Most companies now have AI running in six different departments, bought by six different people, none of whom has ever compared notes with the other five. That is not an AI adoption problem. It is a missing job description problem, and it is getting more expensive every quarter that it stays unfilled.
This article is grounded in current advisory work, not retrospective analysis. Mark Lynd is a 5x CEO/CIO/CISO with Thinkers360 Top 10 global rankings across Cybersecurity and Artificial Intelligence and was ranked #1 globally in Cybersecurity in 2023. He is currently Head of Executive Advisory and Strategy at Netsync, advising enterprise C-Suites and boards on the AI and cybersecurity questions moving fastest in 2026. The frameworks and patterns referenced here are from active engagements this quarter.
The Coordination Problem Nobody Owns
Enterprises are not struggling to find AI tools. They are struggling to find anyone whose job it is to say no to the wrong ones, or to notice that marketing, operations, and finance have each independently licensed a similar capability from three different vendors at three different price points with three different data handling terms. IBM's Institute for Business Value found that 76 percent of surveyed organizations now have a chief AI officer in 2026, up from 26 percent just a year earlier, one of the fastest role-adoption swings the IBV has tracked in recent memory. The same research found organizations with a chief AI officer achieved roughly 5 percent higher return on their AI investment than those without one. That gap is not about the title. It is about what having a single accountable owner does to spend discipline, vendor consolidation, and the willingness to kill a pilot that is not working instead of letting it quietly consume budget for another year.
The urgency is not hypothetical. Gartner predicted that 40 percent of enterprise applications will be integrated with task-specific AI agents by the end of 2026, up from less than 5 percent at the start of 2025. That is not a gradual curve a company can address whenever convenient. It is a compressed adoption window, and every application that gets an agent bolted on without a coordinating strategy becomes another data flow, another vendor relationship, and another point of risk that the rest of the organization has to discover rather than plan for.
Boards feel this gap too, even when they cannot name it precisely. Gartner's 2025 board of directors research found that 86 percent of organizations are piloting or deploying AI, yet only 18 percent of boards are actively using AI tools themselves. A board that has not worked hands-on with the technology it is being asked to fund is poorly positioned to evaluate whether a proposed AI initiative is well scoped or whether it duplicates something three other departments already licensed last quarter. An AI strategist's job, in large part, is to be the translator who can tell the board which of the dozen AI requests on this year's budget actually deserve funding, in language the board can act on without first becoming AI experts themselves.
The risk shows up first as shadow AI, which is really just the coordination problem's most visible symptom. A BlackFog survey of 2,000 workers at companies with more than 500 employees found 49 percent admit to using AI tools without employer approval, and strikingly, 69 percent of presidents and C-suite members said they were personally comfortable with that shadow use continuing. Leadership is not unaware of the problem. A meaningful share of leadership is participating in it, because there is no sanctioned, well-understood path to get an AI capability evaluated and approved quickly, so people, including executives, route around whatever process exists.
Picture a national retailer where the marketing team has licensed a generative AI content platform, the customer service team has stood up an AI chatbot from a different vendor, and the supply chain team is piloting a demand forecasting model from a third. Each initiative made sense in isolation and each was approved by a different budget owner who had no visibility into the other two. Eight months in, the CFO asks for a single number representing total AI spend and nobody can produce one, because the spend is scattered across a dozen line items under different cost centers with different renewal dates. Worse, an audit finds that two of the three vendors have overlapping data processing agreements with materially different security and retention terms covering the same categories of customer data. No one designed this outcome. It is what happens by default when nobody owns AI strategy end to end.
The Case That This Is Just Another Fad Title
The honest objection here is that chief AI officer looks a great deal like chief digital officer did a decade ago, a role invented in a hype cycle that most companies quietly folded back into the CTO or CIO's job once the initial excitement passed. Skeptics can reasonably point out that adding a C-suite title does not automatically fix coordination problems, that plenty of AI-titled hires have become figureheads with a slide deck and no real budget authority, and that a company already paying a CTO, a CDO, and a CIO does not obviously need a fourth technology executive competing for the same seat at the table. The safer, cheaper path, the argument goes, is to assign AI strategy as an explicit responsibility inside an existing role rather than inventing a new one, and to revisit the question again once the current adoption wave settles into something more predictable.
That argument is right that the title itself guarantees nothing. It is wrong that the underlying coordination need will fade the way chief digital officer's did. Chief digital officer emerged largely to push traditional companies toward channels, web and mobile, that were already well understood technically and mostly about organizational will. AI strategy is different in kind because the technology itself is still changing fast enough that a part-time owner cannot keep pace with vendor capability, regulatory movement, and internal adoption simultaneously while also running their existing full-time job. The IBM data on return differences between companies with and without dedicated AI ownership is early, but it points the same direction as the coordination failures described above, that this function performs meaningfully better when someone owns it as a primary job rather than a responsibility bolted onto an already full one. Whether that person carries a chief-level title or not is a secondary question. Whether someone owns it as their main job is the one that predicts the outcome.
What Leadership and the Board Should Ask This Week
Leadership and the board should ask for a single consolidated view of every AI tool currently in production or pilot across the company, who approved each one, and what it costs in total, not per department. If that list cannot be produced within a week, that inability is the answer to whether a strategist role is needed. They should ask who currently has the authority to say no to a new AI vendor request, and whether that authority sits with one person or is scattered across whichever budget owner happened to sponsor the request. They should ask how many of the AI tools employees are actually using were ever formally evaluated, versus adopted informally because no approved alternative existed. And they should ask what percentage of current AI spend is being tracked against a measurable business outcome rather than treated as a cost of staying current.
There is a smaller, sharper version of this test worth running before the larger audit. Ask any three department heads, independently, who in the company they would call before signing a new AI vendor contract. If the three answers are three different names, or if one answer is nobody, the coordination gap this piece describes is not theoretical. It is already costing the company money and creating risk exposure nobody has mapped, right now, in whatever AI tools those three departments are already using without having compared notes.
The companies that answer these questions cleanly already have something functioning like an AI strategist, whatever the title on the door says. The ones that cannot answer them are not lacking a title. They are lacking a decision-maker, and the bill for that gap is already accumulating, one uncoordinated vendor contract at a time.
