An ambition often contains an assumption about the market: there is room to grow, customers want this, demand is rising fast enough to sustain the investment. As soon as that ambition presupposes AI work, the nature of that assumption changes. It is no longer just about whether the market is growing, but about whether the market is growing in a way that fits what AI in this company can already take over, what still requires oversight, and what remains human work. The market growth gate of the ambition test therefore asks a more precise question: is the growth you are assuming based on demand that already exists today, or on demand that only arises once work is organized differently.
That difference is not theoretical. A management team speaking about market growth sometimes means revenue growth at unchanged capacity, and sometimes revenue growth that is only achievable because part of the work shifts to AI with human oversight. Both are legitimate. Only the second requires a different kind of evidence, and that evidence is missing from most strategy documents.
The shift this test revolves around is not something for the future. In some companies, AI already takes over parts of customer contact, data processing, or first-line advice today, with an employee approving or rejecting. In other companies, the same work still rests entirely with people, not because the technology is lacking, but because the organization cannot yet demonstrate which part of the work can actually be taken over. That difference largely explains why two companies with the same market opportunity arrive at different growth forecasts. Whoever already knows which tasks become available can deploy that capacity for extra volume without extra FTE. Whoever does not know this still has to translate growth into extra people, and hits a limit sooner.
Market growth that leans on AI deployment therefore presupposes a capability that sometimes already exists and sometimes does not: the ability to know which work falls into which of the three categories, and how much capacity that frees up. Without that overview, a growth figure is a hope, not a plan.
This gate is not market research and not advice on which market you should enter. It is a test of the assumption already embedded in the ambition. Sufficient evidence consists of three elements. First: a substantiation of demand growth that is separate from the AI promise, that is, what the market would do if nothing changed in the organization of work. Second: an estimate of the capacity freed up because certain tasks move to AI execution or AI with oversight, expressed in hours or FTE, not in a percentage without a range. Third: a link between that freed-up capacity and the additional demand the ambition assumes it can serve.
If one of the three is missing, the market growth assumption has not been tested but assumed. That is not necessarily a problem for the ambition itself, but it is for the conversation about it: a management team that says "growth" without these three elements uses the same word for different plans. This gate is not separate from the other readiness dimensions. Whether that additional demand can also be served operationally is connected to how you test whether the organization can carry the operational side of an AI ambition, and whether the customer accepts the shift itself is described separately in how you test the customer demand behind an AI ambition.
A market growth assumption that does not hold up under testing is information, not a verdict. There are three routes. The first: adjust the growth expectation to what is demonstrable, with a timeline that fits the pace at which capacity actually becomes available. The second: maintain the ambition but rewrite the substantiation, so that it no longer leans on an AI shift that is not yet proven, but on other levers such as price, margin, or geographic expansion. Here the question also touches the margin side of the ambition, to be tested via how you determine whether the margin of an AI ambition remains achievable. The third: go through the gate again after a period in which the organization first demonstrates which work can actually be shifted, before the growth ambition is built on that.
What does not belong at this gate is a decision about personnel. If a lower market growth outcome should have consequences for staffing levels, separate legal requirements and a different process apply than this test. The ambition test delivers an outcome about readiness, not a substantiation for that decision.
The underlying question at this gate — which work in this company can genuinely be taken over by AI, which part requires oversight, and which part remains human work — is answered per task with the work scan from FTE TO AI.
To see whether your market growth assumption leans on demand or on shift, you do not need to go through the full test right away. A free readiness check of eight short questions, one per dimension, shows where your organization is furthest along and least far along. The full ambition test, with all four layers and five confidence gates, is under construction. If you want to know first how you bring the rest of the organization along once the outcome points toward change, that connects to how you involve the workforce in a strategy change without the process stalling.
Vertel wat u wilt bereiken, dan kijken we samen wat daarvoor moet staan.
Answers come from this site’s knowledge base. Not tailored advice, and not a scan of your company.