Raising capital has never been simple for early-stage founders. The pressure to build a compelling pitch, identify the right investors, maintain outreach momentum, and still run the company creates a uniquely draining marathon. But according to Brigitte Baumann, founder of efino.ai and one of Europe’s most respected angel investors, a structural shift is underway, and AI is already quietly changing how both founders and investors operate.
This became clear during a recent webinar hosted by Dealum, where Brigitte unpacked the realities of AI-driven fundraising from both sides of the table. Her message was straightforward: the change is real, but uneven. Investors are adopting AI faster than founders; the biases built into these tools are significant, and the human element is still far from replaceable.
Investors are using AI earlier, deeper and more aggressively
One of Brigitte’s key observations was that investors have embraced AI tools more quickly than founders themselves. Venture firms, she explained, increasingly rely on automated systems to surface relevant startups, map sectors, and perform early-stage due diligence.
“Some investor committees already allow the use of AI when screening applications,” she noted, pointing out that AI can now highlight potential red flags, benchmark financials across thousands of companies, or compile a background overview of a founding team in seconds.
This efficiency sounds positive until you consider the underlying bias. Brigitte stressed that most models are trained on US data and Silicon Valley-style growth archetypes. As she put it, AI tools “inherently favour hyper-growth profiles,” meaning European founders, impact sectors and companies with more realistic growth paths may be unfairly downgraded before an investor ever looks at them.
Founders are using AI mostly for polishing, not strategy
While investors automate screening, founders still use AI mostly for surface-level tasks: pitch decks, emails, website copy, and sometimes investor lists. Brigitte argued that this is a missed opportunity. The real value, she said, lies in using AI to understand readiness, refine financing strategy, and evaluate whether the fundraising ask is credible for the next milestone.
She highlighted a reality many founders ignore: “Most startups today go through four to six financing rounds.” That means every round needs clear KPIs and a data-driven rationale. AI can support this, but only if founders use it beyond the cosmetic layer.
The risk: skipping the thinking and getting caught instantly
Both Brigitte and webinar moderator Darja raised a concern that resonated strongly: AI makes it dangerously easy for founders to bluff.
Darja recalled that after ChatGPT launched, application quality suddenly became suspiciously polished. “You can immediately see when something is written by AI because it’s just too perfect,” she said. The problem becomes obvious during real conversations, when the founder cannot answer second-layer questions because the underlying thinking was never theirs.
Brigitte agreed. Founders who outsource strategic reasoning to AI expose themselves instantly once an investor probes deeper. “It looks good on level one,” she said, “but the moment we ask follow-up questions, it becomes clear they had no idea how the model arrived at those answers.”
AI is amplifying existing biases – especially gender gaps
Brigitte has long worked on gender bias in funding and warned that AI tools amplify these disparities rather than address them.
One example: projections. Women tend to submit realistic forecasts; men tend to overstate. AI interprets male forecasts as ambition and female forecasts as a lack of ambition, even though women are statistically far more likely to hit their targets.
Another example is sector familiarity. Many female-led startups operate in the femtech and health niches, where the average investor, and therefore most training data, has limited expertise. Unsurprisingly, companies in these less-familiar sectors receive lower scores.
Her advice for founders was simple: stay authentic, but back up your numbers with evidence. Pipeline proof, signed letters of intent, and a clear breakdown of underlying assumptions help counteract automated misinterpretations.
The future: AI agents talking to AI agents – but not yet replacing humans
Darja raised a concern many founders share: what happens when founder-side AI and investor-side AI start talking to each other? Will early-stage investing lose the human element entirely?
Brigitte believes that automation will expand dramatically, especially in tasks like data rooms, syndicate creation and initial filtering. She also mentioned emerging “pure AI funds” that plan to rely solely on algorithms for deal sourcing and decisions, although she suspects it will take a decade to understand whether they work.
Still, she remains optimistic about the human layer. “I want to keep the human at the heart of this,” she said. “I still want to meet the entrepreneur, understand who they are, and see how we connect.”
Darja reinforced this point from an investor perspective: for pre-seed and seed stages, “you bet more on the team and the drive.” No AI system can reliably evaluate resilience, chemistry or founder intuition. These qualities often define early-stage success.
A future of efficiency – not replacement
The consensus was clear: AI will significantly reshape fundraising, but it will not erase the human element. The winners will be founders who pair AI-enabled efficiency with human authenticity, automating the grunt work while keeping strategic thinking, storytelling, and relationship-building firmly in their own hands.
Brigitte summarised the vision simply: bring more efficiency and effectiveness into the process, but keep humans in the centre.
Rewatch the full webinar below or directly on YouTube.
