AI is not just something VCs are looking to invest in; it is having a tangible impact on which startups they back. From sourcing deals to screening founders and conducting due diligence, AI is reshaping how investors find, evaluate and prioritise opportunities.
For deep tech founders, this changes everything: what you say, where you say it, which signals matter, and how credible you look - not just to a person, but to the algorithm.
The shift in discovery
According to CRM and market intelligence company Affinity, 64% of venture capital firms are using AI to discover new investment opportunities for their pipelines. Data aggregators, such as Harmonic, Pitchbook and Dealroom, act as startup discovery engines, collating comparable data points on millions of startups from as early as incorporation.
These systems ingest data from websites, GitHub, preprints, patents, conference agendas, media coverage and social channels to identify patterns that fit the venture model. If your startup is invisible across these channels, you may never even enter the funnel.
Clarity becomes a superpower
For deep tech founders, this means your public footprint matters more than ever. Clear descriptions of your technology, consistent terminology, and visible evidence of progress increase your chances of being surfaced by algorithms as well as humans.
Deep tech doesn’t often fit neatly into the sort of patterns that these AI models are best at identifying, which makes it even more important that founders are able to communicate the essentials in the simplest and clearest way possible. Any anomalies in production cycles or regulatory delays need to be explained, and nothing left to be interpreted by intuition.
Mistakes are more costly than ever
AI tools are also being used to triage inbound pitches. Decks, summaries and data rooms are scanned by algorithms for keywords, comparables, traction markers and risk flags. This accelerates decision-making, but it also compresses the window to make a strong first impression, and exacerbates the impact of even the smallest of errors.
Typos, missed explanations or outdated information that could all feasibly be missed by a human first pass can trip exclusion protocols and cause your startup to miss out. Assume your first reader will be an AI model and aim for short, simple and precise.
Communications becomes a competitive advantage
Roughly two thirds of AI citations come from editorial and PR sources, not ads or owned channels and websites. Deep tech startups that aren’t visible to large language models are not just missing out on building their reputation for potential customers, they are also missing out on opportunities for investment.
As AI standardises parts of the dealflow process, the ability for startups to differentiate themselves shifts to storytelling and credibility. Crisp, clear messaging with efficient execution is crucial, as is ensuring that your digital footprint is accurate and up to date. Incorrect information on jobs boards, social media or incorporation registries, for example, can all trigger the initial algorithmic filters.
An AI-powered investment landscape doesn’t mean the best startups won’t still succeed, it just changes the priorities in the early stages. This means that clarity beats cleverness, visibility beats secrecy, and communications is no longer optional. If you want to be found, understood and funded, you need to speak coherently to both humans and machines.
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