The easiest way to misread go-to-market (GTM) in deep-tech is to treat it as a volume function. More pipeline. More coverage. More activity. Zeki’s research points to a different conclusion. GTM hiring is now outpacing technical hiring across most scale-up verticals, and the same research shows GTM expertise becoming more valuable as the role itself evolves. This is not a signal about volume. It shows that, at a certain stage, value creation depends less on adding commercial capacity in the abstract and more on how technical capability is made usable in the market.
Hiring Velocity of Technical and GTM Talent in the Last Year Across Verticals
Zeki’s data helps explain why. The most important roles are often the hardest to define, the hardest to fill, and the most expensive to get wrong. In deep-tech and AI, job descriptions lag reality, salary benchmarks age quickly, and the strongest people are rarely active in the market. The problem begins when companies apply old definitions to roles that have already changed.
Value sits where capability meets context
One of the clearest signals in the market is the growing importance of roles such as solutions engineers. Customer engagement in AI-driven businesses is more consultative and iterative, with teams shaping a solution around a specific client environment rather than moving buyers through a fixed product. These roles increasingly draw from data, systems and engineering backgrounds as well as commercial ones.
That pattern points to where value is being created. It sits at the point where technical capability must be interpreted, adapted and made credible in a real operating environment.
In simpler markets, GTM can sit further downstream. In deep-tech, it sits much closer to the moment where the product is tested against reality. The gap is not simply between seller and buyer. It is between what a product can do and what a customer can actually use.
It shows up in monetisation, not just messaging
As companies move towards product-market fit, the constraint shifts. The question is no longer whether the product works in principle, but how quickly and reliably that value can be captured.
This is where GTM becomes decisive.
Its contribution is not limited to generating demand. It determines how clearly the product is positioned, how consistently it lands with the right buyers, and how efficiently complexity is handled inside the sales process. In practical terms, it increases the speed at which technical promise becomes revenue.
This is also why different commercial profiles are beginning to matter. The market is not simply rewarding experience or seniority. It is rewarding usefulness—the ability to operate in environments where the product, the process and the market are still taking shape.
The value is partly in reducing uncertainty
The GTM talent market is notably more fragmented than the engineering market. There is no small set of employers or backgrounds that define the best operators. That fragmentation reflects something fundamental.
In deep tech, commercial work is not performed in stable conditions. It exists at the edge of uncertainty—technical, operational and commercial.
Value is created by reducing that uncertainty.
Sometimes that means helping a customer understand how a product fits into their environment. Sometimes it means identifying where assumptions do not hold under real conditions. Sometimes it means shaping how a product is positioned or delivered so that it can be adopted at all.
This is why title is such a weak proxy. The work does not align neatly to a single, standard career path.
What this changes
Taken together, the pattern is consistent.
GTM becomes more important as companies move from building to monetising. The work moves closer to technical interpretation. The talent required becomes harder to define and harder to find. This leads to a different definition of value.
GTM is not simply the function that converts demand into revenue. It is one of the functions that determines whether demand becomes usable at all — whether a technically valid product can exist as a commercial system.
Where the value actually sits
The value of GTM in deep tech is not only in revenue produced. It sits in three connected effects.
- It reduces the distance between capability and adoption.
- It accelerates the point at which a company understands where it truly works.
- And it increases the speed and reliability with which that understanding becomes revenue.
Each of those effects compounds the others.
From the outside, GTM still looks like sales. Inside the company, it plays a different role.
It is one of the mechanisms that turns possibility into proof.
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