Trends 2040

In this scenario, AI becomes a basic utility, like electricity or the internet. You no longer use it as a separate application; it sits in the machine, the software, the building and the phone. The signal today: assistants already work inside cars and inside the programs employees open every day. Quantum computers calculate according to the laws of quantum mechanics and could become a major accelerator for certain problems, such as simulating molecules. When they will be reliable enough for everyday use is still uncertain. In that scenario, by 2040 almost everything people work with helps them think and make decisions, from the forklift to the office building.

For a long time a robot did exactly what it was programmed to do, movement by movement. AI changes that. Such a robot is given an instruction in plain language, such as "tidy this shelf", and works out the steps itself. It learns by copying people and by practising a task thousands of times in a simulation. Driverless cars already carry passengers in a number of cities. Humanoid robots are learning to work in spaces built for people, with stairs, doors and handles, and are being tested in factories and warehouses. In the 2040 scenario, machines share what they learn: a robot builds on what similar robots elsewhere have practised. How fast that goes depends on cost and reliability.

Sensors and cameras are the feelers of the digital world. They measure temperature, vibration, movement and congestion, and keep getting smaller and more affordable. AI recognises patterns in those measurements and so sees in time that a pump is starting to falter or that a place is getting crowded. Grid operators and factories already work with this. In the 2040 scenario, sensors and cameras measure more and more of the world, and AI sees at a glance how a factory, a port or an entire supply chain is doing. Data becomes a raw material: who owns it and is willing to share it helps decide how far such a chain can go.

Biotechnology uses living cells and their DNA to make or repair something. With the gene-editing technique CRISPR, researchers change a small stretch of DNA in a targeted way. Regulators such as the FDA have approved the first CRISPR treatment, for an inherited blood disorder. In some forms of blood cancer, doctors modify the patient's own immune cells so that they attack the cancer. AI speeds up this research: it predicts the shape of proteins, the building blocks of the body, and works out which substances could act on them. Researchers then test the best candidates in the laboratory. In the 2040 scenario, such applications help more people stay healthy for longer. How fast that happens depends on research, price and what society finds ethically acceptable.

The energy system of 2040 draws on many sources. Solar and wind depend on weather; batteries balance fluctuations. New drilling techniques make geothermal energy accessible in more places. Smart grids manage these flows: they take measurements throughout the network, switch automatically and shift consumption to times when supply is plentiful. AI forecasts solar and wind output and tomorrow's demand. Demand is rising, with the International Energy Agency expecting sharp growth in data centres' electricity use. Technology companies are already signing contracts for small modular nuclear reactors intended to power data centres from the 2030s. Batteries, grids and turbines need metals such as lithium and copper. AI is helping search for materials that could replace them.

Technology has become geopolitical. The most advanced chips come from a few manufacturers; the largest AI models come from a handful of providers. Governments restrict chip exports and want their own data centres, models and access to raw materials. This ambition is known as digital sovereignty. The European Commission invests in AI factories, and the EU AI Act sets rules for AI development and use. Other power blocs make different choices. In the 2040 scenario, several technology blocs coexist, each with its own chips, models and rules. Organisations operating across borders move between these different worlds.

In many countries the number of older people is growing and the number of people in work is falling. The United Nations and the OECD foresee further ageing; how many people will be working also depends on participation and policy. Healthcare, engineering, education, logistics and government compete for the same workers. Automation becomes less about saving money and more about getting the work done. AI handles administration, robots lift and drive, and people stay in the workforce longer and increasingly work part-time. Customers change too: older populations need different products and services. In this 2040 scenario, an organisation's capacity depends more on how people, AI and robots work together than on how many applicants it attracts.

Many big changes happen where forces meet. AI that calculates on a computer which substance could work as a medicine or material, and robotic laboratories that test day and night, could in this scenario greatly speed up the search for new medicines and materials. In the 2040 scenario, sensors, AI and care robots make it possible for many more older people to live safely at home. A smart grid that keeps itself in balance lets solar, wind, geothermal and nuclear power work together. And machines with a brain take over the heavy and repetitive work, giving people more time for what people do well: judging, caring, designing. Nobody knows which combination will break through first.