In case you’ve been completely in the dark about the latest in the world of startups and tech, AI is all the rage now.
For the first time in years, we are seeing mass adoption of generative AI technologies on an individual consumer level—unprecedented progress that happened in just a single quarter despite the fact that AI has been the buzzword of the decade to date.
As a result, AI has become the hottest area for innovation and investment, with new startups stepping into the spotlight and offering disruptive solutions across a variety of sectors and verticals. It’s only a natural outcome that investors are keen on discovering the next ChatGPT or Dall-E equivalent to invest in, given the capacity for these tools to revolutionize any given industry or line of work.
But it’s not as easy as it seems to get investment as of today—even though startup investment was considered the epitome of the “American Dream” or even the Gold Rush a few years ago, the situation has changed due to large economic shifts—and securing investment is a bigger challenge than it used to be before. So what exactly do investors look for when deciding to back an AI startup?
In this article, I'll explore five crucial factors that should drive the decision-making of VCs and investors when identifying investment opportunities and evaluating long-term potential in the competitive and oversaturated AI space.
1. Problem And Solution Match
This might seem like an obvious qualifier for any startup, not necessarily specific to AI startups per se—but it becomes even more important for advanced technology like AI in particular. This stems particularly from the fact that AI is trained based on specific data samples that make it more or less helpful to specific industries, problems and areas—and the niche application at first can serve as a strong starting point for the future scaling of the business should it strike a chord in its initial development stage.
Investors must evaluate an AI startup on its ability to offer a resolution for a significant problem in a specific market and—whether it’s an obvious or implicit pain point. The value proposition should be clear, and the technology should have the potential to disrupt the existing market landscape.
2. Product-Market Fit And Growth Potential In The Market
Whether it’s a red or blue ocean that the startup is entering, it’s key to prove that there is significant potential for growth and market share acquisition. Identifying a specific problem to offer a solution for is only one way to achieve this—it’s also important to identify the market entry game plan, whether it’s creating a market, quickly growing an unsaturated market or disrupting a currently saturated market with a brand new offering.
Needless to say, investors often desire potentially lucrative and high-potential market opportunities. They want to see a startup that can tap into a market with substantial revenue potential, with a clear path to acquiring customers and scaling the business.
An easy way to showcase strong fit and potential is by demonstrating early traction, be it through a minimum viable product (MVP), an initial customer/user base or strategic partnerships. Another powerful way to secure investor trust is by winning validation from industry experts or notable early customers.
3. Proprietary Technology, AI Intellectual Property And Expertise
Proprietary technology is key to differentiating your offering from the sea of competitors gunning for the same investment. This includes patents, proprietary algorithms, unique data sets or innovative approaches that set the company apart from competitors—and any kind of IP protection that can offer a strong competitive advantage and thus increase valuation. A strong technical team with expertise in AI and related fields is also crucial.
Another important way to truly showcase differentiation is by putting together a team with the necessary track record, skills and expertise to drive the AI technology development forward. It’s not uncommon for investors to take the approach of investing in talent and teams rather than an abstract idea—so it’s important to have the necessary resources in terms of skills and knowledge in place before anything else.
4. A Strong, Diverse Founding Team
Building on the idea of necessary expertise above, it’s important not to forget the diversity of perspectives and skills required to build an end-to-end successful company. A capable and experienced founding team with a proven track record is essential—and the trick is to demonstrate team balance with complementary skills in engineering, business, marketing and direct industry expertise.
5. Scalability And Long-Term Profitability
Investors don’t just invest in an idea—they invest in long-term ROI and scale. Prior to approaching any individual or fund for investment, it’s important to have a strong understanding of the long-term growth plan, business model and monetization opportunities. Illustrating the potential for the proprietary AI solution to be scaled beyond the initial industry or market is also key to demonstrating a trajectory for acquiring more market share.
A clear and viable business model—at least to experiment with at the beginning of the growth journey—that shows how the startup will generate revenue and achieve profitability is essential to attracting solid backing. Investors will meticulously assess the startup’s unit economics, pricing strategy and potential revenue streams.
Last But Not Least
Before building out a startup, it’s important to identify a desired exit strategy or scenario, be it an acquisition, merger or initial public offering (IPO). This provides investors with a clear picture of what kind of return on their investment to expect and what the product roadmap will look like as the startup grows.