Blog Series: The Impact of AI in Impact Investing – Part 3/10
In my first post I wrote about AI as a force for equal opportunity. In my second post I reflected on the difference between equal opportunity and equal outcome and why intent makes all the difference. Now I want to take this one step further: what does this mean for us as investors in practice?
With AI, the question is rarely whether something can be built. Most things can. The real question becomes: why is it being built, and for whom?
Venture capital has been built on clear principles, such as testing product/market fit, validating scalability, and backing strong traction. These principles remain as important as ever. But in the age of AI they are no longer enough. If building is easier, then the challenge for investors is not to ask can it scale, but should it scale.
That is where problem/impact fit comes in. Does the product solve a problem that truly matters? Does it broaden participation, or does it risk reinforcing existing inequalities? Does it create access, or limit it to the already privileged?
For Shaping Impact Group this is exactly where the logic of venture capital and impact investing come together. The principles of venture capital keep us sharp on execution and growth. The lens of impact ensures we look at intent and inclusion. Together they create a stronger methodology, one that can guide impact investors like us as AI accelerates both opportunity and risk.
This also means that our role as investors is shifting. It is not enough to evaluate business models on efficiency and scalability alone. We need to test whether founders are building solutions that society actually needs, and whether their use of AI strengthens or weakens equality of access. That requires a different set of questions in sourcing, a different lens in due diligence, and a different type of support once we are invested.
In my next post I want to write about how to measure this, how to combine the financial KPIs every investor needs with the impact KPIs that tell us not only if a company can scale, but whether it should.
I am curious to hear your thoughts: when you look at impact AI-driven companies, what is the first question you think investors should ask? Let me know here on LinkedIn
