How can we identify and support promising AI talent?

Over the past decade, investors have set their sights on startups that are building innovative artificial intelligence (AI). The long-run potential of AI is unquestionable, with this next-gen technology promising to tackle some of the world’s biggest challenges: from climate change to global pandemics, the race is on to develop solutions that will improve the quality of life of people all around the world.

Admittedly, recent data from CB Insights reveals that investment in AI startups has dipped somewhat. While globally, companies developing this technology raised over $7.2 billion in Q2 2020, funding has slipped from the previous quarter.

In the throes of a pandemic and global recession, however, this slight drop can be forgiven. AI has been around for over 50 years as a discipline, yet it has only recently entered the public consciousness. Despite this, it has already dominated the investment landscape; relative to other emerging technologies, AI companies were the leading investment category globally in 2019, securing over $23 billion in financing.

That said, the latest figures from CB Insights must serve as an impetus to bolster our efforts and give the best possible support to the most promising companies developing the tech of the future. What’s more, now more than ever we must focus on backing the right businesses—let’s cut through the noise and filter the genuinely innovative AI startups from those trying to use this tag to lure in investors and customers.

Separating Fact from Fiction

There is a tendency for tech businesses to use the tag “AI startup” to secure higher valuations than their counterparts—namely, software companies. But this clumsy misuse of the term risks holding back the entire sector, thereby presenting the first hurdle to effectively nurturing real AI talent.

While there is no comparable data for the US, a 2019 report from MMC Ventures revealed that two-fifths of Europe’s “AI startups” do not actually use any AI programs in their products. This revelation should serve as a red flag for the entire industry.

Conflating terms makes it difficult to distinguish between what is, and what is not, a true AI business. It can not only lead to overspending and poor execution, but it may well signal a business’s downfall when it is outcompeted by those with more clarity and focus.

Vetting companies from the outset will reduce the risk of diverting invaluable resources away from companies that have AI at their core.

Two questions can help determine whether a company is “AI-driven.” Namely: will this company move the AI needle forward? And does it derive its core competitive advantage from the use of AI?

Where will AI Startups go Wrong? 

Having identified the right businesses, the next step is to help them reach their full potential. The strong investment in AI is encouraging, but if done in isolation, it does not offer the right support to the teams who are developing the actual technology.

Early-stage startups will typically bear the highest risks and have the highest failure rates; that is why we cannot overlook the importance of helping founders properly unpack their idea and create a plan of execution.

In the field of deep tech, ambitious young teams will generally possess the drive and technical skills needed to design and create an innovative product. However, even here they may need to source AI tech experts that could help build-out and refine the product beyond the startup’s early idea.

Importantly, a powerful vision and tech expertise are still not enough to guarantee the success of an AI startup; a lack of appropriate mentorship and limited business acumen may stand in the way of their ability to overcome common roadblocks.

For instance, even if startups are able to secure the necessary funding, a common pitfall is a limited understanding of how much money it actually takes to run the business. A workable budget is key to steady growth, and failing to look past the development budget could land deep tech startups in hot water.

Indeed, AI startups will fail for the same reasons other startups do. A recent report identified the most common reasons behind failures, offering insight into the kinds of challenges that fledgling AI companies will face. Topping the list is a lack of market need for the product, which was noted in 42 percent of cases. An error as fundamental as this can be almost impossible to overcome once the gears have been set in motion.

Startups are—and should be—on the lookout for mentors who can guide them through the early stages; who can contribute commercial, financial and legal expertise to help them see their vision through and provide the necessary guidance to overcome the logistical hurdles of growing a business.

How to Nurture AI Talent

Genuine support comes through working very closely with entrepreneurs at a strategic and operational level. After all, the combination of factors that determine success is far beyond the technology itself; the reality is that the best product will not always win. All that really matters is that it is good enough to solve a problem that somebody will be willing to pay to fix.

So, any AI startup seeking to beat their competitors must ensure that they are genuinely solving a market problem.

With little prior experience, it can be difficult to devise a business model that takes into account all the key elements that will ensure this will happen; namely, an economically viable application for the technology, a well-thought out financial model, a strong marketing strategy, and good sales proficiency.

Third-party advisors will be able to fill any knowledge gaps that exist with the team and ensure that all of these factors have all been carefully considered. Most importantly, they will be able to test the market fit and validate the concept to ensure that the core proposition is, in fact, workable.

Incidentally, the aforementioned CB Insights report ranked this as the third most common reason why fledgling companies fail: 23 percent of startup failures were attributed to not having a diverse team with different skill sets. This highlights the importance of surrounding founders with a strong team of trusted advisors that can help AI startups execute their ideas and navigate the early-stages phase.

Whether it is by creating growth programs that set companies on the path to a commercially scalable product or revising the traditional VC model to include more opportunity for mentorship, we must do more than just finance AI startup. We must provide specialized support, help with basic business functions, as well as access to talent, capital and peer networks.

Funding the technology is only a fraction of the equation, and only through a comprehensive and multi-pronged approach, will we be able to assist founders that are making a positive and tangible impact on the world around us.



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