How ready is your company for AI? Learn from CVS' mistakes.

One year in, McKinsey shares six lessons from those working hands-on with agentic AI. A grounded view of what’s been learned so far — and where challenges remain. My 5 cents: success will depend less on the tech itself and more on how organizations adapt their ways of working

In my recent article in Fast Company, I dive into a question every leader should be asking: “Is your AI strategy making work easier or just adding another layer of complexity?” Despite all the technical breakthroughs, true success with AI across the enterprise isn’t just about specs or features, it’s about trust and adoption. The most effective AI meets people where they already work. It integrates seamlessly into existing workflows, surfaces inefficiencies you didn’t even know existed, and turns insights into action. I explore why the AI revolution won't be about the technology itself, but about why it hinges on employee adoption and our willingness to partner with it to simplify work. Read the full piece here: https://lnkd.in/gDt8tn_r

“…These stumbles are a natural evolution of any new technology, and we’ve seen this pattern before with other innovations. To understand the early lessons, we recently dug into more than 50 agentic AI builds we’ve led at McKinsey, as well as dozens of others in the marketplace. We’ve boiled down our analysis results to six lessons to help leaders successfully capture value from agentic AI…“

If you’re leading a team right now, you’re probably thinking about how AI will change the way your people work. That’s the right question — but how you solve it depends entirely on the kind of work they’re doing. Some work is everyday stuff — repeatable, procedural, easy to automate. Other work is deep thinking — creative, judgment-based, where the real value happens. The mistake many leaders make is treating both the same when they think about AI. You shouldn’t. This short video breaks down that difference — and helps you see where AI can free up your team’s time vs where it should amplify their judgment 🎥 Watch the 2-minute video: https://lnkd.in/eKkzfN9T 📝 Read the blog for a deeper look: https://lnkd.in/e8nFD_X6 💬 Join the live Q&A webinar to talk it through: https://lnkd.in/eAM43B2v

Most companies don’t fail at starting with AI. They fail at scaling it. Here’s why: Shiny tool syndrome → Chasing the newest AI tool without a clear strategy. No integration → AI pilots that never connect with existing workflows. Lack of training → Teams aren’t equipped to actually use the tools effectively. Data issues → Poor data quality = poor AI performance. Scaling AI isn’t about having more tools. It’s about alignment: strategy, systems, and people all working together. The companies that win with AI in 2025 won’t be the ones experimenting the most — they’ll be the ones who turn experiments into everyday impact.

📰 Just came across this article, and it’s too good not to share. AI alone won’t fix broken processes or poor culture. With no solid foundation, even the best tools won’t deliver results. But when strong processes, healthy culture, and clear direction are already in place, modern AI and agentic coding can act as a multiplier of success. From my perspective, this is the real challenge for many companies today. It’s easy to get distracted by shiny new tools, but the harder — and more valuable — work is in building a system where people, processes, and strategy are aligned. Only then do technologies like AI create lasting impact, instead of just another hype cycle. Original link: https://lnkd.in/dX8QVFPQ

Here’s a number that should wake you up this morning: 78% of organizations are now using AI in at least one business function—up sharply from 55% last year. But here’s what’s more interesting - up to 74% (and possibly more) are struggling to scale beyond pilots, with some studies indicating as many as 95% of generative AI pilots at large companies aren’t delivering full-scale impact yet. The AI revolution isn’t about who adopts first. It’s about who implements smartly. Recent data shows companies that successfully scale AI report productivity gains of 15-44% and 6-10% revenue growth, especially in priority functions like customer operations, marketing, and product development. The global AI market hit $244–254 billion in 2025, projected to reach $827 billion by 2030 at a 27.7% annual growth rate. Yet the gap between adoption and value realization remains massive. The difference? Strategic focus on high-impact areas, robust data quality, and workforce training. Here’s the contrarian insight: More AI isn’t always better AI. Companies seeing real ROI are those solving specific problems with targeted solutions - not just chasing every shiny new tool. The $15.7 trillion question for 2030 isn’t “Are you using AI?” It’s “Are you using AI strategically?” What’s one AI implementation in your organization that actually moved the needle? Ready to implement AI strategically? https://lnkd.in/gRVF62QP

Here’s the thing about AI: the more layers you add, the more fragile it gets — unless your foundation is rock solid. Want to scale AI with confidence? Start with clean data, clear roles, and simple, measurable pilots. Then keep going — iteratively. In our blog, Start Small, Think Big: Scaling AI with Confidence, Matt Zarek shows you how to build momentum without getting buried in hype (or half-finished pilots). Read it now: https://hubs.la/Q03G5t3Q0 If you could automate one process tomorrow with AI, what would it be? Drop your dream use case below! #AIMaturity #AIImplementation #FutureOfWork #Innovation #dreamdesigndeliver #ThisisCompugen

If you're leading an AI initiative and haven’t read MIT's State of AI in Business 2025 report, you're flying blind. The report makes one thing painfully clear: Most businesses aren’t adopting AI properly. The failures aren’t about bad models. They’re about bad bets. Misaligned tools, performative pilots, and tech for tech’s sake. It’s a reality check for leadership. The report shows where AI is actually working and where it’s just lighting money on fire. In our latest SNACKS post, we break it down and explain how YOR.AI is staying on the right side of the GenAI Divide. Building real systems, solving real problems, and skipping the vanity. Link to the MIT Report in the post! #AI #GenAI #AIBlueprint #DigitalStrategy #AIforbusiness #MITAI #OperationalAI  #WorkflowAutomation #TechLeadership #AIImplementation #YORAI #AIThatWorks https://lnkd.in/g6FfW5AP

95% of companies are getting nothing from their AI investments. Not because the tech is broken, but because the approach is. This is what MIT’s State of AI in Business 2025 report sheds light on. It shows where AI is actually working and where it's just setting money on fire. Our latest SNACKS post at YOR.AI highlights the wins that matter and how we’re staying out of the graveyard of demos, wrappers, and science projects. Building what works. Link to the MIT report is in the post!