We believe that Artificial Intelligence (AI) could have over the long-term a positive impact on productivity and GDP growth. However, the impact will not be linear across sectors, especially in the early phases. Those companies that are already investing heavily in AI technologies are the most likely to see benefits to revenues and/or profitability, but disappointments will happen given increased and new competitive pressure as well as the emergence of questionable business cases in light of the involved costs.
With rising expectations around AI, the tech sector and US mega caps have outperformed strongly in recent times, leading to higher market concentration. In particular, the US tech companies have risen by 300% since the start of 2019, whereas non-tech stocks gained just 79%. This poorly discriminated performance has been driven by robust earnings growth in the US Mega Cap, a supportive economic backdrop and the launch of ChatGPT 3.5 (2023) that led to a cycle of investment in AI technologies. Investors may need to consider a potential reset of the tech sector’s valuation levels, and determine the companies which are likely to be the future winners and losers across the market.
To help identify such companies, we use a framework which categorises them into four AI types: tech providers, tech enablers, deployers and disruptors. The AI tech providers (e.g. semiconductor companies) are the early winners that are well-positioned to exploit the robust AI demand, while the AI tech enablers (e.g. hyperscalers/cloud providers, data centres) are heavy investors in Al, purchasing the majority of the leading-edge AI graphics processing units (GPUs). The AI deployers are those businesses that are already leveraging AI to transform their businesses whereas the AI disruptors are new entrants that will disrupt business processes by using AI technologies to achieve greater scalability.
You can now read the full whitepaper at the link below
