The CEO who is still standing in 2027, respected and in control of their company, will very likely be the one who ended their relationship with the advisers they have trusted for years. Not out of disloyalty. Out of survival.
The tell in the transcripts
Listen to how the largest technology leaders now talk about AI on their earnings calls, quarter after quarter. The striking thing is not the enthusiasm. It is the absence of the traditional big consultancies from the story. The companies actually building the future are relying on their own people and their own conviction, not outsourcing their thinking to a firm that sells the same deck to every client in the industry. What used to be the safe choice has quietly gone missing from the conversations that matter.
Why the old model breaks in the AI era
Here is the mechanism, and it is not a personal attack on anyone’s competence. The traditional consulting model sells time and headcount. You pay for months of discovery, a large team and a slide deck at the end. That model was tolerable when change was slow. In the AI era it is a structural mismatch, for one blunt reason: by the time a lengthy engagement delivers, the technology it was scoped around has already moved. You paid for an answer to a question that has changed. This is the failure I set out in Your Traditional Partners Are Failing You in the Age of AI, and it is why buying hours is no longer the same as buying understanding.
There is a fair counter-argument, and I will make it honestly. The best consultancies are not standing still; they are building AI capability, buying firms and retraining people, and some are genuinely good at it. So the honest version of my claim is not that every consultancy is doomed. It is narrower and harder to dodge: the old engagement model, long timelines, big teams, generic playbooks, is the thing that breaks, whoever is selling it. A firm that has truly changed how it works can be valuable. A firm selling the pace of 2015 in 2027 cannot.
What replaces it
The pattern that works now is smaller, faster and closer. A trusted adviser who understands the business and can move at the speed the technology demands, working alongside internal people who own the outcome, rather than a large team that arrives, extracts fees and leaves. The direction of travel is towards conviction and capability held inside the company, supported by a few sharp external voices, not rented wholesale from outside. It is the same reason the right leader for this is usually already inside the building, which I argued in The Sleeper Has Awoken, and the reason concentration on one big external provider is its own risk, as in The Proud Leader Who Handed Off His Own Future.
How fast the ground can move is not theoretical. When a strong, cheaper open model appears seemingly overnight and resets what everyone assumed about cost and capability, the lesson is not about one model. It is that anyone whose advice was built on last year’s assumptions is already behind, and a slow engagement cannot catch up.
The CEO still standing in 2027 will not be the one who spent the most on the most famous firm. It will be the one who had the nerve to stop, and to build the understanding inside their own walls.
If you are leading your organisation through this, I work with a limited number of senior leaders each quarter. Get in touch at Anglero.com.
Thomas Anglero is a Strategic AI Advisor, keynote speaker and author of Intro to Artificial Intelligence. He has delivered over 450 keynotes across 30 countries for organisations including IBM, the WHO, the World Government Summit and the European Commission. He founded the IBM Watson AI Lab for Cancer at the Oslo Cancer Cluster and closed over $500 million in enterprise transformation deals as CTO and Chief Innovation Officer at Cognizant.
Frequently asked questions
Why would a CEO end long-standing consulting relationships because of AI?
Because the traditional model of long timelines and large teams is too slow for how fast AI moves. By the time a lengthy engagement delivers, the technology it was scoped around has already changed, so the CEO who moves to something faster tends to stay in control.
Are all management consultancies failing in the AI era?
No. The honest claim is narrower: the old engagement model of long timelines, big teams and generic playbooks is what breaks, whoever sells it. A firm that has genuinely changed how it works can still be valuable.
What replaces the traditional consulting model?
Something smaller, faster and closer: a trusted adviser who understands the business and moves at the speed of the technology, working alongside internal people who own the outcome, rather than a large team that arrives, charges and leaves.
Why does the pace of AI make slow consulting risky?
Because the ground moves suddenly. When a strong, cheaper model appears almost overnight and resets assumptions about cost and capability, advice built on last year’s assumptions is already behind, and a slow engagement cannot catch up.
The first honest voice on AI inside a company almost always has to come from outside it. Not because outsiders are smarter, but because an internal hire cannot tell you the truth without risking their own job.
Why the internal hire cannot be straight with you
An internal AI executive is carrying things an outsider is not: worry about keeping the job, office politics, still learning the culture, protecting their own salary and standing. Inside most corporate cultures you do not talk back to the boss, and you are certainly not meant to make them lose face. So when an internal person sees something the leadership does not want to hear, the safe move is silence.
There is a sharper edge to this. When an outsider brings a new perspective, the room offers praise and respect. When an internal employee comes off smarter than the boss, they quietly become a threat, and leaders do not want to feel threatened by their own people. That dynamic alone keeps the most useful internal observations unsaid. It is the same trap I described in The Proud Leader Who Handed Off His Own Future.
What an outside advisor actually trades on
Here is the fair objection, and I want to answer it directly rather than pretend it does not exist. If the argument is that an outsider is free because they do not fear for their job, someone will rightly say: but you are selling your next engagement, so you are not free either. True. So let me name the real incentive. An advisor’s reputation depends on being right, and on being remembered as the one who told the truth. The incentive rewards candour, not comfort. The employee’s incentive runs the other way, because for them it is a livelihood. For the advisor it is one client among many, and the willingness to be fired for the truth is the whole value.
That willingness has to come with judgment. Candour in service of the company, delivered at a pace the organisation can actually absorb, is the job. Not a grenade rolled into the boardroom. Move too fast and you damage the very company you were brought in to help. So the mandate is to say what no one inside will, and to know how hard the room can take it. This is also why buying more consulting hours is not the same thing, a point I made in Your Traditional Partners Are Failing You in the Age of AI.
The internal champion is the next step, not the first
None of this means you never build internal AI leadership. You do, and it matters. But it is the step after the honest reckoning, not the one that replaces it. The right internal leader, the living embodiment of AI I described in Who Should Actually Lead Your AI Initiative, is often already inside the building, as I argued in The Sleeper Has Awoken. Their moment comes once the outside voice has cleared the ground.
The outsider is not braver than your best internal person. They are simply free to be fired for telling you the truth, and right now, that freedom is worth more to you than another year of polite agreement.
If you are leading your organisation through this, I work with a limited number of senior leaders each quarter. Get in touch at Anglero.com.
Thomas Anglero is a Strategic AI Advisor, keynote speaker and author of Intro to Artificial Intelligence. He has delivered over 450 keynotes across 30 countries for organisations including IBM, the WHO, the World Government Summit and the European Commission. He founded the IBM Watson AI Lab for Cancer at the Oslo Cancer Cluster and closed over $500 million in enterprise transformation deals as CTO and Chief Innovation Officer at Cognizant.
Frequently asked questions
Why should the first AI advisor come from outside the company?
Because an internal hire cannot tell the whole truth without risking their job, salary and standing. An external advisor has none of those constraints and is free to say what no one inside will.
But isn’t an outside advisor also biased, since they want the next engagement?
Yes, and the honest answer is that an advisor’s reputation depends on being right and remembered as the truth-teller. The incentive rewards candour, and the willingness to be fired for the truth is the whole value.
Should an outside advisor just say everything bluntly?
No. Candour has to come with judgment, delivered at a pace the organisation can absorb. The job is to say what no one inside will, not to damage the company by moving faster than it can handle.
Does this mean a company should not build internal AI leadership?
It should, but as the next step, not the first. The right internal leader is often already in the building, and their moment comes once the outside voice has cleared the ground.
Traditional consulting partners are failing executives in the age of AI because their business model sells time and hours, while AI now delivers the same analysis in minutes. The second obstacle is the leader’s own working habits: AI has to be woven into every decision, not opened as an occasional tool. Both have to change before results arrive.
The partner running plays from a game that no longer exists
You are sitting in a meeting, listening to the same partner you have worked with for years present their quarterly update. The slides are sharp. The language is confident. The recommendations sound reasonable. And somewhere in your chest, there is a tightness you cannot name, because the results are not coming.
They will tell you they need more time. More hours. Another engagement. They will reframe the delay as complexity. But you already know what is happening. Your traditional partners, the ones who built the infrastructure that got you here, are running plays from a game that no longer exists.
This is not a criticism. These are capable people who built real things. But they built them in a world where information moved at human speed, where competitive advantage came from scale, and where the consulting model was built around selling expertise by the hour. That world is gone. An AI can now read every book in a library in seconds. It can analyse your entire pipeline overnight. And your partner is still scheduling a workshop for next month.
The second obstacle is you
The uncomfortable part is what comes next. Because the second thing holding you back is not them. It is you.
Not because you are inadequate, you would not be in that chair if you were. But because you are not yet using AI the way it needs to be used. Not as a tool you open when you remember, but as something woven into every decision, every analysis, every conversation. Something that pushes you the answers you need before you know you need them. That is what it means to be AI-native. And almost no one is there yet, because almost no one has had the space. You are moving from meeting to meeting, call to call, and by the time you sit down at your desk, you have not even opened your inbox. This is why AI is a culture project before it is a technology project.
The coach whose sport has matured
Think of a coach who has run the same drills and the same plays for an entire career, and they worked. The team won. But the sport has matured. The athletes are faster, more talented. The competition is different. The old playbook does not apply, and running it harder will not close the gap.
You are that coach. And the field has changed around you.
There is nothing wrong with your instincts. What needs to change is who you trust with this next chapter, and how deeply you trust yourself to learn a new way of leading. Your traditional partners want to sell you time and hours. The right partner asks what you need.
Frequently asked questions
Why are traditional consulting partners failing in the age of AI? Because their business model sells time and hours, while AI now delivers the same analysis in minutes. They built their expertise in a world where information moved at human speed and advantage came from scale. An AI can read every book in a library in seconds and analyse an entire pipeline overnight, while the partner is still scheduling a workshop for next month.
Is the problem only with the partners? No. The second obstacle is the leader’s own working habits. AI has to be woven into every decision, every analysis and every conversation, not opened as an occasional tool. Almost no leader is AI-native yet, because almost no one has had the space, moving from meeting to meeting without even opening the inbox.
What does it mean to be AI-native as a leader? It means AI is not a tool you open when you remember, but something woven into every decision, pushing you the answers you need before you know you need them. It is the difference between using AI occasionally and leading with it continuously.
What actually needs to change to get results? Both obstacles at once: who you trust with this next chapter, and how deeply you trust yourself to learn a new way of leading. Traditional partners want to sell you time and hours; the right partner asks what you need. Nothing is wrong with your instincts, but the field has changed around you and running the old playbook harder will not close the gap.
This edition is adapted from the Clarity at the Top podcast. Watch the full episode on YouTube.
Thomas Anglero is a Strategic AI Advisor, keynote speaker and author of Intro to Artificial Intelligence. He has delivered over 450 keynotes across 30 countries for organisations including IBM, the WHO, the World Government Summit and the European Commission. He founded the IBM Watson AI Lab for Cancer at the Oslo Cancer Cluster and closed over $500 million in enterprise transformation deals as CTO and Chief Innovation Officer at Cognizant.