Who are the winners and losers from the AI boom in 2026?

The adoption of AI tools is accelerating rapidly.

Which companies are the winners and which are the losers from the AI revolution?

Who are the winners in the AI boom, who are the losers in the AI boom

by Henry Cobbe CFA, Head of Research, Elston Consulting

The Artificial Intelligence (AI) boom is a “space race” in technology and software development as countries and companies compete to innovate and dominate this new market.

History

Whilst work the early groundwork for language models was developed by IBM in the 1990s, the use of “neural networks” to develop “Large Language Models” started in 2000.  In 2017, Google researches published a landmark paper “Attention Is All You Need” outlining “transformer architecture” for neural networks.  In June 2018, OpenAI published a paper “Improving Language Understanding by Generative Pre-Training.”  OpenAI launched GPT-1 in 2018, a decoder-only model which solves tasks via prompting.   GPT-2 was launched in 2019, and GPT-3 in 2020.  The consumer-facing chatbot ChatGPT was launched in 2022 which massively socialised AI for individuals and businesses.  Since 2023, many LLMs have been trained to process and generate data other than text such as images, audio or video.  These are also called Multimodal Large Language models MLLMs.

With the massive increase in prompts from individuals and businesses, faster and more powerful processing chips are what enable AI to handle millions of queries every moment of the day.  This requires extensive infrastructure to handle rapidly growing demand.

AI as infrastructure

​It is worth viewing AI both as a form of infrastructure as well as a technology.  The infrastructure roll out for the creation of internet technology required fibre optic cables, servers, switches and an overhaul of the telecommunications network.  The infrastructure roll out for the creation of AI technology requires large temperature controlled data centres with server banks full of powerful memory and processing chips to handle the vast number of simultaneous queries.

The rapid adoption of AI

​The adoption of AI has been one of the fastest adoptions of a new technology, more akin to a vertical take-off, than a typical adoption j-curve.  The chart below shows the adoption of ChatGPT.  From launch in November 2022, it gained 1m users in the first 5 days, 100m weekly active users by January 2023, 800m users by October 2025, and over 1bn users expected in 2026.  People are using AI regularly both for work-related and non-work related enquiries, with most workers reporting that AI improves the speed and/or quality of their work and a material time-saver.

Source: https://openai.com/business/guides-and-resources/chatgpt-usage-and-adoption-patterns-at-work/

Key players

​OpenAI is leading the consumer revolution with ChatGPT, but Anthropic and Google are focused more on enterprise applications. 

The evolving use cases for AI

​Almost everyone in the developed world is using AI almost all the time for a deeper type of “ask anything” search.  But this is just the beginning.  The real value (to its winners/adopters) and risk (to its losers/disrupted businesses) is in embedding AI into business processes so that businesses can do more with fewer people.  For firms that could and do successfully adopt AI, the potential productivity and hence profitability gains are substantial.

Who are the winners or losers from the AI boom?

​We see three different types of winner from the AI boom, which vary in nature at different stages of the adoption process.

Stage 1: AI revolution infrastructure.

​For the first stage we see the beneficiaries of the AI revolution being the firms that benefit from the growing and material capital spending on AI.  Examples include chip manufacturers (NVIDIA), and even real estate investment trusts (REITs) to roll out the vast physical data centre capacity.  In this stage the losers will be those that over-invest in infrastructure and fail to achieve a sufficient return on investment.

Stage 2: AI service providers. 

We see the AI service providers that are consumer or business facing being the next potential beneficiaries.  These are currently the tech providers (Microsoft, Meta, Google).  In this space race, it’s not clear who the clear winners and losers will be.  This is why at the start of 2024, these large tech stocks wobbled with the unveiling of Chinese AI platform DeepSeek which seemed to be able to do more with less.  Furthermore today’s tech winners may not be tomorrow’s AI winners: it also depends on whether their vast investment into AI and AI infrastructure brings sufficient revenue rewards. ​

Stage 3: business adoption of AI. 

For firms that can and do successfully adopt AI should see a dramatic increase in productivity and profitability as they are able to maintain or increase their revenues per employee.  The losers are those firms whose proposition is threatened, challenged or entirely replaced by AI.

Taking a diversified, thematic approach

​At this early stage it is hard to identify the winners and losers from the AI infrastructure and service roll out.  For investor’s its worth remembering how product lifecycles within technology can be short and brutal.  Nokia dominated mobile phones, only to eclipsed by the Blackberry, which soon after lost out to the iPhone.  We expect investors to take broader thematic and diversified approach to the AI thee.

The impact on employment

Whilst this shift to AI could create challenges in the jobs market it could be positive for the profitability of companies that successfully integrate AI into their business processes.
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The growth in AI necessarily could replace jobs for people.  The safest jobs are manual ones – electricians, plumbers, builders, maintenance.  The most at risk are graduate entry level services jobs such as entry level accounting, finance and law, where the process-oriented “thoughtful” work can be readily replaced, accelerated or even automated using AI.

Summary

​The AI revolution is here, and as with any period of innovation and disruption this introduces tremendous risk and opportunity for established and new businesses activities alike.  For advisers seeking exposure to potential winners, understanding the inherent exposure of existing traditional funds and consideration of the underlying make up of relevant thematic funds is key.