Thought Leadership on AI & Tech Leadership
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Latest !nsights from our Experts
Beyond the Hype · How CIOs and CTOs Can Turn AI into a Strategic Advantage
Every board now asks for an AI strategy, and CIOs and CTOs are expected to answer it. The bigger opportunity is to lead the conversation about what AI should and should not do, backed by a governance framework.
Doom & Gloom or Wine & Roses? The Spectrum of AI Predictions, and Ours
The people building AI disagree on paradise or extinction, but they agree on how big the change is and how soon. Which outcome your company gets depends less on prediction than on preparation. Start with the spectrum, then study the Great Repricing, which will shape your margins, roles and pricing power.
Strategies for Executing Your Technology Roadmap
A strong technology roadmap is a focused plan for how technology supports revenue and growth, not a list of tools or pet projects. Plan adoption, not just delivery, with training and local champions as explicit tasks. Choose which AI ideas get a pilot and which wait.
The Rack of Reinvented Wheels Running Your Company
Employees run critical workflows in their own AI accounts, undocumented and unmanaged, a rack you would never tolerate in a server room. Banning it does not work, so take inventory and run it like infrastructure. Decide what graduates to production.
The Sector-Specific Governor on AI Innovation · The Cost of Being Wrong
The real brake on how fast your sector adopts AI is the cost of being wrong, not the regulator. That cost varies by orders of magnitude across sectors, so tune your own governor and move faster than peers who never questioned theirs.
Vendor Partnerships in the Era of AI Arbitrage
Vendors are quietly capturing the spread between AI-compressed costs and pricing anchors that have not moved. Check vendor proposals against that lower cost, because firms that move first capture the gain. The window will not stay open.
The AI ROI Problem Is Not the Model · It Is the Operating Model
The AI value problem has not stalled because the models are weak; it has stalled because organizations have not redesigned the work. Rebuild the workflows that actually produce EBITDA before the next company in your sector does. The model conversation is no longer sufficient for boards and operators.
Within a Decade You’ll Be Able to Buy Competitors for Pennies
The right AI question is not which functions to automate but what your company will be worth in 2032. Five components of value are at stake: revenue multiple, EBITDA margin, customer relationships, proprietary data and IP, and brand and trust equity.
We’re All Becoming Cyborgs 1.0 · We Just Don’t Realize It
Using AI to draft, critique and reframe your own thinking is a form of augmentation, and the line was crossed so quietly that few noticed. The cyborg era has begun, and version 1.0 is live. Organizations that see it now will build the version of themselves this era rewards.
Your Employees Are Already Using AI. You Just Don’t Have a Strategy For It Yet.
The next phase of AI leadership in mid-market companies is about visibility, not adoption. Your employees have already done the hardest part by experimenting on their own. Find out what AI is already happening inside your walls, and make that work count.
Cybersecurity & the AI Ecosystem
AI expands your attack surface in ways traditional cybersecurity frameworks often overlook. The AI ecosystem includes far more than the models themselves, so understanding these risks is now part of enterprise risk management. Treat cybersecurity as an enabler of responsible innovation, not a cost center.
Stronger Together Was a Slogan · Now It’s a Strategy Requirement
Business strategy, AI and technology only compound into a position when they are unified, and two out of three does not work. Companies that keep them separate are choosing a slower failure. Treat unification as a strategy requirement, not a slogan.
You Get One Counter-Punch to a Competitor’s AI · Make it Count
When a competitor announces a major AI capability, both the panic response and the freeze response lose. The winners spend the first 72 hours widening their options while rivals narrow theirs. Broaden your horizon of possibilities before you jump.
AI Usage is Still Basic · What the First Large AI Usage Study Didn’t Find
AI usage is still basic, and the first large usage study measured access, not depth. The race is how quickly you move from transactional use to structural integration, from asking to building. Measure the move from conversations that end to systems that keep running.
Superfluous Be Gone · Inefficiencies AI is Destroying
AI is quietly dismantling the friction, opacity and institutional advantages that have shaped business for decades. Information asymmetry, the billable hour, the middle tier and credentialism are all in play. Audit which of your advantages survive a world with radically less friction.
The Innovation Dividend · Why the Right Projects Pay You Twice
The standard ROI calculation treats every project as isolated, but the best investments change the math for the next one. Ask whether a project justifies its cost, and also whether it makes the next one cheaper, faster and more likely to succeed.
Innovation is a Process: Project Vista®
Innovation is a process, not lightning that strikes, and the process has a shape. Divergent ideation widens the field on the left, convergent prioritization narrows it on the right, and a hinge point joins them. Project Vista is built on that shape.
Better to Be the 1st or 2nd AI Mover in Your Sector? Yes.
Whether to move first or second on AI depends on which scenario you are in, not on the old fast-follower rule. The deciding variable pairs information intensity with implementation complexity. Know your scenario before you choose a position.
Measuring Tech Monetization
AI makes ROI attribution harder than ever, because it augments people and arrives alongside many other changes. Set baselines and choose an attribution approach, such as before and after, A/B cohorts or regression, before the tool goes live. It costs a few extra hours of planning.
Taming the Agentic AI Genie · Real-world Governance for the Mid-market
Your employees are already using agentic AI, whether your governance framework acknowledges it or not. Design governance as a freeway, not a roadblock, so guardrails enable speed. Govern it well enough to capture the value safely.
The End of Cross-references · The Taxonomy AI Superpower Nobody is Talking About
AI can now work across systems that label the same information differently, which takes the pain out of definition fights. Stop waiting for your industry to agree on categories. Use your data instead of endlessly preparing it.
Why Most AI Projects are Failing, and How to Beat Those Odds
Most AI projects fail because organizations bolt transformative technology onto foundations that were never built for it. Data readiness and the org chart are the obstacles, so align AI with IT first. Fix the foundation before you add more pilots.
Every Company is in a Race in 2026, but Very Few Even Realize It
The bigger opportunity in Pokémon Go was the data its players built without knowing it, and your business may be hiding a similar asset. Look for architectures where your data asset grows stronger through the very act of being used.
The One Thing New CEOs Can’t Get From Their Own IT Team · An Honest Tech Assessment
New CEOs inherit technology they did not build, and an inside view is shaped by history and self-interest. An independent, vendor-neutral assessment in the first 90 days gives you the truth early enough to act. Lead with clarity rather than assumption.
How Change Management Works in the Real World, Where There Are Things Like Budgets
Most change initiatives fail because the frameworks were never designed for the budgets and constraints most companies actually face. Treat the budget as a design input, not a detail, and test any approach where the gap between theory and practice is widest.
When the World’s Biggest Firms Ignore Their Own Advice
Bloomberg spent $10 million on a custom language model that a general-purpose commercial one then outperformed. Even McKinsey and Samsung could not outrun commercial AI providers in zones where those providers hold every incentive. Check where you are building against vendors who keep advancing.
The Great Repricing · AI’s Coming Impact on Labor & Money
The coming AI disruption is less about jobs than about the price of thinking and the price of money. Repricing rewards the early and punishes the late, so prepare clear-eyed now rather than restructure in panic.
Innovation is a Process · Opportunity-space Matrices
Most companies start with a solution and hunt for a problem, which yields the same cost-reduction list every competitor has. Build an opportunity-space matrix so your team looks in all the places ideas might be hiding.
Beyond Sleeping at Night · Information Security as Strategic Advantage
Doing just enough on information security to sleep at night leaves you with minimal compliance and a stagnant posture. Treat security as a strategic advantage, a moat competitors cannot easily cross, because digital trust is becoming the primary currency.
Why Popular Innovation Frameworks Fail the Mid-Market
Popular innovation frameworks are serious work, but they cannot fix an organization that only asks how to cut cost or improve efficiency. Change the questions your company asks about technology before you adopt another methodology.