Published 29 August 2026
Het Financieele Dagblad, the Dutch financial daily, reported this week that the big consultancies have opened a hunt for a new kind of AI specialist. Deloitte, Accenture, Capgemini and McKinsey are all recruiting the same profile: the forward deployed engineer. Not because it is fashionable, but because their clients are demanding it. Those clients are done experimenting and want AI running safely, at scale, inside their actual processes.
Now read that headline from your own chair. The most expensive advisory firms in the market are fighting over the same scarce people, on behalf of clients who can afford their rates. The question is not whether that talent gets found. The question is who it ends up working for. Odds are, that is not you.
What is a forward deployed engineer?
A forward deployed engineer (FDE) is an AI specialist who combines a technical background with the skills of a consultant: they design, build and integrate AI solutions into daily operations, and sit at the client's table while doing it. Not a builder who delivers from a distance, but the person who carries the technology onto the work floor.
Palantir coined the title, the big AI labs adopted it, and Deloitte has now turned it into a full US service line. When a Silicon Valley job title starts appearing in European consulting vacancies, that tells you exactly where the market is.
Why everyone suddenly wants the same profile
The hunt is not a fad. It is the logical consequence of a painful lesson the numbers have been teaching for two years.
| What happened | The number | Source |
|---|---|---|
| GenAI pilots that produce no measurable P&L impact | 95% | MIT NANDA |
| Agentic AI projects predicted to be scrapped by end of 2027 | over 40% | Gartner |
Companies have learned, expensively, that the problem is not the AI model. The problem is the last mile: from impressive demo to the real process, with real data, real permissions and real users. That is exactly the gap the forward deployed engineer exists to close. The market just admitted out loud what we have been writing here for a while: AI success is not a model choice, it is an integration problem.
The math nobody does for you
If you are a corporate with a big-four budget, this is good news: the scarce talent is being recruited, trained and flown in on your behalf.
For everyone below that line, the math is uncomfortable. The firms themselves say that people who master both the technical and the advisory side are hard to find. What is scarce, and fought over by the highest bidders, gets expensive. And whoever sells expensive talent brings it to the clients with the deepest pockets and the longest contracts. Small and mid-sized companies stand at the back of that queue. Not because their problem is smaller, but because their budget is.
Meanwhile your own organisation started without you: at over 90% of companies, employees already use personal AI tools for work, mostly outside any policy. Waiting for the talent market to trickle down does not fix that.
What you can do without a big-four budget
Look again at what the forward deployed engineer actually does: bring AI to where the work happens, grounded in the company's real data, translating between the technical and the executive table.
That is a role. But the core of it is not a person, it is a capability. And there are two ways to get that capability into your company.
Route one: hire the scarce specialist. The right call when you need a complex integration or custom software. Just do not count on quick availability, and know you are bidding against firms with more money.
Route two: become AI-native yourself. The questions an executive most wants to put to AI (what is moving in my numbers, where is margin leaking, what do these hundred documents actually say) do not require a nine-month implementation. They require an assistant at your level, grounded in your data, on your laptop. That exists today, and no recruiter is involved. The step-by-step version is in how to implement AI: what you actually need.
The routes are not mutually exclusive. But the order matters: the executive who becomes AI-native first knows exactly what to hire a specialist for later, and can no longer be sold a pilot that dies in a drawer.
What AI Board does not do
Honesty first. AI Board is not a consultancy and not a staffing agency. It will not build your ERP integration, write custom software for your production line, or replace an engineer running a months-long implementation. That work still needs human talent, scarce or not.
What AI Board does do: put the thinking and analysis half of that scarce specialist on your own desk, today, with no queue.
AI Board is your personal AI assistant that makes you AI-native: it runs on your own laptop, grounded in your company's data, and gets sharper as your knowledge grows. Private by design, reasoning at CEO, CFO and CTO level, so you ride the AI wave instead of swimming behind it.
Frequently asked questions
What is a forward deployed engineer?
A forward deployed engineer is an AI specialist who combines a technical background with consulting skills: they design, build and integrate AI solutions into daily operations while sitting at the client's table. Palantir coined the title, the major AI labs adopted it, and consultancies such as Deloitte now run entire forward deployed engineering practices.
Why are AI specialists so scarce?
Because the profile in demand combines two worlds that rarely meet in one person: deep technical AI knowledge and the advisory skills to work with an executive team. According to Het Financieele Dagblad, Deloitte, Accenture, Capgemini and McKinsey are all chasing this same profile, precisely because their clients want AI moved from pilot to production. The firms recruit externally and retrain internally, and say themselves that people who master both sides are hard to find.
Should my company hire an AI specialist?
For complex integrations and custom builds: probably, eventually. But the questions an executive team has today (insight into its own numbers, documents and decisions) do not need a scarce specialist. A personal AI assistant on your own laptop, grounded in your own company data, covers that half without a hiring process. Start there, and you will know precisely what to hire a specialist for later.
Can I become AI-native without an AI team?
Yes. Being AI-native is not a headcount question but a way of working: asking your own questions of your own data instead of waiting for someone else to compile the report. That starts on one laptop, with one decision-maker, in days rather than quarters. See what an AI-native executive is for what that looks like in practice.
The big firms are fighting over the people who bring AI to the work. You can wait for whoever is left over, or start today on the side of the equation you control. See what an AI-native executive team runs on →, or first read why most AI projects fail and what your shadow AI economy is already doing.