Venture capitalists have a detailed guide to investing in software-as-a-service (SaaS) companies that has served them well over the past few years, making it an attractive investment.
But the lessons venture capitalists have learned from investing in SaaS do not apply to the world of artificial intelligence. AI companies take a very different path than SaaS providers, and the old rules just don’t apply.
Here are four things VCs are getting wrong based on their previous success in SaaS investments related to AI:
1. ARR growth is not the best indicator of long-term success in AI
Venture capitalists continue to pour money into AI companies at a breathtaking pace, some might say it’s ridiculous, Databricks has raised a staggering $ 3.5 billion in funding, including a $ 1 billion Series G in February. Six months later, followed by $ 1.6 billion Series H in August, valued at $ 38 billion. DataRobot recently announced a $ 300 million Series G funding round, bringing its valuation to $ 6.3 billion.
While the private market is crazy about artificial intelligence, the public market is showing signs of more rational behavior: the publicly listed C3.ai lost 70% of its value from its all-time high in December 2020. In early September 2021, the company released the results of the first fiscal quarter, which caused a further disappointment in the share and triggered a renewed price loss of almost 10%.
So what’s going on? What is happening is that private markets funded by venture capitalists generally fail to understand AI. The fact is, AI isn’t difficult to sell, but AI is quite difficult to implement and has value.
In general, the real danger with SaaS is market risk: will customers buy? For this reason, private markets have always been organized around annual recurring sales (ARR) growth, and if you have a rapid ARR growth then customers will clearly want to buy your product and therefore your product has to be good.
But that’s not how the AI market works. In the AI market, many customers are ready to buy because they are desperate for a solution to their pressing business problems and the promise of AI is so big that venture capitalists continue to put money into companies like Databricks and DataRobot, leading them to absurd valuations without considering billions flowing into these companies to create hundreds of millions of ARRs at best. It’s brute-forcing funding of an already over-hyped market. But the fact remains that these companies have failed to produce results for their customers on a systematic basis.
A Forrester report sheds interesting light on what’s really behind the numbers that some AI companies claim with these huge ratings. Databricks reported that four customers had a positive three-year net ROI of 417%, and DataRobot had four customers that had a return of 514% over three years. The problem is, of the hundreds of clients these companies have, some of their best clients must have selected for this analysis, and their returns are still not that impressive. Their best customers are barely doubling their annual return – Hardly an ideal scenario for a transformative technology that should bring in at least ten times your investment.
From the SaaS world, VCs learned to appreciate the Minimum Viable Product (MVP), a first version of a software product with enough features to be usable so that potential customers can provide feedback for future product developments. I hope customers who buy the MVP also buy the full version. Building an MVP has become a standard practice in the SaaS world as it shows VCs that customers would pay money for a product that addressed a specific problem.
3. Successful AI pilots don’t always mean successful real-world outcomes
Rather than focusing on the most important factor when customers get tangible benefits from artificial intelligence, venture capitalists are obsessed with ARR growth. The fastest way to get to ARR expansion is brute-force sales, selling services to cover the gaps because you don’t have the time to build the right product. It’s time to develop the right product. This is why you see so many consulting toolkits disguised as products in the data science and machine learning marketplace.
But you can’t do that with AI. The way AI works in the laboratory is fundamentally different from what it does in nature. You can run an AI pilot based on clean data and find that if you follow AI’s predictions and recommendations, your business will theoretically make $ 100 million, but by the time AI goes into production the data will have changed that Advertising conditions have changed.Your end users may not accept AI recommendations. Instead of making $ 100 million, you can actually lose money because AI leads to bad business decisions.
You can’t extrapolate from an AI pilot in the way that you can with SaaS.
4. Signing up customers for long-term contracts isn’t a good indicator the vendor’s AI works
Venture capitalists like customers to sign long-term contracts with a supplier; They see it as a strong indicator of long-term income and success. But that’s not necessarily the case with AI. The value AI creates is growing so rapidly and potentially so transformative that any vendor who truly believes in their technology won’t try to sell a three-year deal and then negotiate the price.
AI providers that put a lot of effort into locking up customers with long-term contracts fear that their products will not create any added value in the short term. You try to get a three year contract and then we hope that at some point the product will be good enough to finally add value before the extension talks take place. And that often never happens. According to a study by MIT / BCG, only 10% of companies get some benefit from AI projects.
Venture capitalists have been trained that any supplier who signs many long-term contracts must have a better product, while in the world of AI, the opposite is true.
Getting smart about AI
Venture capitalists need to be AI savvy and not rely on their old SaaS playbooks. AI is a rapidly evolving transformative technology, much like the Internet in the 1990s. Venture capitalists have not been obsessed with the profitability or income of internet companies to invest in. They were basically saying, “Let’s see if people get any benefit from the technology.” When people embrace technology and create value from it, they don’t need to worry too much about sales or profitability first. Those who create value will earn money.
Perhaps it is time to transfer that early internet mindset to artificial intelligence and evaluate new technologies based on whether customers are getting value instead of relying on forced ARR numbers. AI is destined to be a game changing technology, just like the internet. As companies draw sustainable value from AI, it will be successful and highly profitable for investors. Smart venture capitalists understand this and will reap the rewards.
