During San Francisco Tech Week I overheard that a Nordic manufacturer of automotive seat belts was reportedly scouting for an AI company to acquire.
Seat belts? AI? Whaaat?
A little research reveals two such manufacturers, Autoliv and Holmbergs,¹ both based in Sweden. I also learned that Volvo is already using billions of real-world driving data points to feed its AI safety systems, with over-the-air updates that continuously improve vehicle safety.²
Suddenly, the idea doesn’t seem so strange.
Thinking about the possibilities for a seat-belt manufacturer acquiring the right AI capabilities: they could combine crash-prediction data with occupant attributes to adjust belt tension in milliseconds during an accident; they could use AI-powered digital twins to replace Crash Test Dummies and simulate thousands of collision scenarios, while reducing the need for expensive destructive crash testing; they could even use data as a new revenue stream. An AI-enabled safety company could analyze millions of driving events to identify patterns in collisions, near misses, and occupant injuries. Properly anonymized, this aggregated risk intelligence could be licensed to insurance companies, fleet operators, and automotive OEMs.⁵
These opportunities extend well beyond manufacturing seat belts and could transform a component supplier into a predictive safety technology and data analytics company. Starting to get it?
But there’s an even bigger lesson for AI founders.
While venture funding is setting records, a disproportionate share is flowing to just a handful of companies. In Q3 2026 there were two dozen billion-dollar funding rounds that absorbed fully one-third of all global venture capital.⁶
Meaning that many promising AI startups probably won’t secure another funding round on acceptable terms, and some won’t raise again at all. They’ll need to find an exit, and the obvious buyers on the list are going to be flooded with choices.
But what if the most valuable application of your AI technology isn’t the one you’re selling today? What if your computer-vision model, or proprietary dataset, or machine-learning capability is worth more to an industrial behemoth or real estate conglomerate than to another software company?
The right strategic buyer doesn’t just acquire what your company does today. It acquires what your technology could enable tomorrow.
This is precisely why at Rocket Science, our Valuation Engineering process begins with a levers audit to identify underlying assets and capabilities that could create disproportionate strategic value for an acquirer. Then we look beyond conventional strategic and financial buyers to identify non-obvious acquirers—companies in adjacent sectors that could use your assets to leapfrog their competitors, crack open new markets, or fundamentally reinvent their businesses.
Because your highest-value exit may be hiding in an industry you’ve never considered.
Sources:
- https://www.autoliv.com/seatbelt; https://www.holmbergs.se/product/seat-belts/
- https://www.volvocars.com/us/safety/technology/; https://www.volvocars.com/us/media/press-releases/16E8682FC787809D/
- https://www.autoliv.com/press/autoliv-advances-vehicle-safety-through-virtual-testing-2479733
- https://www.nhtsa.gov/document/nhtsa-advanced-anthropomorphic-test-devices-development-and-implementation-plan-2024
- https://content.naic.org/insurance-topics/telematics; https://www.ftc.gov/news-events/news/press-releases/2026/01/ftc-finalizes-order-settling-allegations-gm-onstar-collected-sold-geolocation-data-without-consumers
- https://news.crunchbase.com/venture/q3-2026-global-startup-funding-ai-billion-dollar-rounds-exits-data/