In past articles, I have written about the threats and opportunities of Artificial Intelligence(AI) but the plot is now thickening rapidly, so I want to dig deeper. Specifically, I want to focus on the challenges of investing in AI startups. What are these challenges and how will venture capitalists deal with artificial intelligence? I’ll cover this aspect of investing in AI below.
One of the Challenges of in Investing in AI Startups: It Requires Specific Knowledge
In my opinion, AI will have a massive impact on the Venture Capital industry as it offers VCs many opportunities and severe challenges. One of the challenges of investing in AI startups is the lack of familiarity and understanding of AI itself.
Although I am not heavily involved in today’s AI technology, I have been an interested observer since writing my Ph.D. thesis in one of the first AI-oriented programming languages—Information Processing Language—5 (IPL-5), which two of my thesis advisors at Carnegie Mellon University—Allen Newell and Herb Simon–created. Also, several of my VC investments have involved AI—a voice recognition system, a neural network-on-a-chip, and currently, a hardware architecture optimized to reduce the power requirements of the large language models used in AI.
Many companies are already using artificial intelligence for activities like customer support, applicant ranking, contract review, problem-solving, document drafting, etc. So, one challenge for venture capitalists will be to start considering how effectively startup companies use AI tools. Determining this will require considerable knowledge of AI.
VCs are seeing many interesting AI companies in which to invest. However, AI companies can be very technical and challenging to understand. I don’t think the average “generalist” VC has the tools to perform adequate due diligence on some of these companies.
Complicating the VC’s Task: Uncertainty in AI’s Applications
AI already presents a challenge: How can investors tell who wrote the business plan or pitch deck? Will the VCs be able to tell if a business plan or pitch deck was written by AI? Maybe. Only the most knowledgeable and AI-experienced VCs are likely to have this skill. So, part of the challenge of investing in AI startups is determining how these companies are using it. Is their pitch deck born from knowledge and competency, or did they seek help from an outside source? Is that source AI?
Here are a couple of interesting anecdotes that illustrate these thoughts:
Recently, after reviewing a pitch deck with an entrepreneur, I wondered how difficult it would be for AI to write a business plan for a similar company. So, I dictated a few short paragraphs into my cell phone and asked ChatGPT to create a business plan. The result was a 7-page document that was a perfectly reasonable first draft of a business plan for a similar company.
Then, I asked ChatGPT to create a pitch deck for the company, and I received an 8-slide pitch deck that addressed most of the most critical issues. I could have asked for more detail in the business plan or the pitch deck, but ChatGPT made the point. Could I have discerned that the documents were created by AI, not by a person? I’m not sure. They were very professional sounding.
Is AI a Replacement for Competency or a Tool for the Competent? Further Challenges of Investing in AI Startups
To further the point, a few weeks ago, I received a fairly lengthy email from the CEO of a major institution, and because it was very consistent in style and a little slick, I wondered if it had been authored or possibly edited by Artificial Intelligence. So, I asked ChatGPT to see if AI had written it. ChatGPT’s response was, “I can’t tell for sure. Certain aspects suggest that AI created it, but others suggest a human wrote it.” And ChatGPT listed three aspects in each direction.
In other words, If I, as an investor, can’t be 100% certain the team I am talking to wrote a business plan or pitch deck, what do I do? Can you see why this uncertainty could be among the challenges of investing in AI startups?
Why Are These Seen as Challenges for Investing in AI Startups from a VCs Perspective?
In the case mentioned above, the uncertainty puts more-than-normal emphasis on me (the investor) to check the team members’ backgrounds and make certain that they have the skills to create the documents and that they did write them—and that they have the skills needed to build the company.
The huge mistake would be to get snowed by a clever pitch deck, only to discover that the creators do not have the competence to create or execute the plan.
Another one of the challenges of investing in AI startups, which I mentioned first, is determining if the startup is capable of using AI tools effectively and to their advantage. Certainty is an important determining factor for venture capitalists. They need to trust in the companies they fund, but they also need to understand how AI can impact those decisions. And, as I’ve mentioned, the average “generalist” VC may not be able to do that. So, there is hesitancy. Especially from those with only small venture capital funds.
So, the question is, who WILL invest? Where can AI startups expect to find funding? And how will those capable and willing to invest despite the challenges of investing in AI startups find the startups in which they want to invest?
I’ll cover this in my next blog, so that AI startups seeking funding can be more prepared to get it.
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