You Cannot Delegate the Design of the AI-Era Company
The CAIO appointment has become the most common substitute for the work it was supposed to do. The data has finally caught up.
I am driving the AI redesign of my own business myself.
Not because I have to. I have a team. I could hand it to someone. I have chosen not to and the more I watch other leadership teams, the more I am convinced that this choice is the only reason it is working.
Here is the scene I keep seeing in the rooms where I advise. A board meeting. The most senior leader in the room points at AI and assigns the work to someone else, a CTO, a newly appointed Chief AI Officer, sometimes a transformation lead. The intent is real. The delegation is real. And within a quarter, that workstream quietly changes shape. It stops being about what the function could become. It starts being about how the function can be made smaller. Reinvention turns into a cost exercise. And nobody notices the substitution, because the headline number — efficiency — still goes up.
That substitution is what I want to write about today. And the data has finally caught up with what I have been watching.
The substitution
On 4 May, IBM’s Institute for Business Value published a study of more than 2,000 organisations. The headline: 76% of companies have now appointed a Chief AI Officer, up from 26% a year ago. An enormous shift in a single year.
But the finding that actually carries weight sat lower in the report. The organisations genuinely delivering on their AI objectives, the ones converting investment into outcome, had done something the others had not. They had redesigned five core areas of the business: technology, finance, HR, operations, and the cross-functional work between them. That group was four times more likely to have delivered on its business objectives than the group that had only made the appointment.
Read that again. The appointment is not what produces the value. The redesign is. And most of that 76% have not done the redesign. The same study found only 25% of the workforce uses AI regularly, even though 86% of CEOs believe their people have the skills to. The gap is not capability. It is design.
Here is what I think is happening. The CAIO appointment has become the most common substitute for the design work itself. It looks like a decision. It feels like a decision. It can be announced on a board call. But the decisions AI actually requires, what stays human, what becomes agentic, where the handoffs sit, which functions get rebuilt rather than augmented — are not decisions a new title can make from outside the operating committee. They are architectural choices about how the company makes decisions. And those belong to the person whose job is to design the company.
What the Cloudflare story was actually about
You saw the Cloudflare announcement. So did I. Matthew Prince and Michelle Zatlyn cut 1,100 people, 20% of the workforce, on the same day they reported Q1 revenue up 34%. The post was titled Building for the Future. The market took more than 20% off the stock by close.
Cisco cut 4,000 the same week, also during record revenue, and the market barely moved.
The difference is not the size of the cut. It is whether investors could see the new company behind the smaller one. Prince offered productivity multipliers — two times, ten times, a hundred times more productive per person. He offered a 600% rise in internal AI usage. What he did not offer was the redesigned operating model. He offered the consequence of one, not the architecture of one. And the market priced the gap.
That is the same gap I see in the rooms I sit in. The leader has not designed the new company. They have delegated the question of what the new company should be. So when the productivity gains arrive, the only thing the operating model knows how to do with them is shrink, because nothing else has been designed to absorb them.
This is what I mean when I say recomposition, not reduction. Cutting is what an undesigned system does with an efficiency gain. Designing is the work that turns the same gain into something that compounds.
The CEO is the systems architect
Here is how I now think about this. The CEO is no longer the chief allocator of AI investment. The CEO is the systems architect of the AI-era company.
That is a different job. It is not about choosing models or vendors, or whether to centralise the data lake. It is about answering five questions no one else in the company has the authority to answer.
One. What decisions will humans continue to make? Not what tasks humans will do, what decisions. This is the question most leaders skip. Decision rights, not task lists.
Two. Where will agents execute end-to-end, and what does a wrong answer cost? Agentic work compounds. A wrong agent decision propagates faster than a wrong human one. The architecture has to know which calls are reversible and which are not.
Three. Which functions get reinvented, not augmented? Augmenting an obsolete function is the most expensive thing a company can do with AI. Some functions need to be rebuilt from the operating model up.
Four. Where does accountability sit when the work is mixed? When an agent and a human co-produce a decision, who carries the consequence? If you cannot answer that in plain language, the EU AI Act’s Article 14 will answer it for you in August.
Five. What does the company sound like to a customer in two years? The easiest question to skip, and the most important. If you cannot answer it, you do not have an AI strategy. You have an automation programme.
These are not technology questions. They are design questions about what the business is. A CAIO who joined three months ago cannot answer them. The person whose job is to design the company has to.
What this reveals
The danger here is not loud. It rarely is. AI failures arrive quietly, fewer questions asked, less friction, dashboards staying green while judgment leaves the system. Delegated design fails the same way. The productivity numbers climb. The board is satisfied. And two years on, the company is smaller, faster, and no more valuable than it was, because no one ever designed what it was becoming.
What to do this week
Audit last quarter’s AI workstreams. For each one, ask whether the outcome looked like reinvention or like reduction. If the answer is always reduction, you are running a cost programme wearing agentic vocabulary.
Look at where your CAIO reports. If the answer is technology leadership, ask whether you have hired a senior engineer with a new title, or a senior designer of the company. If it is the former, the CAIO is not the problem. The design vacuum above them is.
Then sit down, alone, for two hours, and answer the five questions for one function. Not the whole company. One. Whichever one you think about most. If you cannot answer them after two hours, you have just found your next strategic priority.
The commitment
I am driving the AI redesign of the business I operate myself, this year. Function by function, decision right by decision right. Not because I enjoy the discomfort, but because I believe the leaders who try to hand this off will spend the next two years explaining to their boards why productivity went up and value did not.
I am asking my fellow C-level peers to do the same. Drive it yourself. The design of the company of the AI era is not a workstream. It is the job. It is your job.
I will write again in a few weeks about what I am learning doing it. In the meantime, if you are sitting on a CAIO appointment and a quiet sense that something is not landing, call it what it is. The appointment is not the strategy. You are.
AI strategy, leadership, CEO, organisational design, Human × AI, agentic AI, future of work
Sources: IBM IBV Study, May 2026 · BCG, “AI Has Made Work Reinvention a CEO Mandate” · Cloudflare Q1 earnings (CNBC) · Davenport & Bean, MIT Sloan
You’ve hit on a massive truth, Karine. The CAIO appointment is often just box-ticking to avoid structural redesign. And you're exactly right: when an undesigned system gets an efficiency boost, its default move is to shrink and cut heads rather than build value.
But your premise that leaders should rebuild the organization starting with AI is where the theory hits a wall. Designing around a tool might work for a brand-new startup with a blank canvas, or a low-risk digital service. But for complex, established companies, that’s an incredibly dangerous, outside-in approach.
Having led high-risk transformation programs in the trenches, I’ve learned that a successful redesign requires a very specific sequence. You cannot rethink how to organize your people or deploy resources around AI until you have done the hard work of cleaning up your data and figuring out what actually needs to be measured.
Without that operational ground truth, a tech-first redesign triggers a domino effect of blind spots:
The Reality vs. Margin Gap: If you don't first map exactly how input costs drive value at the product or process level, a redesign is just a blind guess on whether you're actually saving money.
The Blame Game: When a human and a machine co-produce a decision, you need absolute clarity on who owns the consequences and practical safety nets to catch errors before they scale.
The Friction Domino Effect: Optimizing one department usually breaks another. If an automated process saves operations money but kills the customer experience, the financial gains are wiped out instantly.
CEOs absolutely need to be systems architects, but they can't build from 30,000 feet. We have to anchor the architecture in operational logic first. Otherwise, even a CEO-led redesign risks becoming just another high-level corporate hallucination.