Investment in AI technology will grow markedly in 2022 as the sector continues to expand, according a new player in the market. Machine learning tech start-up TUBR is operating in an area where new innovations and developments in technology are rife, breakthroughs that will form the foundations of new industries in years to come.
Dash Tabor, CEO and co-founder of TUBR, said: “This is an exciting time to get into the market as people are starting become more comfortable with what AI can do for them. While the word has become a buzz word the true AI market still isn’t as noisy as it will become.”
Her comments come in the wake of a report by Tortoise Intelligence which found that investment in AIcompanies had increased by 115% last year compared to 2020, the largest year-on-year growth in two decades.
Total AI investment reached $77.5 billion in 2021, compared to the previous record of $36 billion in 2020, with Covid-19 contributing to surging interest in AIfrom investors and governments. Investors shouldn’t be deterred by the apparent risk involved in backing nascent AItechnologies, Dash added.
She said: “There is always a risk in investing. Period. If you aren’t comfortable in the space there is an added risk but this shouldn’t keep someone away from exploring,” she said. “Investors don’t need to be deep tech experts to pick a winner. The same principles apply; do you like the team? Do you like the problem? Do you like the product?”
The investment report said interest in AI investment has also been driven by the sudden need for remote working and collaborative spaces forcing business leaders to understand that the need for digitisation is vital.
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It also found that the US retains its leadership in AI, with China in second place and the UK in third, due to home-grown talent and a strong startup scene. The immense amount of research in AI will see the introduction of a raft of new products in medicine, new materials, the environment and many other areas, so investors need to keep a close watch on new developments.
AI will fuel advances in new drug discovery, remedies for climate change, image analysis and more but investors focused on stock market movements may not be paying attention to projects not obviously connected to short term finial performance.
Research and development projects often come up with products that go way beyond the researcher’s original goals and spotting this kind of potential could prove to be very lucrative for investors.
Dash said that, though there are basic principles to learn in understanding the difference between machine learning and AI, those interested in investing will often need to assess between companies that have created AI IP and products that are aspirational.
“If you’re more interested in investing in the technology than the company’s product then be careful of the buzzword effect on the pitch. Never invest off a deck. This can be difficult to validate as many products in this space are not a tangible product, but code that runs in the background but is still very valuable and innovative. Do your homework, as you should with any deal and you’ll find the exciting company that’s worth investment.”
