-market enterprises aiming to streamline operations. It automates rule-based tasks, freeing up human resources for more strategic work. CEOs should assess how these tasks align with their core objectives to determine RPA’s fit. Similarly, AI-driven analytics offer predictive capabilities that enhance decision-making. These analytics tools provide insights derived from past data trends, improving both strategic planning and operational efficiency.
Machine learning algorithms further push the boundaries by identifying patterns that humans might overlook. This adaptability allows middle-market firms to refine operations consistently. Choosing the right machine learning tools depends on understanding the specific problems these enterprises need to solve. For CEOs, aligning these solutions with company objectives remains vital, ensuring technology investments deliver the expected returns.
The adoption of cloud-based solutions has become a cornerstone for scalable and flexible automation. These solutions enable businesses to manage increasing workloads seamlessly. Cloud technology also supports collaborative tools, facilitating better communication and project management across the enterprise. This infrastructure can be advantageous for mid-market firms, offering scalability without significant infrastructure investments.
To ensure successful implementation, companies must foster cross-functional teams. These teams include IT professionals, operational managers, and department heads who oversee integration efforts. Cross-discipline collaboration guarantees that automation solutions address the organization’s broader needs and objectives. This collaboration diminishes resistance by involving stakeholders in decision-making processes and fostering a shared vision for technological progress.
Selecting the right tools requires a deep understanding of the company’s operational landscape. CEOs should prioritize tools that offer not just a tactical advantage but also strategic improvements. Assessing the potential impact of automation on productivity, cost, and market responsiveness is crucial. Consulting resources such as employee training adoption can provide insights into preparing teams for this transition.
Overall, a strategic focus on the right automation tools and techniques can significantly enhance the profitability of private equity-backed enterprises. A successful automation strategy, therefore, hinges on careful tool selection, cross-functional collaboration, and a clear alignment with company objectives.
Measuring Success and Adjusting Strategies
Implementing automation in private equity-backed enterprises requires more than installation; it demands effective evaluation. Measuring success through data analytics and performance indicators provides insights into financial and operational impacts. Key metrics such as cost savings, productivity improvements, and return on investment (ROI) are pivotal.
Cost savings highlight direct financial benefits by comparing pre- and post-automation expenses. Reductions in labor costs and error rates translate into tangible figures reflecting automation’s economic value. Productivity improvements, on the other hand, showcase operational efficiency. Metrics such as output per hour and task completion times offer insight into gains made in workflow and throughput. These improvements often signal that automation is reducing bottlenecks and enhancing overall capabilities.
ROI provides a comprehensive view of automation’s financial efficacy, relating net returns to the initial investment. This metric allows for the evaluation of automation projects against traditional approaches. Higher ROI signals better allocation of resources, ensuring that the enterprise gains substantial value from its initiatives.
CEOs can leverage analytics to pinpoint areas ripe for further optimization. Adjustments might involve scaling successful elements or reevaluating underperforming aspects. By setting benchmarks and regularly assessing key performance indicators (KPIs), businesses can align automation efforts with strategic goals. For instance, if a specific process automation results in unexpected delays, root causes can be addressed promptly to mitigate future issues.
The continuous improvement cycle is critical. Analyzing data trends ensures that strategies remain responsive to business objectives. CEOs can adopt agile methodologies to instigate iterative enhancements, fostering a culture of responsiveness. This can lead to adaptation and increased competitiveness in the market.
For an in-depth look at identifying AI opportunities that can further drive profit, consider exploring how mid-market companies can refine their focus here. Aligning automation with broader AI strategies can significantly amplify enterprise value, ensuring investments pay dividends well into the future.
Final words
Automation presents middle-market companies, especially those backed by private equity, with a transformative opportunity to enhance profitability. By strategically identifying areas for automation, implementing the right technologies, and continuously measuring their impact, CEOs can significantly improve their operational efficiency and cost-effectiveness. Automation is not merely a trend but a necessity to stay competitive. It requires commitment to innovation, investment in the right tools, and a proactive approach to change. The journey to an automated, efficient enterprise promises substantial rewards for those willing to embrace the challenge.
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About us
Velocity Road is a cutting-edge AI consulting firm specializing in enterprise transformation through strategic AI adoption and workflow automation. Our team helps mid-market and private equity-backed companies navigate the complexities of AI, optimizing operations, enhancing productivity, and driving measurable business impact. By integrating AI-powered solutions, developing custom automation agents, and delivering tailored training programs, we ensure organizations unlock the full potential of artificial intelligence. Whether streamlining processes, identifying high-value AI use cases, or building scalable AI roadmaps, Velocity Road provides the expertise and strategic guidance needed to stay competitive in an increasingly AI-driven world.
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