Thought Leadership on AI & Tech Leadership

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Four colleagues seen from behind stand at a sunlit window looking out over a landscape of rivers and roads that differs from the paper map on the table, with five colored paths fanning toward the horizon.

The Competitor That Frightens You Most · Your Case for Transformation

Every leader has a quick answer for which competitor scares them most, and that speed is the problem. This piece maps five competitor types along a stewardship-to-exploration spectrum, with a scoring exercise to test your own blind spots before deciding whether to transform.

Four colleagues seen from behind in a sunlit office look at a wall display where a large stream of gray dots passes through a funnel and becomes three highlighted amber cards.

The CVE Vulnerability Flood is Good News · Here’s Why

A record CVE count sounds like a crisis, but FIRST’s own data says otherwise: AI is finding old flaws faster, not creating new ones. And it’s doing so for the good guys. The real risk is a prioritization gap, not the raw number. Here’s the filter that matters, and the one question a CEO should ask Monday.

Three colleagues, seen from behind in a bright sunlit open office, gather around a large glass wall panel where glowing abstract tiles from many different sources flow together into one unified view, representing a company building a single pane of glass for its data.

A Single-pane View Has Never Been Easier – Taking the AI Shortcut

If you shelved enterprise software while AI reshaped the build-versus-buy math, the delay may have paid off. This piece weighs the real evidence on cost, productivity, and code quality against the case for a custom single-pane view, and lays out the guardrails and a 90-day way to test it.

An empty high-backed leather chair at the head of a long, dark boardroom table, with a ring of heavy brass keys glowing amber on the left and a web of glowing teal pathways stretching from the right toward a distant city skyline, representing a CIO's seat that must both run the platform and move AI forward.

Only 11% of CIOs Are AI Vanguards · What to Do If Yours Isn’t (Yet)

Gartner finds only 11% of CIOs are AI Vanguards who deliver real business value from AI. The seat now asks for two jobs: run the platform and move AI forward. When one person can’t do both, the fix is about the seat, not a verdict on the person in it.

A dim office corridor at night lined with identical dark doors, one glowing amber with a bright keyhole and thin teal threads of light running from it across the floor to several of the other doors, representing unseen AI agents moving between company systems with no one keeping track.

Less than a Third of AI Agents are Governed · Why Mid-market CEOs Should Care

Most AI agents at mid-market companies have no owner, no access limits, and no one watching. Gartner finds only 21% of organizations are positioned to govern them. The fix is five cheap, boring steps, starting with a list of what is already connected.

Analytics Maturity Survey of Mid-Market industries

Our 2026 Mid-market Analytics Maturity Survey

This annual benchmark shows how far mid-market companies in 18 industries have come in data, BI and AI maturity. The 2026 result is a structural lag behind enterprise, so check where your industry and revenue band stand.

A blank sheet of paper and a pen on a dark leather desk at dusk, with a clear pane of glass floating above the sheet revealing glowing amber and teal layers beneath it, including a small set of balanced scales, representing the hidden tradeoffs inside an ordinary decision.

Want to Capture the AI Dividend? You Must See the Tradeoffs Clearly

A renewal’s summary page shows what a decision costs, not what it trades away. AI makes that blind spot expensive, because the savings it creates go to whoever sees the tradeoffs first. A decision ledger puts them on the page, one choice at a time.

Is Your Low-Hanging AI Fruit on the Right Tree? In the Right Orchard?

Easy AI wins are tempting, but a self-contained process is only worth automating if it will still matter in a few years. Check the process’s future before its complexity. The real payoff of an early project is the governance and measurement habits it teaches, not the savings.

A long, dark industrial corridor of identical doorways receding into the distance, with the two nearest doorways on the left glowing amber while the matching doorways on the right and farther down stay dark, representing a staggered rollout where teams not yet live serve as the comparison group.

The Control Group Is Gone · How to Prove AI Works When Nobody Will Work Without It

Once a team won’t work without an AI tool, you’ve lost the group you’d compare it against. Prove the value while you still can. Stagger the rollout, count work at intake, check what people say against your system records, and decide up front what result would change the plan.

An empty boardroom conference table seen from directly overhead, shrouded in shadow except for a single sharp cone of spotlight illuminating one empty chair at the head of the table, representing the accountability question every board is now asking about AI oversight.

The 9% Problem · What Your Board Actually Wants to See on AI

Your board is about to ask who is accountable for what your AI does, and how you would prove it. Nine percent of your peers could answer today. Build governance in the right order, and get an independent look at which stage you are in.

A dim leadership meeting room seen from the end of a long wooden table, with five tall vertical light columns on the far wall filled to different heights in teal and the shortest one glowing amber, representing a five-number technology scorecard with one measure off track.

Including Tech in the Weekly Meeting · 5 Metrics for Companies with an Operating System

Your weekly scorecard probably has no technology line, and that is a design gap, not neglect. Add five technology numbers to the meeting, starting with baselines and thresholds. If the count is still zero by Monday, that is your first item on the Issues List.

A grid of identical steel precision instruments laid out in dim shadow, with one instrument near the center lifted and lit by warm golden light, representing the difference between commodity tools and the scarce judgment to use them well.

Cheap Tools, Scarce Judgment · Why Outside Expertise Has Never Been More Valuable

AI tools get cheaper every quarter, but the experience to use them well does not. That makes now the moment outside expertise is worth the most. Start small with an assessment or one month of advisory service.

If Your Tech Budget Looks Like Last Year’s, You Missed the Turn

Last year’s tech budget plus a percentage no longer works. What technology costs, how it is priced and who answers for it have all changed. Rebuild the budget row by row, and name who owns each decision.

An aged topographic contour map glowing faintly in deep indigo and slate blue, with a single hand-drawn amber route winding from the lower foreground up through misty valleys toward a bright point of light on a distant ridge, representing a mindset that has been given a path to follow.

Yes But We Need a Path · Innovating Beyond Efficiency vs. Singularity Teaching

A mindset without a path is a very expensive notebook. Singularity University’s Executive Program teaches why to think exponentially; Innovating Beyond Efficiency supplies the path from the why to the work. Take the why seriously, then build the path.

A single beam of light scanning across a row of vendor storefronts, representing an AI agent silently evaluating and shortlisting suppliers before a human buyer ever makes contact.

Trust Sold Your Last Deal · An Algorithm Is Scoring Your Next

Trust won your last deal, but an algorithm may score your next one before anyone calls you. Ask three questions this quarter about what an agent actually sees when it looks at you. Buyers who no longer pick up the phone are 38 percent of the room today.

The 2026 AI Dividend Map · 25 Industries, 4 Shapes

This annual map scores 25 industries against three customer gates and places each in one of four shapes. Find yourself twice, once for your market and once for the mix inside your own company. Then read what to do from your seat under each shape.

Shapes of the AI Dividend · Rising Bar vs. Falling Floor

Weighted by payroll, fewer than one in twenty-five jobs faces winner-take-all AI, but unlocking the dividend is not capturing it. Find your shape, name the force closest to your margin, and learn whether the line is moving at working speed or buying speed.

Tracking AI EBITDA is all about choosing a metric

Proving AI EBITDA · Metrics That Boards Actually Believe

When the CFO asks how you know the result was the AI, an aggregate number will not hold. Carry one measure all the way through, and take the baseline now. A before-picture cannot be recreated later, only argued about.

Technology Can’t Transform the Business Alone

Technology teams cannot transform a business alone, because much of what decides success sits outside them. The CIO is accountable for the outcome without owning most of it. A major transformation creates a temporary organization inside the permanent one, and leading it takes influence rather than authority.

Team “Still Not Ready for AI”? · Readiness Is Designed, Not Awaited

Waiting for your team to be ready for AI misreads readiness, which organizations design rather than wait for. The earlier deferral was right, and starting now is right too. Treat readiness as design work your leadership team already knows how to do.

Your Next Customer Won’t Be Human · MCP and the Rise of Agent Docks

Your next customer will probably arrive as software, a buyer’s agent that already tries to read your company and gets it wrong. Build an Agent Dock so those agents find current facts and terms. Do it while traffic is light.

Orchestrating an AI team

One AI assistant stops being enough as a workflow grows, so the work moves to specialized agents under orchestration. Each system still needs accountability above it. The future is an orchestrated AI team inside a business system built for measurable outcomes, with leadership deciding what good work means.

Maximizing Your AI Investment · From Efficiency Traps to Hybrid Intelligence

Stopping at efficiency is why so many AI projects fail to pay back. The winners use hybrid intelligence to augment the people who understand their industry and to rewrite its economics. They fund the effort with 18-month quick wins.

Traction or (Dis)traction? AI Strategy as a Lens for Alignment

The flood of AI announcements turns into distraction when you have not decided where you are going. Strategy is the lens that lets you check each new tool against the map in minutes. Decide your direction first.

The Best of Both Worlds · Balancing Citizen AI Exploration with Production AI Rigor

Citizen AI exploration and governance are two different organs, not opposite ends of a spectrum. Give people a license to explore, bounded by governance, plus a pipeline that promotes what works. Prohibition only breeds outlaw AI on personal accounts.

The AI Rorschach Test & the High Cost of Presumption

The leader who froze hiring on faith in AI and the leader who keeps it at arm’s length are both presuming, not measuring. The only way out is to start exploring. Run a pilot and measure one workflow.

From AI Strategy to AI EBITDA · The Board Shift Most Mid-Market Consulting Has Missed

Your board has moved from asking about AI strategy to asking where the EBITDA is in the CFO’s quarterly numbers. A strategy deck cannot answer that. Build an AI EBITDA narrative that traces the money, including where the AI dividend leaks.

Human in the Loop or Rubber Stamp? · Achieving Real AI Oversight

If your reviewer just glances at AI output and clicks approve, you have a rubber stamp, not a human in the loop. Real oversight is one of the highest-return AI moves, and the back office is the right place to start.

Last Year Your Competitors Subscribed to AI Tools · Now They’re Hiring Them

AI has shifted from a per-seat tool to something closer to a hire, and this transition is bigger than the last. The window where it is an advantage rather than table stakes is open now, and it will not announce its closing. Start deciding what your AI workforce should look like.

Innovation is a Process · What 3 Months of Successful Production AI Actually Looks Like

Most CEOs cannot picture the next ninety days of their AI program, because every version they were sold is shaped like a project. Replace it with a three-month process: map the field first, then build the freeway and harden one real thing, then prove it.