Sign up for our newsletter and get the latest big data news and analysis.

How Can We Best Identify and Nurture Promising AI Startups?

In this special guest feature, Salvatore Minetti, CEO, Fountech.Ventures, outlines a number of important points for how we ought to help promising early-stage startups build towards commercial success. Foundtech.Ventures acts as venture builder and investor for deep tech and AI startups. With a presence in Austin, Texas, US, and London, UK, the company supports startups through the stages of ideation, development, commercialization and funding.

Artificial intelligence (AI) promises to tackle some of the biggest issues humanity is facing at present; from the coronavirus pandemic to climate change, this technology can offer us the tools we need to solve these generation-defining challenges.

Indeed, AI has a starring role to play in the future of technological innovation – and, as a result, it should come as no surprise that it continues to dominate the investment landscape. Relative to other emerging technologies, AI companies were the leading investment category globally in 2019, securing over $23 billion in financing last year according to Tech Nation.

However, investment alone is not enough, and solving key societal problems will only happen if we properly support and nurture the innovative AI startups who are developing the actual technology. The problem is not the shortage of startups, but rather the shortage of scale-ups; the hype surrounding AI means there are plenty of entrepreneurs starting new AI ventures, but there are few companies that survive and scale.

Below I will outline how we ought to help promising early-stage startups build towards commercial success.

Identifying true AI potential

The first hurdle is to identify startups that genuinely have AI at their core; rather than software companies in disguise.

The clumsy (mis)use of the term AI risks holding back the entire sector, though this is more common in Europe than 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 has made it difficult to distinguish between what is, and what is not, and AI startup, with many latching onto the term in the hopes of securing higher valuations than their counterparts. Yet, conflating the meaning of a product or service can not only lead to overspending and poor execution, but also a business’ downfall when it is outcompeted by those with more clarity and focus.

A company might, for instance, utilize artificial intelligence to automate functions like finding and securing promising leads for sales teams. However, if it does not then employ the technology to make better sense of the data and extract value from the information – in an effort to continuously improve the quality and efficiency of its lead generation capabilities – then it is unlikely that AI is the lifeblood of a company or initiative.  

To truly progress the field of AI, we must pinpoint those businesses that will push the frontiers of this technology. By extension, it is therefore important to be clear about what we mean when we say an organization is “AI-driven”. To cut through the noise and power AI-driven solutions to real world problems, we need to ask: will this company move the AI needle forward? Does it derive its core competitive advantage from the use of AI?

Nurturing AI talent

Identifying the right businesses is the first step in the process. True AI startups are still subject to vulnerabilities, however, which often includes a lack of appropriate mentorship and limited business nous.

That is why investment alone is not enough. While it is important to provide businesses with the capital they need to develop their technology and scale, genuine support comes through working very closely with the team at a strategic and operational level.

After all, the startups who promise to break ground in this field might lack the necessary experience to oversee the logistical hurdles of growing a business. Founders will be on the lookout for experienced teams who can help them in terms of planning across all key elements of the business; this ranges from locating AI tech experts who can help build-out and refine the product beyond the startup’s early ideas, to securing C-Suite team members to carry out the vision, as well as creating the financial model.

A powerful vision and tech expertise are not enough to guarantee the success of an AI startup. Tech entrepreneurs need to have good strategic capabilities to overcome the operational challenges of running a business – an element that will often require third-party input. Effectively fostering innovation involves providing technical and commercial skills, as well as experience, to small young teams who may not have it.

Long-term investment like this, which goes beyond just financial investment, will prevent startups from running into common roadblocks.

One of the most common reasons that AI startups fail is that there is no real market need for the product: a pattern that is evident across all sectors, and not just limited to the field of deep tech. In a study by CB Insights, 42% of startup failures could be put down to this factor.

The blight of many ambitious teams is that they build a prototype, and then hope that somebody will find use for it. Mentoring young companies from the outset will pave a clear pathway and help them understand the market fit and potential demand for the product – ensuring their vision has real substance.  

Ongoing support will also minimize the risk of running out of capital. Indeed, many AI startups are either under-funded from the outset or burn more cash than necessary. Working in partnership with mentors who can prove market fit and demand, whilst also ensuring the financial model is well thought out and adhered to, will prove more effective when implementing a long-term growth strategy.

Building the right team

Another challenge that will be familiar to all business leaders is the difficulty of assembling the right team. This is particularly critical in the early stages – and going into business with the wrong team can leave a startup vulnerable to gaps in critical areas. An outside opinion can help founders onboard people with the right skills and experience needed to successfully grow the business.

Incidentally, the aforementioned CB Insights report ranked this as the third most common reason why fledgling companies fail: 23% of startup failures were attributed to not having a diverse team with different skill sets.

Funding is only the first step towards realizing the vision of an AI startup; and yet, we often do not look beyond this. Funnelling investment into AI or deep tech companies will not, if done in isolation, create a thriving ecosystem of AI talent that can transform businesses, societies and governments. Instead, we must offer support at every step along the journey to assist founders that are making a positive and tangible impact on the world around us. Whether it is by creating growth programmes 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 to help young teams navigate the most crucial stages of their business’ journey.

Sign up for the free insideBIGDATA newsletter.

Leave a Comment

*

Resource Links: