Faster drug trials and better movies: how AI is transforming businesses | Artificial Intelligence (AI)

Keir Starmer this week announced a 50-point plan aimed at giving the UK world-leading status in artificial intelligence and growing the economy by as much as £47bn. per year over a decade.

The multi-billion pound investment, which seeks to create a 20-fold increase in the amount of AI computing power under public control by 2030, has been pitched as a game changer for businesses and public organisations.

Reaction to the announcement has been mixed, as it is far from clear that the much-hyped potential of AI will result in the level of economic benefit forecast. Many are concerned that the technology could lead to massive cuts, while others fear a destruction of the value and growth of the creative industries after learning from proposals to make it easier for AI companies to mine artistic works into data, at no cost .

Despite such concerns, for many in business, the AI ​​revolution is already here, transforming their industries. So how are they implementing the technology to improve productivity, and where do they hope it can deliver further gains in the future?

Aviation

Airlines are increasingly turning to artificial intelligence for the complex logistics of managing large fleets and thousands of crew members in unpredictable skies. AI is used across Ryanair’s operations to optimize revenue, schedules and “tail allocation” or select the best aircraft for each flight; BA also uses it at Heathrow to help select gates according to the number of transfer passengers on an inbound flight.

EasyJet said it had embedded artificial intelligence in its new Luton control room, and its predictive technology now refines inventory levels on planes and redesigns maintenance regimes to prevent failures. Meanwhile, the budget carrier’s Jetstream tool helps with the brain-wrenching task of quickly redeploying crews and aircraft with maximum efficiency and minimum disruption when problems arise. Gwyn Topham

Energy

One concern raised over Starmer’s AI expansion plan is that the hugely energy-hungry data centers required to run their programs could exceed the UK’s grid capacity. Others, however, argue that the technology could actually accelerate the clean energy revolution by solving the problem of how to power future energy systems.

The power grid must increasingly adapt to real-time fluctuations from thousands of renewable energy sources and accommodate new technologies such as electric car batteries that can draw power from the grid but also release it back when needed.

Google was one of the early adopters of a digital energy approach. Its AI subsidiary DeepMind developed a neural network in 2019 to increase the accuracy of power output forecasts for its renewable energy fleet. By forecasting production and demand with greater accuracy, it has been able to balance its consumption and even sell some electricity back to the grid. Google says this has increased the economic value of its wind power by 20%.

Meanwhile, in the UK, energy supplier Octopus Energy is using the advanced data and machine learning capabilities of its Kraken operating system to give its customers access to electricity when it is cheaper and greener through its time-of-use tariffs. Using electricity in the off-season means it can often be 40% cheaper, reducing the need for investment in new fossil fuels or expensive grid expansion projects. Jillian Ambrose

Starmer’s plan proposes revising UK law to allow AI models to scrape intellectual property from the internet for training, provided they allow copyright holders to opt out of the process. The creative industries have raised serious concerns that this would threaten the livelihoods of professionals across the sector.

But elsewhere in the sector, media companies are signing licensing deals with the big AI developers or embracing the technology to get the most out of their own – and their clients’ – content.

Advertising giant WPP invests £250 million a year in data and AI and has run a number of marketing campaigns using the technology, including creating a “Jen AI” that allowed users to invite friends on a Virgin Voyages cruise with a personalized message from pop. star and actress Jennifer Lopez. And for Euro 2024, Mars’ brand Snickers used an AI impersonation of football manager José Mourinho to allow users to send a customized message to friends.

In the music industry, Sony has worked with Pink Floyd’s David Gilmour to allow fans to remix the music and artwork of a classic album, while Warner Music used AI to enable country music star Randy Travis, who lost his ability to sing after a stroke, to release new albums.

And in movies, machine learning and “directed” artificial intelligence have led to improvements in the special effects industry, helping studios decide who to market their movies to and even trying to predict the commercial success of a movie based on a script. Mark Sweney

Medicines

Large pharmaceutical manufacturers and small AI-specialized biotech companies are using the technology to speed up drug development and reduce costs and failure rates. Drugs usually take at least a decade to develop, and 90% of drugs that go into clinical trials on volunteers fail.

AI helps them design smarter clinical trials by selecting patients most likely to respond to treatment. A recent analysis by the Boston Consulting Group found that since 2015, 75 AI-generated drugs have entered clinical trials, of which 67 were still being tested last year.

A treatment for a fatal lung disease called idiopathic pulmonary fibrosis has been hailed as the world’s first fully AI-generated drug in late-stage trials. Developed by the Massachusetts-based company Insilico Medicineit used AI to generate 30,000 new small molecules and whittled this down to the six most promising drugs and then a lead candidate. Meanwhile, AstraZeneca, the UK’s largest drugmaker, said more than 85% of its small molecule drug pipeline is “AI-assisted”.

Ministers are considering opening up the NHS database to private companies so they can use anonymised patient data to develop new medicines and diagnostic tools. However, privacy advocates oppose such a move, as even anonymized data can be manipulated to identify a patient. Julia Kollewe

Retail trade

Retailers haven’t been able to stop talking about the rise of artificial intelligence in their work for the past six months as they hunt for ways to become more efficient amid rising labor costs. Sainsbury’s, for example, is using AI-enabled forecasting tools to help it put the right amount of products on the shelves in different stores as part of a £1bn cost-cutting initiative. Marks & Spencer is using artificial intelligence to write online product descriptions and help advise customers on outfit choices based on their body shape and style preferences, as part of efforts to boost online sales.

Tesco chief executive Ken Murphy said AI was already widely used to make purchasing decisions, adding that the technology was at a level where interactions with customers would be “really powered and driven by AI in almost every facet of the business “. He suggested it could be used to analyze customers’ loyalty card data and give them “inspiration and ideas relevant to them and their family”, including how to save money or look after their health by buying – or not overbuying – certain items . Sarah Butler

Call centers

Productivity and service levels could be transformed in the public sector by AI-enhanced efficiencies that automate the simplest tasks for call handlers, argues Adolfo HernandezCEO of outsourcing group Capita.

For example, you save by pulling up previous interactions with customers on old ground. Programs can merge council services in the background so that the planning application department and building services are aligned. Or by listening in the background to transcribe and summarize calls, reducing time spent writing notes.

Capita has introduced its “Agent Suite” product with two customers. Early indications, it says thereshowing a 20% reduction in average call handling time, a 25% reduction in post-call management, and a 15-30% increase in calls resolved on first interaction. Nils Pratley