Month: July 2026

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The One Diagnostic Step Every Failed AI Rollout Skipped

There are two ways a board loses confidence in a CEO’s AI strategy. One is watching a rushed rollout blow up in public. The other is watching nothing happen, quarter after quarter, while rivals pull ahead. Leaders treat these as opposite sins — one of recklessness, one of paralysis. They are the same sin wearing two costumes.

Consider a government vehicle-inspection office. For years, getting a car certified meant a wasted morning: unexplained queues, arbitrary waits, a process nobody could explain and everybody dreaded. The clerks weren’t the problem. They were as trapped in the system as the drivers standing in line.

When the office was finally redesigned, the fix didn’t come from the counter staff working harder. It came from above — from leadership finally treating the process itself as something to be mapped, tested, and rebuilt. Decades of avoidable frustration turned out to be a leadership failure wearing a service-counter disguise.

That’s the pattern behind almost every stalled or embarrassing AI rollout today: cause and effect get separated. The department that visibly breaks is rarely the one that made the mistake. The quarter where the failure shows up is rarely the quarter where it was made. That lag is exactly why the rushed CEO and the frozen CEO can’t see they share a cause. Skip the diagnosis, and the bill arrives later — as a scrapped pilot, a quiet rollback, or a board that’s run out of patience. Each time, it looks like an isolated, unrelated event. It isn’t.

The Proof Is Piling Up

This isn’t a resource problem, and it isn’t confined to one company, sector, or country.

Starbucks spent nine months running an AI tool meant to automate beverage-inventory counts across its North American stores, before quietly retiring it after the system kept miscounting and mislabeling items, such as confusing similar milk types. Ford has been rehiring and promoting more than 350 experienced engineers after automated quality-control systems failed to capture the expertise of veteran employees. Commonwealth Bank of Australia replaced dozens of customer-service staff with an AI voice bot, then had to reverse the job cuts when the system couldn’t keep up and call volumes climbed. IBM automated large parts of its HR function, discovered the tool could resolve routine requests but stumbled on anything requiring judgment, and announced plans to triple its U.S. entry-level hiring soon after. A widely cited MIT study found that 95% of enterprise generative AI pilots fail to deliver measurable returns.

None of these were companies short on capital, talent, or enthusiasm. Every one of them had the AI capability. What none of them had was a diagnosis of the underlying process before the tool was chosen.

What Got Lost

That’s understandable, in a way. Most companies today are wide open to AI because their own stakeholders are demanding they keep up. A new tool appears, it gets deployed, and results get measured afterward. That works fine when the change is as simple as installing a new printer. It fails the moment the process underneath is genuinely complex — which is most of the time. What’s missing is the step where the existing process gets mapped, stress-tested for bottlenecks, and redesigned before automation is even on the table.

Both the rushed CEO and the frozen CEO would benefit from the identical corrective move — not “go faster,” not “go slower,” but insert the diagnostic step neither is in the habit of taking.

If that sounds obvious, it’s worth asking why so many organizations quietly abandoned it. Process management — mapping, testing, and redesigning core operations — was standard executive discipline in the 1990s, built on Total Quality Management, Lean, and the Theory of Constraints. Somewhere along the way, leadership teams let it lapse. The lesson hasn’t gone anywhere; it’s just been sitting unused. Years before generative AI, executives attempting Robotic Process Automation without first doing this work were warned by experts that skipping it was a recipe for failure. The warning was accurate then. It’s still accurate now, just louder.

There’s a second reason the step feels skippable: nearly every executive has personally felt AI work well. Ask ChatGPT or Claude a question on your phone, and an articulate, confident answer arrives in seconds. That experience quietly convinces leaders that AI should transform every part of the business with the same ease. But personal productivity gains and enterprise-wide transformation are not the same category of problem. Real organizational change requires the unglamorous work of scoping, staffing, and sequencing multi-year projects. There is no shortcut from a good chatbot answer to a redesigned supply chain.

One Reveal Worth Adding

In other podcast I have drawn a sharp line between planning and strategy: planning extrapolates from what you’re already doing, while strategy forces a real choice that involves tradeoffs. Most AI “strategies” are actually AI plans — lists of tools to deploy, extrapolated from what competitors are doing, with no binding constraint identified and no real choice made. A genuine AI strategy starts by asking which single process constraint, if resolved, would unlock the most value — and works backward from there. Everything else is activity dressed up as strategy.

The Actual Fix

The CEOs who rush and the CEOs who freeze are both missing the same discipline — not courage, not caution, but the willingness to slow down at the exact moment everyone else is speeding up. The rushed CEO skips the diagnosis to look decisive. The frozen CEO avoids it to look careful. Neither has done the work.

The fix isn’t a faster rollout or a longer pause. It’s a process that’s been mapped and stress-tested before a single tool gets chosen. Boards don’t ultimately reward the leader who moved first or the one who moved last. They reward the one who knew where to look before moving at all.

PS: 5 Prompts to Use With Your Favorite LLM

Copy these into Claude, ChatGPT, or your assistant of choice to apply the article to your own organization.

  1. Find your lag. “Walk me through a recent failure or slowdown in my organization. Help me trace it backward — what department, decision, or process choice from 12–24 months ago might actually be the root cause, even if it doesn’t look connected on the surface?”
  2. Spot your substitute behavior. “I’m about to approve/reject an AI tool for [describe the process]. Before I decide, ask me questions that test whether I’ve actually mapped this process and identified its bottleneck — or whether I’m just reacting to pressure to ‘do something.’”
  3. Run a mini process diagnosis. “Here’s how [a specific process] works today, step by step: [describe it]. Identify the most likely bottleneck, and tell me what would need to be true for automating this process to actually help rather than just move the bottleneck somewhere else.”
  4. Test for real strategy vs. planning. “Here’s my current AI roadmap: [paste it]. Using Roger Martin’s distinction between planning and strategy, tell me honestly whether this is a strategy — with a real choice and a clear binding constraint — or a plan that’s just a list of tools.”
  5. Pressure-test your own excuse. “I’m the CEO/leader in this situation: [describe whether you’re moving fast or holding back on AI]. Play devil’s advocate and challenge me on whether my current pace is actually a disguised way of avoiding a proper process diagnosis.”

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The Missing Run: Why Your Innovation Efforts Remain Uninspiring and Empty

As the person responsible for driving innovation in your organisation, you have probably sat through a version of this conversation more than once.

The leadership team agrees that a new category is needed. Everyone nods. A workshop is scheduled. Consultants are hired, sticky notes are deployed, and three months later the team resurfaces with a list of incremental improvements dressed up in the language of transformation. Nothing changes. The cycle repeats.

This is not a talent problem. It is not a budget problem. It is not even a creativity problem — though it will feel like one. It is a navigation problem. And the reason it keeps recurring is that most organisations begin every innovation effort from the same invisible assumption: that they already know what kind of thing they are trying to become. They don’t. And without that clarity, no workshop, no consultant, and no off-site retreat will produce a genuinely new category. You will keep generating better versions of what you already are.

There is a framework that changes this calculus entirely. It arrived quietly, in a new book by Joe Pine — the same strategist who gave executives The Experience Economy twenty-five years ago and reshaped the way the world thought about what companies actually sell.

What a Category Actually Is

Before you can design a new category, you need a precise definition of what a category is. In business, a category is not a filing label or a market segment. It is a space in people’s minds — the mental frame that allows a customer to understand what a product is, where it belongs in their life, and why it matters. “Smartphone,” “microwave oven,” and “streaming service” are all categories that someone invented. Each one began as an answer to a need that customers had not yet been able to name.

Category design — the deliberate act of creating a new mental frame rather than competing inside an existing one — is widely discussed and rarely achieved. Most executives who attempt it eventually conclude that it requires a creative leap they cannot engineer. That conclusion, it turns out, is wrong. What it actually requires is a ladder.

The Ladder Most Executives Have Only Seen Half Of

Pine’s original insight, from The Experience Economy, was that organisations don’t just sell things — they offer value at different levels, and those levels form a hierarchy. At the bottom are commodities: undifferentiated raw inputs where price is everything. Above that are products: manufactured goods with consistent specifications. Above that are services: activities performed on behalf of the customer. And above that are experiences: carefully staged events that engage customers emotionally and memorably.

Every hotel in the world, for example, offers a blend of products and services — a room, a meal, a concierge. A smaller number have moved up to experiences: the Marriott’s flagship properties with their signature design and curated atmosphere. Sandals, in the Caribbean, built an entire brand around the all-inclusive experience category. Each of these companies moved up Pine’s ladder deliberately, and each time they did, they left their competitors arguing about price on the rung below.

Here is what Pine’s original framework did not include — and what his new book, Transformation Economy, now adds. There is a fifth rung. Above experience sits transformation: an offering that does not merely engage or delight the customer, but permanently changes them. Not their situation. Not their environment. Them — their skills, their identity, their capabilities, their trajectory.

This rung exists in every industry. In most, it is unnamed, unclaimed, and therefore available. It is the most defensible category a company can occupy, and the hardest to copy, because transformation is not a feature. It is a relationship with a long-term outcome.

Rung Invisibility: The Hidden Reason Innovation Stalls

Most companies have never asked which rung they currently occupy. They operate without a precise definition of their own offering type, which means that when they sit down to innovate, they have no fixed starting point. Call it rung invisibility: you cannot climb toward a destination you cannot see.

This is the innovator’s dilemma in its most structural form. It is not that successful companies refuse to innovate — it is that they keep innovating on the wrong rung. They add features to products, extend services, improve experiences, and call it transformation. The ladder makes the distinction visible. Once you can see the rungs, you can locate yourself accurately, name the next rung, and build toward it with precision.

Waiting With a Destination in View

In 2007, Andrew Ng began uploading his Stanford computer science lectures to the internet. The vision was clear: university-quality education, accessible to anyone, anywhere, free. What was not yet ready was the road. Broadband penetration was uneven. Streaming infrastructure was immature. Mobile adoption had not reached the scale required. The concept of learning via video had not yet been normalised for a mass audience.

Ng spent five years building precursors, testing formats, and watching the infrastructure mature. When Coursera launched in 2012, it was not because the idea had finally arrived — it was because the enabling conditions had. MasterClass followed a similar logic: the transformation offering was clear (learn directly from the world’s best practitioners, not just their subject matter), but the model required cinematic production quality and broadband capable of delivering it at scale. Both companies launched not when they were ready, but when the world was.

This is a categorically different posture from running innovation workshops. It is not luck. It is not serendipity. It is the discipline of naming a destination — a specific rung, a specific transformation offering — and then building the long-term strategy around the conditions that will make the climb viable. Pine himself waited over twenty-five years to write Transformation Economy. As he has said, the world simply wasn’t ready before now.

Corporate Inspiration at Its Finest

As a leader, you have probably tried to inspire your organisation through personal energy — motivating speeches, bold vision statements, off-site retreats designed to generate momentum. When the results are mixed, the temptation is to conclude that you need more charisma, a better facilitator, or a more compelling narrative. You don’t. What you need is a structure that does the inspiring for you.

This is what Pine’s ladder offers when it is embedded in a corporate strategy: inspiration that lives in the architecture of the plan itself. Aspirational but credible. Fact-based. Free of hyperbole. Specific enough to span a decade without losing its force. When employees understand not just what the company does today but which rung it is climbing toward — and what conditions the organisation is watching for — they engage differently. The destination gives their work a direction that no workshop can manufacture.

Steve Jobs was explicit, in at least one public interview, that Apple’s strategy was to wait — to define the destination clearly and hold it until the technology matured enough to make the climb possible. Inside Apple, the roadmap to the iPhone and iCloud gave those who knew it something to work toward that transcended any individual product cycle. That kind of inspiration is structural, not charismatic. It is replicable. And it begins with locating yourself honestly on the ladder.

What to Do Next

Every organisation, without exception, can do this. The transformation rung exists in your industry. It is almost certainly unnamed. The fact that it is unclaimed is not a warning — it is an invitation.

The work begins with three questions. What rung does your organisation currently occupy — precisely, not aspirationally? What would a transformation offering look like in your sector: what would it permanently change about your customer? And what enabling conditions — technological, cultural, regulatory, infrastructural — are not yet mature, but are on their way?

The EndPoint Method offers one systematic approach to answering these questions within a long-term strategy process. But the starting point is available to any leadership team willing to look at the ladder honestly and ask where they are.

Innovation is not a creativity problem. It is a navigation problem. Pine’s ladder is the instrument. The fifth rung is waiting.

PS — Five Prompts to Take This Further

Use these with any AI assistant (Claude, ChatGPT, or similar). Replace the bracketed text with your own details.

Prompt 1 — Locate your rung “I work in [industry]. Our core offering is [brief description]. Using Joe Pine’s five-rung ladder — commodities, products, services, experiences, transformations — help me identify which rung we currently occupy and what evidence supports that assessment. Be precise, not flattering.”

Prompt 2 — Define the transformation offering “In the [industry] sector, what would a genuine transformation offering look like? Define it using Pine’s standard: an offering that permanently changes the customer themselves, not merely their situation or experience. Give me three specific examples of what this could mean for a company like [company type].”

Prompt 3 — Map the enabling conditions “The transformation offering I want to build is [brief description]. What external conditions — technological, cultural, regulatory, or infrastructural — are not yet mature enough to support this at scale? Which of these are likely to mature in the next five to fifteen years, and what signals should I be watching for?”

Prompt 4 — Diagnose your innovation process “My organisation runs [describe your current innovation process — workshops, sprints, planning cycles]. Using the concept of rung invisibility — the idea that companies cannot innovate toward a destination they cannot see — identify the specific points in our process where the absence of a named transformation rung is likely to be causing us to recycle existing assumptions.”

Prompt 5 — Draft the strategic narrative “Help me write a one-page internal strategic narrative for my leadership team that: names our current rung on Pine’s ladder, defines the transformation offering we are building toward, identifies the two or three enabling conditions we are watching, and explains why this is a navigation strategy rather than a creativity exercise. Tone: direct, credible, free of consultant language.”

P.S. The LTSP26 Conference is open for registration here on Linkedin. https://www.linkedin.com/events/7475287796359028737?viewAsMember=true. Part of the lineup will feature Category Cathy, an interactive AI persona with unique knowledge of work by experts like Joe Pine, author of Transformation Economy.