Shipping AI Faster Than You Can Measure It Is a Risk

Momentum Without Measurement Is Not Progress

There is a version of the Artificial Intelligence problem that gets all the attention: the company that has not started, that is paralyzed by uncertainty, that keeps deferring the decision to next quarter. But there is a second version that is quieter, more common among ambitious companies, and in some ways more dangerous. It is the company that is moving fast on AI — running pilots, deploying tools, generating ideas — but doing it without governance, without measurement, and without anyone accountable for whether any of it is actually working. That company feels like it is ahead. The data often says otherwise. And a CEO advisory group in Columbus, Ohio on July 10, 2026 illustrated this second version with unusual clarity.

Six business leaders gathered that morning, representing creative services, insurance, healthcare, functional medicine, financial planning, and digital strategy. Half of them had already moved AI pilots into production. A third had three or more pilots running. This was not a room of AI skeptics or laggards. And yet the same survey revealed something striking: not one of the six companies had anyone who owned an AI KPI, every single one described their data as raw and not yet usable, and half had no AI safety protections in place at all. This is what shipping AI faster than you can measure it looks like — and it is a pattern that ambitious companies need to understand before it costs them.

What Six Columbus Leaders Revealed About AI Momentum

The July 10 Columbus session drew a group weighted heavily toward regulated and sensitive-data industries: insurance, healthcare, functional medicine, and wealth management accounted for four of the six companies, with creative services and digital strategy rounding out the room. This composition matters, because the AI readiness gaps that showed up in the data carry more weight in industries where client data is protected by regulation and where trust is the foundation of the business. Here is what the survey revealed:

• 100% had no one owning an AI KPI. Not a single company in the room had a person accountable for a measurable AI outcome. 67 percent had no KPIs tied to AI at all, and the remaining 33 percent tracked results occasionally with no clear owner. In a group where half were actively running pilots, this is the defining gap — momentum without measurement.

• 100% had raw, not-yet-usable data. Every respondent described their data as raw material they could label if needed, rather than clean, structured, decision-ready information. This unanimous result points to a shared foundation gap: the companies want AI-driven outcomes, but none had yet built the organized data infrastructure that reliable AI depends on.

• 50% had no AI safety governance at all. Half the room had zero protections in place, and another 33 percent had rules that were only partly enforced. For the insurance, healthcare, functional medicine, and wealth management companies present — all handling regulated, confidential client data — this is not a minor administrative gap. It is a live compliance and trust exposure.

• 50% had no single accountable owner for AI outcomes. Three of six companies had either no clear owner or a working group with diffuse responsibility. The other half had named a CEO or general manager as the accountable owner — a strong signal, but one that raises its own question about whether the busiest person in the company can also be the one building AI workflows day to day.

• 67% named talent and skills as their biggest blocker, and 67% named revenue growth as their top goal. The pattern that has defined the entire GPS Summit series held once again: the tools are available and the goal is clear, but the internal expertise to connect the two is what most companies are missing.

AI confidence averaged 6.2 out of 10, ranging from 2 to 8. Notably, the operational agility in this room was strong — 33 percent could make a production change the same day and another 33 percent within a week. This is a group that can move quickly. The question the data raises is not whether they can act, but whether they are building the measurement and governance structure to ensure their fast action produces durable, safe, measurable results.

"Incredible insights. Already have a ton of ideas." — Joey Z., Bonfire Red

Joey's comment captures the energy this kind of session generates — and also, in a subtle way, the exact risk the data reveals. Bonfire Red is a creative company that already has three or more AI pilots in production, an engaged CEO accountable for AI, and same-day operational agility. It is one of the more advanced companies in the room. And yet it has no KPI owner and no AI safety protections. A ton of ideas is a wonderful asset. But without the structure to measure which ideas are working and the governance to deploy them safely, a ton of ideas can become a ton of unmeasured, ungoverned activity. The difference between the two is AI Leadership.

The Discipline That Turns AI Activity Into AI Results

The Columbus data offers one of the clearest lessons in the GPS Summit series precisely because this was not a room of beginners. When a group that is already deploying AI still lacks measurement, governance, and data readiness across the board, it reveals that these disciplines are not automatic byproducts of AI activity. They have to be built deliberately — and the companies that build them are the ones whose AI investments compound rather than plateau.

Why 100% With No KPI Owner Is the Signal to Watch

The most important number from Columbus is the unanimous one: not a single company had a person who owned an AI KPI. This is significant because it decouples AI activity from AI accountability. A company can run pilots, deploy tools, and generate ideas indefinitely without ever answering the fundamental question: is this producing measurable business value? Without a KPI and an owner, that question never gets a rigorous answer. Pilots continue because they are interesting, not because they are proven. Resources get allocated by enthusiasm rather than by evidence. And the AI in Marketing, Customer Engagement, and operational initiatives that could be driving real revenue growth are never optimized, because no one is measuring which ones work.

The fix is straightforward but requires intention. Every AI initiative needs a specific, measurable outcome attached to it — leads generated, hours saved, proposal turnaround time reduced, Customer Experience scores improved, cost per deliverable lowered — and a named person responsible for tracking and improving that number. This single discipline transforms AI from a portfolio of experiments into a managed business function. It is one of the first things a developed internal AI leader puts in place, and it is one of the core capabilities the GPS Summit builds.

The Governance Gap That Regulated Industries Cannot Afford

With four of six Columbus companies operating in insurance, healthcare, functional medicine, and wealth management, the finding that half the room had no AI safety governance carries particular weight. These are industries where client data is protected by regulation, where confidentiality is a legal obligation, and where a single mishandled data exposure can create liability far exceeding any efficiency AI might deliver.

The risk is concrete. Without a governance framework, a team member at a healthcare or financial services company might feed protected client information into a public AI tool with no visibility into where that data goes. AI-generated outputs might reach clients without adequate review. And when a regulator or a client asks how AI is being used with their data, there is no policy, no audit trail, and no accountable owner to provide an answer. This is not a reason for regulated businesses to avoid AI. It is a reason to build the governance infrastructure first — the data access controls, usage policies, and review protocols that let these companies capture AI's benefits without creating unacceptable risk. Building that framework for a specific regulatory context is exactly the kind of applied AI Leadership the GPS Summit develops.

The Data Reality Behind Every AI Ambition

The unanimous data finding in Columbus — every company describing their data as raw and not yet usable — is one of the most honest signals in the GPS Summit series. It reflects a truth that most AI conversations skip past: AI is only as capable as the data it can access, and most companies have not yet done the unglamorous work of organizing that data into a form AI tools can use effectively.

For a wealth management firm, this means client interaction records, portfolio data, and communication histories scattered across systems that do not connect. For a healthcare organization, it means patient and operational data locked in formats that AI cannot easily read. For a creative agency, it means project, client, and performance data that has never been structured for analysis. In every case, the path to meaningful Customer Insights and genuine Business Growth runs through a data foundation that has to be built before the most valuable AI use cases become possible. The good news from Columbus is that all six companies have the raw material — they described data they could label if needed. What they need is the leadership to turn that raw material into an AI-ready asset.

When the Real Blocker Is Time, Not Talent

One of the Columbus leaders offered a piece of feedback that cuts to the heart of the small business AI challenge — and did so by pushing back directly on the survey itself:

"You need to change the answers for the number-one blocker question, because my biggest one by far is time." — Helen S., Third Street Digital

Helen's clarification is valuable precisely because it names the blocker that so many small business leaders feel but that rarely fits neatly into a survey category. It is not that she lacks talent, budget, or access to tools. It is that she lacks bandwidth — the time to evaluate tools, redesign workflows, clean data, and manage pilots while still serving clients and running the business. In smaller agencies and firms, time is very often the real constraint, and it is one that muscling through does not solve.

This is one of the most compelling arguments for developing a dedicated internal AI leader rather than trying to add AI to an already-full executive plate. When AI is one more thing the owner does in stolen moments between client work, it stays perpetually under-resourced and under-prioritized. When AI is owned by a developed leader whose specific mandate is to drive it forward, the time constraint dissolves — because the work finally has a home. The GPS Summit exists to develop exactly that leader, turning AI from a time-starved side project into a properly owned business function.

The GPS Summit: From Fast Activity to Measurable Advantage

The Columbus room was full of companies that can move — half already running pilots, a third capable of same-day production changes. That agility is a genuine asset, and it is more than many organizations have. But agility without governance, measurement, and data discipline produces motion, not necessarily progress. The GPS Summit is designed to give fast-moving companies the structure that converts their speed into durable Competitive Advantage.

It is a structured, cohort-based AI Leadership development program that takes your most capable high-potential leader — including the CEOs and functional leaders already carrying AI ownership in companies like those in the Columbus room — and equips them to build the measurement, governance, and data foundation that turns AI activity into measurable business results.

GPS Summit participants leave equipped to:

• Install AI KPI ownership and measurement — closing the exact gap that 100 percent of the Columbus companies shared, by attaching measurable outcomes and named owners to every AI initiative so activity becomes accountable and optimizable.

• Build governance for regulated environments — establishing the data protection policies, usage rules, and review protocols that let insurance, healthcare, financial, and other regulated businesses deploy AI safely and compliantly.

• Turn raw data into an AI-ready foundation — assessing the current state of organizational data and building the clean, structured, accessible foundation that reliable AI and genuine Customer Insights depend on.

• 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 67 percent of the Columbus group named as their top priority.

• Own AI as a business function, not a side project — giving AI a proper home with a dedicated, accountable leader, so it stops competing for scraps of executive time and starts driving real Digital Transformation.

To learn more about the GPS Summit and how it turns AI momentum into measurable results, visit the GPS Summit overview page or review the full competitive comparison.

Speed Is an Advantage Only When You Know Where You Are Going

The companies in the Columbus room have something valuable that many organizations lack: the willingness to move, the agility to act, and in several cases, the early production experience that proves they can turn AI ideas into deployed reality. That is not a small thing. Joey Zornes left with a ton of ideas. Half the room was already running pilots. This is a group with momentum.

But momentum is only valuable when it is pointed in the right direction and measured along the way. A company shipping AI fast without measurement is like a car accelerating without a dashboard — the speed feels like progress right up until it becomes a problem. The discipline that the Columbus data revealed as missing across the board — KPI ownership, governance, data readiness — is precisely the discipline that separates the companies whose AI momentum compounds into lasting Competitive Advantage from the companies whose momentum quietly dissipates into unmeasured activity.

Every company in that room can build this discipline. The raw material is there — the data, the leadership engagement, the operational speed, the clear revenue goals. What is missing is the developed internal leader who can install the structure that makes the momentum count. That is the person the GPS Summit builds. And for a fast-moving company, the addition of that leader is not a brake on speed. It is the steering, the dashboard, and the map that finally make the speed worth having.

When you are ready to give your most capable leader the foundation to turn AI activity into measurable business results, enroll them in the GPS Summit here. To learn more about BREATHE! Experience and the full program, visit breatheexp.com.

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How many AI initiatives are running inside your business right now that no one is actually measuring — and what would change if a single accountable leader owned the outcomes?