Misuse of AI in Valuation Leads to Trust Issues
It is a big mistake to generate a valuation analysis or report for your company by first deciding on a desired valuation target—for example, US $20 million to support a seed-stage fundraising—and then asking AI to produce the analysis to match that figure. For startups in particular, this approach will not build trust with potential investors; in fact, it is more likely to destroy it.
Why is this so damaging? First, it is unethical. Second, while AI can indeed produce a polished, comprehensive-looking valuation report, it can just as easily be instructed to “work backwards,” creating assumptions and inputs designed to justify a pre-set outcome. Such analysis may look structured, but it is fundamentally misleading, as there is no genuine connection between the company’s actual facts—its business model, operating performance, development milestones—and the figures presented. The output lacks credible evidence and cannot withstand professional scrutiny.
And what if you go a step further, generating or fabricating supporting “evidence” to back up the assumptions and conclusions? My answer is simple: Good luck. Do not underestimate the experience and diligence of professional private equity and venture capital investors—they will identify gaps, inconsistencies, and unsupported claims long before you even realise they exist.
In valuation, credibility is everything. Once trust is lost, no amount of clever AI-generated output can win it back.
