What AI adopters in the UK can learn from the dot-com bubble
It’s been an incredible 18 months for the AI sector, dominating discussion in the tech industry during 2023 and 2024 across the globe.
According to GlobalData, the worldwide AI market is projected to be worth nearly £300 billion in 2030, up from £63.5 billion in 2022, which represents an annual growth rate of an impressive 21.4%.
AI is clearly the next big thing in our industry, and the only similar moment in the tech sector I can compare it to is the dot-com bubble of the late-1990s and early 2000s.
It was a crazy time, with huge investments at values you couldn’t comprehend because there was no business model to monetise these companies.
People were investing significant money to avoid missing out, and that created a hype, but businesses would struggle for revenue, then disappear or be sold at a significant discount compared with the investment they raised when the money ran out. Lastminute.com is probably one of the most memorable examples of this.
Despite some similarities between these two seminal moments for our sector, I believe investors are now much wiser, more savvy and much more selective about where to place their money.
There’s a much greater focus on getting a return on your investment, as well as the quality of the business model you are investing in. There’s also arguably less risk because investors are building on an infrastructure that’s been around for over 25 years, although some are still holding back because the pace of change is so swift in AI they are concerned they could commit too early to the wrong company or product.
Businesses are using AI to drive real benefits in terms of either revenue gains or productivity, with companies in two real camps when it comes to adoption – the larger businesses and the smaller SMEs.
The issue for smaller SMEs is they perhaps don’t have the in-house expertise to take advantage of the AI capabilities that exist. Interestingly, these organisations are likely to take more risks and have less governance to overcome, but resource might be the real challenge.
Larger companies have the money to secure that resource but perhaps have a much different approach to governance and risk, so you’ll see them take a much more incremental approach to adoption of AI.
This could create an unusual situation where the technology is moving really fast but adoption is incrementally slower at larger businesses because of the concerns around risk and governance.
Another big question is: how will the growth of AI impact jobs? A report by investment bank Goldman Sachs in March last year suggested that AI could replace the equivalent of 300 million full-time jobs across the globe.
Over the next 3-5 years I believe this technology focus will be on augmenting individuals, rather than replacing them, but there’s no doubt that using AI can significantly reduce the cost base of a company and sadly certain roles will become redundant over time.
It’s important that companies don’t just adopt AI if it does not provide any competitive advantage. Educate yourself on where the technology is and what it can do for you before making a big judgement call. Another challenge is that the technology is changing so quickly that it’s hard for companies to know which AI it should support.
For many SMEs an initial approach could be to implement AI in a business area that can be controlled and then assess how this impacts the business and evolve from there. Consider what problems you want to solve, or what opportunities you have and assess how AI could help in that area to support growth or reduce costs.
It’s going to be a fascinating time for the AI sector in the UK, and one that many will be watching on with interest in the coming years.