Artificial Intelligence (AI) is no longer just a story about excitement, imagination, or headline grabbing technology. It has become a major driver of global equity markets. Reshaping earnings expectations, valuations, and the composition of major indices. For advisers, the key question is not whether AI is “real,” but whether clients understand how much AI exposure they already have and whether that exposure is deliberate.
Why AI has changed the valuation debate
At its simplest, equity valuation is driven by two things:
- the future cash flows investors expect a company to generate, and
- the multiple they are willing to pay for them
AI has affected both. It has led investors to reassess growth prospects of companies able to monetise the technology. At the same time, confidence in the durability and value of those future earnings has increased.
That helps explain why the first phase of the AI trade was led by the largest US technology companies: the so-called Mag 7. These were not speculative start-ups waiting for AI to make them viable. They were already profitable, cash-generative businesses with dominant platforms, deep customer relationships, and the capacity to invest at scale. AI did not create their quality. Instead, it gave investors a new reason to reassess their growth potential.
Before tools such as ChatGPT, AI mattered but still felt abstract for many investors. Once people could interact with a model directly, the market could more easily imagine its potential. Applications have quickly emerged across software, cloud computing, search, advertising, customer service, and productivity. The companies with the data, distribution, infrastructure, and capital to exploit those opportunities naturally attracted attention.
Beneath user-facing applications such as ChatGPT sits a more complex infrastructure story. Large Language Models (LLMs) require vast computing power. They must be trained on enormous datasets and then run each time a user submits a prompt. That created intense demand for graphics processing units, or GPUs, which are well suited to processing many calculations in parallel.
