Disclaimer: These thoughts are my own and do not constitute investment or legal advice. They are purely educational. Please refer to the terms and conditions for further information.
Over the last half year, the availability of venture capital and the number of corporate investments has tanked. Traditional venture rounds, bridge rounds, and acquisitions have all gone down in all sectors. That is all sectors except for artificial intelligence. Why is artificial intelligence different? Let us look at the points that drive the difference and how to deal with them.
What is an investment’s value?
Compared to on-market investments, early-stage companies are valued based on the potential return an investor believes an IPO or merger brings than by complex numbers. Returns per share are great for established stocks, but a 6-month company building an AI model will have widely swinging values based on deals closed and the timeline of developments. Consequently, startup valuations are a mixture of complex financial projections, gut feelings, and voodoo, which can vary between individual investors. Yet, investors should base them on the actual estimates of the company’s potential and the issues ahead.
Fear of Missing Out
Yet, with many startups operating in cutting-edge fields, such as AI, there is often little material for comparison. Thus, investors might be driven by the fear of missing out, allowing companies to move the valuation and investment sums ever higher without a clear path toward profitability. We have seen similar patterns in the hay days of the app and gig economy, where valuations for WeWorks and Uber sored, as investors believed they were betting on the next big thing. Thus, the fear of missing out on the potential upside and million-dollar exits drives investors.
Imagination Before Investment Potential
Yet, investors still understood the potential of the gig economy. In AI, imagination and science fiction have taken over for some. If we look at today’s AI field, from Machine Learning to Large Language Models, they are great at repetitive tasks and tasks based on existing data. Creativity, genuine empathy, and long-term learning are all beyond the current models. Thus, our AI is still closer to the computers from the 1990s than the systems presented in Star Trek.
In terms of music, AI will be able to create the next Taylor Swift song, as there are enough of her songs to learn. AI will, however, not be able to create a new music genre.
Yet, many startups are trying to sell solutions that require creativity or empathy. One that recently came over to my desk was in debt counseling. AI would be great to build you a budget. AI would be good to summarize meetings and send out little affirmations now and then that a client is on the right path. However, debt counselors, like mentors and coaches, do much more. They have to employ a lot more listening and psychology than pure math. Both are areas where AI isn’t there yet and might be unable to do them in the foreseeable future.
Consequently, I passed on it. Yet, the company still got funded, and only time will tell whether my call was correct.
What to look for in AI Startups?
The example already shows that, in many cases, our ideas about AI and reality diverge. AI is excellent at doing repetitive, comparable small, and mechanical tasks. Today’s AI is more akin to overcharged automation than it is to Data from Start Trek.
Thus, if you are looking at AI application startups, going for the ones that solve real-world problems, trying to make humans more efficient, or eliminating minor annoyances might be crucial to success for the next 2-3 years.
If you want to aim for the big picture, the companies developing the underlying models might be the better bet. After all, they are building the basis for the next round of AI that can simulate creativity or empathy.
The Bigger Picture in AI Investments
While AI startups have the chance of building the next unicorn, by definition, few will. The fear of missing out on investors shouldn’t overwrite essential due diligence. Checking whether technology can achieve something requires some domain knowledge, yet it is much better than praying you made the right choice.
Absent reasonable due diligence, several companies on the stock market will benefit from the AI boom. Companies that build the computing hardware needed or run the Data Centers will be victorious in the current boom, no matter which startup succeeds.
Don’t let AI be your Crypto Investment
If the hype around Bitcoin and Co. has shown anything, it is that publicity and high ideas don’t replace solid business ideas. While the first wave of AI might produce some unicorns, so will the second one. If you plan to invest in the field, take the time to understand what is going on, and don’t let the hype carry you. Whether you invest money or time, a solid understanding and a fast yet deliberate pace are worth more than being the first to burn.