From a 1 to a 10: The AI Gap Inside a Single Room

The Widening Distance Between Companies That Move and Companies That Wait

The most important story in Artificial Intelligence right now is not about the technology. It is about the distance opening up between the businesses that are building real AI capability and the businesses that are still thinking about it. That distance is no longer measured in years. It is measured in quarters. And it compounds — every month a company waits, the companies that did not wait pull further ahead in ways that become progressively harder to close. Nowhere was this dynamic more visible than in a single room in Columbus, Ohio on July 9, 2026, where a CEO advisory group of seven business leaders revealed, through their own self-assessments, exactly how wide the AI gap has become even among peers sitting at the same table.

When these leaders were asked to rate their confidence that their company would be competitive in AI by 2027 on a scale of 1 to 10, the answers ranged across the entire spectrum: a 1, a 2, a 5, a 6, two 8s, and a 10. In a group of just seven companies, the full distance from least confident to most confident was represented. That spread is not a statistical curiosity. It is the clearest possible illustration of a market that is not advancing uniformly but diverging — separating into the companies that have made the organizational decisions AI requires and the companies that have not yet begun.

What Seven Columbus Leaders Revealed About the State of AI Readiness

The Columbus session brought together leaders from a notably diverse set of industries: nonprofit education, commercial real estate, building materials distribution, healthcare staffing, and three companies from the marketing and professional services world. Company sizes ranged from under 50 employees to over 1,000. And while the industries and scales varied widely, the underlying AI readiness data revealed the same set of structural gaps that the GPS Summit series has now documented across cities from coast to coast.

Here is what the survey data showed:

• 71% had no KPIs tied to AI outcomes. Five of seven companies had no measurable standard for AI performance. Only two had reached the stage of a clear AI use case with a defined KPI, a named owner, and a regular review cadence — and those two were among the most confident companies in the room.

• 57% had no effective AI safety governance. 43 percent had zero protections in place, and another 14 percent relied on informal habits with no consistent enforcement. In a room that included healthcare staffing and commercial real estate — both industries handling sensitive personal and financial data — this governance gap represents real, immediate risk.

• 43% had no single accountable owner for AI outcomes. Three of seven companies had either no clear owner at all or a working group with diffuse responsibility. The three companies that had named a CEO or functional leader as the accountable AI owner were, unsurprisingly, further along on nearly every other readiness measure.

• 71% named talent and skills gaps as their biggest blocker. For the entire arc of the GPS Summit series, this answer has led the field — and Columbus was no exception. The tools are available. The use cases are proven. What most companies lack is the internal expertise to deploy and own them.

• 57% named revenue growth as their primary AI goal. Revenue growth led the outcome goals, followed by Customer Experience at 29 percent. Three quarters of the room came in with an AI goal tied directly to the two outcomes AI has the most documented impact on — yet most had none of the infrastructure in place to pursue them.

There was also a notable pattern in operational agility. When asked how quickly their team could make a production change if a key performance number dropped by 15 percent, 71 percent said within a month or quarterly, and only one company could respond same day. This matters because AI adoption rewards organizational speed — the ability to test, learn, and adjust quickly. Companies that struggle to make changes under normal conditions often find that even strong AI initiatives stall before they generate value. The organizations that can act fast are the ones best positioned to turn AI experiments into AI capability.

What the Confidence Spread Actually Teaches Us

The range of confidence scores in the Columbus room — from a 1 all the way to a 10 — is worth examining closely, because it contains one of the most useful lessons in the entire GPS Summit series. The leaders at the low end of the range were not less intelligent, less ambitious, or less committed than the leaders at the high end. They were simply further from having the organizational infrastructure that converts AI interest into AI results. And critically, the difference between a 1 and a 10 was almost entirely explained by decisions any company can make.

What the 10s Had That the 1s Did Not

The companies at the top of the confidence range shared a specific set of characteristics. They had named an accountable owner for AI outcomes. They had at least one AI use case with a KPI and a review cadence. They had moved multiple pilots into production. And in the most advanced cases, they had implemented governance frameworks that protected sensitive data while enabling broader AI use. None of these are exotic capabilities. None require enormous budgets or specialized technical teams. They require organizational decisions — the decision to assign ownership, to measure outcomes, to build governance, and to develop the internal capability to execute.

The companies at the low end of the range had made none of these decisions yet. No owner. No KPIs. No governance. No pilots in production. Their low confidence was not pessimism — it was accuracy. They could see clearly how far they had to go. And that clarity, paired with the right development program, is actually the most powerful possible starting point. A leader who accurately understands the gap is far better positioned to close it than one who underestimates it.

The Question That Reveals Where a Company Really Is

One of the seven Columbus leaders, Marketta Thomas of Zane State College, left a single comment in her survey — a question, really — that captures the exact moment so many organizations find themselves in:

"How to build agents." — Marketta T., Zane State College

Three words. But they contain an entire strategic posture. Marketta rated her organization's AI competitiveness at a 1 out of 10 — the lowest score in the room — and yet her question is not defensive or dismissive. It is forward-looking and specific. She is not asking whether AI matters. She is asking how to build the most advanced form of it. That combination — an honest assessment of being behind, paired with a genuine desire to build something real — is precisely the profile that the GPS Summit is designed to serve. It is the difference between a company that will stay at a 1 and a company that is about to start climbing.

Why Marketing and Professional Services Feel AI First

Three of the seven Columbus companies came from marketing, digital marketing, and executive coaching — a concentration that offers a useful window into where AI's impact lands earliest and hardest. Marketing and professional services are, in many ways, the leading edge of AI disruption, because so much of the work is language, content, analysis, and client communication — precisely the domains where AI capability has advanced most rapidly.

For a marketing firm, AI in Marketing is not an abstract concept — it is an immediate competitive reality. AI that generates content at scale, personalizes campaigns based on Customer Insights, optimizes ad spend in real time, and automates the Customer Engagement workflows that once required entire teams. For these companies, the question is not whether AI will reshape their work. It already is. The only question is whether they will be the firm deploying these capabilities to serve clients better and faster, or the firm being outcompeted by rivals who did. In a service business, where the product is expertise and execution speed, AI-driven Customer Experience improvements translate directly into client retention, referral growth, and Competitive Advantage.

This is why the professional services firms that build genuine AI Leadership now will separate themselves so decisively from those that do not. The capability gap in a knowledge business is not gradual — it is exponential. A firm with a developed internal AI leader can deliver more, faster, and at higher quality than a firm still doing everything manually, and that advantage compounds with every client engagement.

The Data Foundation Most Companies Skip

The Columbus data revealed that only one of seven companies had a clean, labeled dataset with access controls ready for an AI pilot. The rest described their data as raw and unlabeled, scattered and siloed, or not accessible at all. This is the foundation that most AI strategies quietly depend on and most companies quietly skip — and it is one of the most common reasons promising AI initiatives fail to produce results.

AI is only as capable as the data it can access. A marketing firm with disorganized client data, a real estate company with siloed transaction records, a staffing company with unstructured candidate information, a nonprofit with scattered donor and program data — each of these faces the same underlying reality: before AI can generate meaningful Customer Insights or drive Business Growth, the data has to be organized, cleaned, and made accessible in a form AI tools can use. This is not glamorous work. But it is the work that separates the companies whose AI investments compound from the companies whose AI investments disappoint. And it requires an internal leader who understands what AI needs from data and has the organizational authority to build that foundation. That is exactly the capability the GPS Summit develops.

The GPS Summit: How a 1 Becomes a 10

The gap between the least confident and most confident companies in the Columbus room is not permanent. It is not a reflection of fixed advantages or immovable constraints. It is a reflection of decisions — and decisions can be made. The company sitting at a 1 today can be sitting at a 7 or an 8 within a year, not by acquiring more technology, but by developing the internal leader who can build the strategy, install the governance, organize the data, and drive the adoption that the companies at the top of the range have already put in place.

That is the entire purpose of the GPS Summit. It is a structured, cohort-based AI Leadership development program that takes your most capable high-potential leader and equips them to move your organization from wherever it is today to a position of genuine AI competitiveness — with a real strategy, real accountability, and real results.

GPS Summit participants leave equipped to:

• Build a complete AI Strategy with KPI accountability — closing the gap between the 71 percent of Columbus companies with no AI measurement and the structured, accountable programs that the most confident companies had already built.

• Configure and deploy AI agents — answering the exact question Marketta Thomas asked, by developing the hands-on capability to build autonomous AI systems that expand organizational capacity and drive measurable outcomes.

• Organize data for AI readiness — assessing the current state of organizational data and building the clean, accessible foundation that AI tools require to generate real Customer Insights and Business Growth.

• Apply AI to revenue and Customer Experience outcomes — deploying AI in Marketing, Customer Engagement, and customer-facing workflows in ways that directly serve the revenue growth goals that 57 percent of the Columbus group named as their top priority.

• Build governance that enables Digital Transformation — establishing the data protection policies and usage standards that make AI safe to scale in industries handling sensitive personal, financial, and client information.

To learn more about the GPS Summit and how it moves companies from AI interest to AI capability, visit the GPS Summit overview page or review the full competitive comparison.

The Only Number That Matters Is the One You Choose to Change

A confidence score is not a verdict. It is a snapshot. The company that rated itself a 1 in Columbus is not doomed to stay there, and the company that rated itself a 10 has not finished the race — it has simply started earlier. What the full range of scores in that single room demonstrates is that AI competitiveness is not distributed by luck or by industry or by size. It is built by decision. And the most important decision any company can make right now is the decision to develop the internal leader who will move them up the scale.

The seven leaders in Columbus came from wildly different starting points — a nonprofit college, a building materials distributor, a healthcare staffing firm, marketing agencies, an executive coaching practice, a commercial real estate company. But they share the same opportunity. Every one of them can build the AI Leadership, the AI Strategy, and the organizational capability that separates the companies pulling ahead from the companies falling behind. The gap between a 1 and a 10 is real. But it is also entirely closable — for any leader willing to invest in the person who will close it.

Marketta Thomas asked how to build agents. It is the right question — and it is exactly the kind of question that gets answered not by a single workshop, but by a developed internal AI leader who has been given the framework, the tools, and the mandate to build. The GPS Summit exists to develop that person. And in a market diverging as fast as the AI market is right now, the decision to develop them is the decision that determines which side of the gap your company ends up on.

When you are ready to give your most capable leader the foundation to move your company up the AI scale, enroll them in the GPS Summit here. To learn more about BREATHE! Experience and the full program, visit breatheexp.com.

If you rated your own company's AI competitiveness on a scale of 1 to 10 today, what number would you choose — and who inside your organization could move that number if you gave them the chance?