Nine in ten retailers globally are planning to raise their spending on artificial intelligence (AI) to optimise their e-commerce operations over the next 12 to 24 months, with online delivery execution a key area of focus.
That’s a key statistic from research released on 4 February 2026, which suggests retailers view AI as a key lever to drive growth and succeed in a competitive market. A total of 38% of European retailers identify speed, tracking and proactive communication around the delivery process as areas where AI can deliver the greatest impact.
The report by Retail Economics, on behalf of delivery platform Metapack, which was launched to coincide with the tech company’s annual The Delivery Conference (TDC) in London, shows retailers with a turnover of £500m or more are more likely to point to skills gaps and the complexity of integrating AI with legacy systems (54%) as a challenge to AI adoption.
Smaller retailers, with a turnover of under £100m, cite high development costs (35%) and data security or compliance concerns as a notable barrier to using AI.
Alongside the 400-strong retailer study, the Ecommerce delivery benchmark report 2026 also surveyed 8,000 consumers about their use of AI.
It found that globally, 78% of shoppers used AI tools such as ChatGPT in the past year, rising to 93% among those under the age of 35. Some 30% of adults are open to AI acting as a personal shopping agent, recommending products, checking delivery and returns options, and even making certain purchases on their behalf once preferences are set.
By 2030, 48% of shoppers expect AI to act as a helpful assistant across the shopping journey, while a further quarter of shoppers anticipate it evolving into a trusted co-shopper that automates some decisions. Retailers such as JD Sports and Etsy, in the US, have developed tech integrations and started allowing shoppers to transact directly through AI platforms, in recognition of the rising traffic volumes on these channels.
Indeed, the delivery benchmark report argued that AI-based platforms are emerging as a major retail channel, generating 50.2 million monthly shopping-intent visits in the UK, which ranks it alongside the biggest e-commerce sites.
Which AI shopper persona are you?
Retailers and brands are always keen to improve the digital customer experience (CX), and senior leaders in the industry regularly talk up the importance of placing the shopper at the heart of strategy.
For example, New Look CEO Helen Connolly said of the appointment of retail director Mark Matthews in December 2025 that he brings “a customer-first mindset”. US department store chain Bloomingdale’s hired Kirsten Miller as chief technology officer in January, and the new recruit notice posted online said she was joining a team with a “customer first, always” mentality.
If retailers adopting this approach are true to their word, they’re going to need to get to grips with what an AI-enabled customer means for their business.
The Ecommerce delivery benchmarkreport identifies four distinct AI-driven shopper personas, reflecting the various ways consumers are adopting AI when shopping.
It said there are “AI delegators” (17% of shoppers), who are affluent, time-poor shoppers, more often than not millennials, who are comfortable letting AI take the lead for product discovery, comparison and purchasing, to save time and effort.
On the flip side, there are “AI sceptics” (23%), who are cost-focused shoppers who make limited use of this new technology, prioritise low delivery prices over speed or innovation, and stick with what is familiar to them in the shopping process.
The most common types of new-age shoppers, though, are either “AI collaborators” or “AI selectors”. Each representing 30% of today’s shoppers, the former is a young, digitally savvy consumer who uses AI frequently as a trusted co-shopper while retaining final control themselves, while the latter is typically older and uses AI occasionally for information or reassurance.
The report notes that retailers looking to AI to identify speed, tracking and proactive communication around the delivery process will likely have the most success in appealing to the delegator persona.
What is the retail community saying about AI?
Retailers and companies operating in the online delivery ecosystem took to the stage on 3 February 2026 for this year’s TDC, where AI was a hot topic. They shared how it is being deployed in multiple ways to support their efforts in improving service levels and efficiency.
The Cheeky Panda’s co-founder, Chris Forbes, told a tale of Covid times when big orders for his business’s core loo roll product came in and initial excitement at the “big deals” was tempered because the company inadvertently ended up taking stock away from existing customers. He spoke about the importance of retailers ensuring “continuous delivery”, especially for organisations in the early stages of their growth journeys.
“In delivery and fulfilment, you have to ringfence your stockholding so you don’t get too excited when you get big deals – it’s all about continuous delivery.
“Nowadays, we use AI in our stock management systems to ringfence it, so we don’t actually need to over-manage it and over-analyse it on a regular basis. We’ve got controls and limits set up, so it makes it a lot easier.”
Kristian Tottermar, logistics network strategic lead at H&M, didn’t talk about AI specifically, but underlined the importance of holistic supply chain investment to ensure successful delivery.
“We don’t talk about investing purely for delivery,” he commented. “If you optimise your supply chain – [for example, by making it] more transparent or optimising the end-to-end flow – that will enable you to have better availability and delivery.”
Tobias Buxhoidt, founder and CEO of parcelLab, said: “When I think about what AI will do – yes, it will make all of our lives easier – the first thing that will happen is it will dramatically change how customer acquisition works.”
I don’t see a world where AI isn’t taking over a large share of the traditional [customer] acquisition channels we know today Tobias Buxhoidt, parcelLab
Reflecting on the growing number of people using AI to search for products or gain information about brands, as referenced in the benchmark research, he remarked: “This becomes crazily convenient for the customers. It’s not the same for all brands and markets, but this will become a major customer acquisition channel, and it’ll be undifferentiated for brands as they cannot control the acquisition anymore.”
Buxhoidt added that the focus for retailers needs to be on retention and putting services and tactics in place that keep customers coming back, “because the acquisition is going to get so damn hard”.
“I don’t see a world where AI isn’t taking over a large share of the traditional acquisition channels we know today,” he warned.
Buxhoidt argued that when it comes to retail returns management online, AI could help interactions between business and customer become more conversational. Early-stage chatbots have not delivered what consumers need, but the tech entrepreneur said AI-powered online conversational commerce has the potential to help tailor conversations to the moment rather than simply follow a pre-designated path.
Aura Hita Losa, lead on conversational AI at Swiss trainer brand On, said that if AI is used in this area, it needs to solve problems, not simply present further information and content to the customer.
“Imagine you put your founder on the phone to deliver [the customer exchange]. He or she would always have the right thing to say or to do,” she noted. “When customers reach out, they don’t want information – they want a solution, and they want you to act.”
Losa suggested retailers and brands need to use the latest technology, analytics and insights software to become better at remembering customers’ previous problems, so that when they present themselves at customer service – with a complaint or a query, for example – they can be better served.
One could argue that real-life humans can provide the necessary services to deal with these exchanges, but retailers and brands are increasingly looking to technology and AI to take on much of this workload.
Indeed, the conference had earlier kicked off with a debate about AI, human value and retail, between TV celebrity and retail creative Mary Portas and Google DeepMind product management developer Arka Dhar, hosted by Al Ko, CEO of tech company Auctane.
Portas argued that AI needs to be used to make people “more human”, suggesting this as an area where it can have a powerful impact.
Dhar said AI will likely have a strong role to play in helping frontline staff gather comprehensive product information, with AI agents providing some of the prompt questions that will help store staff become more adept at problem-solving for their customers.
He suggested there are still major hurdles to overcome in getting AI to think and act like a particular brand and in getting data management to a level, internally, that will optimise use of the technology.
Richard Lim, CEO of Retail Economics, says: “AI is reshaping retail strategy, not just the CX. Retailers clearly see the potential across conversion, delivery and CX, and consumers are increasingly comfortable with AI playing a role in how they shop. In 2026, the focus shifts from experimentation to execution, where success will be shaped by how effectively retailers can embed AI into their data, systems and everyday operations.”
The Ember Smart Mug 2 is niche, but it has a loyal following. Even though we think there are better mug warmers on the market, Ember is like Apple AirPods or Kleenex. People want what they want. Right now, for Mother’s Day, the Ember Smart Mug 2 is on sale for just under $100, a 30 percent discount and a match of the very best price we’ve tracked. You can save at Amazon, Best Buy, and the manufacturer’s website.
This smart mug is probably overkill. It has a smartphone app that notifies you when your coffee reaches the ideal temperature, and its onboard light also provides a visual indicator that your brew is ready. It intelligently adjusts power usage to keep your drink warm when you’re nearby, and turns off when you’re not around. The self-heating mug is on sale in a few variations—10 or 14 ounces, in blue, white, black, and purple.
The mug offers up to 80 minutes of powered heating time, or you can pop it on the included charging coaster to keep the battery going all day. And you don’t need the smartphone app unless you want to precisely dictate your coffee temperature—the mug defaults to 135 degrees Fahrenheit without your specific input.
Our main gripe is that this proprietary warming system is not dishwasher safe. You need to hand-wash each component, and ensure you do so carefully, because the items are not cheap to replace. But if Mom has been putzing around the house drinking perpetually microwaved coffee, perhaps an upgrade is in order. We have additional recommendations in our guide to the Best Coffee Warmers. You may also want to check our related stories on the Best Espresso Machines, Best Coffee Machines, and Best Pod Coffee Makers.
Google DeepMind’s AlphaFold has already revolutionized scientists’ understanding of proteins. Now, the ability of the platform to design safe and effective drugs is about to be put to the test.
Isomorphic Labs, the UK-based biotech spinoff of Google DeepMind, will soon begin human trials of drugs designed by its Nobel Prize–winning AI technology. “We’re gearing up to go into the clinic,” Isomorphic Labs president Max Jaderberg said on April 16 at WIRED Health in London. “It’s going to be a very exciting moment as we go into clinical trials and start seeing the efficacy of these molecules.”
Jaderberg did not elaborate on the timeline, but it’s later than the company had planned to initiate human studies. Last year, CEO Demis Hassabis said it would have AI-designed drugs in clinical trials by the end of 2025.
Isomorphic Labs was founded in 2021 as a spinoff from Alphabet’s AI research subsidiary, Google DeepMind. The company uses DeepMind’s AlphaFold, a groundbreaking AI platform that predicts protein structures, for drug discovery.
Built from 20 different amino acids, proteins are essential for all living organisms. Long strings of amino acids link together and fold up to make a protein’s three-dimensional structure, which dictates the protein’s function. Researchers had tried to predict protein structures since the 1970s, but this was a painstaking process given the astronomically high number of possible shapes a protein chain can take.
That changed in 2020, when DeepMind’s Hassabis and John Jumper presented stunning results from AlphaFold 2, which uses deep-learning techniques. A year later, the company released an open-source version of AlphaFold available to anyone.
In 2024, DeepMind and Isomorphic Labs released AlphaFold 3, which advanced scientists’ understanding of proteins even further. It moved beyond modeling proteins in isolation to predicting other important molecules, such as DNA and RNA, and their interactions with proteins.
“This is exactly what you need for drug discovery: You need to see how a small molecule is going to bind to a drug, how strongly, and also what else it might bind to,” Hassabis told WIRED at the time.
Since its release, the AlphaFold platform has been able to predict the structure of virtually all the 200 million proteins known to researchers and has been used by more than 2 million people from 190 countries. The breakthrough earned Hassabis and Jumper the Nobel Prize for chemistry in 2024, with the Nobel committee noting that AlphaFold has enabled a number of scientific applications, including a better understanding of antibiotic resistance and the creation of images of enzymes that can decompose plastic.
Earlier this year, Isomorphic Labs announced an even more powerful tool, what it calls IsoDDE, its proprietary drug-design engine. In a technical paper, the company touts that the platform more than doubles the accuracy of AlphaFold 3.
The startup has formed partnerships with Eli Lilly and Novartis to work together on AI drug discovery and is also advancing its own “broad and exciting pipeline of new medicines” in oncology and immunology, Jaderberg said.
“The exciting thing about the molecules that we’re designing is because we have so much more of an understanding about how these molecules work, we’ve engineered them to be very, very potent,” Jaderberg told the audience at WIRED Health. “You can take them at a much lower dose, and they’ll have lower side effects, off target effects.”
Last year, Isomorphic appointed a chief medical officer and announced it had raised $600 million in its first funding round to gear up for clinical trials. Meanwhile, the company has been building a clinical development team. Its mission is to “solve all disease.”
“It’s a crazy mission,” Jaderberg said. “But we really mean it. We say it with a straight face, because we believe this should be possible.”
Security leaders should be turning offensive AI cyber tools on their own systems before threat actors do, exploiting the innate defenders’ advantage to attain the high ground and increase their chances of withstanding a cyber attack.
So says Yinon Costica, co-founder of Google-owned Wiz, who, speaking at Google Cloud Next in Las Vegas, argued that defenders can win against attackers by using AI to exploit an advantage that may not appear obvious at first glance, that of context.
“The same AI model can obviously produce very different results based on the context that we feed into it,” said Costica. “Now, attackers hopefully have much less context about us while as defenders we do have a lot of context about our environments that we can share with the model.
“If, as defenders, we take the first movers’ advantage and we use the AI against ourselves, with the context we have, we actually stand a chance to win…. But we need to act fast,” he said.
“We need to start using AI against ourselves as much as possible, whether it’s to scan attack surfaces, scan code, scan anything, in order to be the first one to see the results and not to wait for the bad guys to do it before us.”
As speed becomes ever more of the essence in cyber security, Costica conceded that this would be a challenge for defenders – but noted that the tools to do this are rapidly becoming available. To try to help, Wiz unveiled three new AI agents at Google Cloud Next – red, green and blue – which are named for the human cyber teams they are designed to help.
“What agents allow us to do is really to get to the next level of acceleration [and] automation of security work,” said Costica.
The red agent is designed to assist red team penetration testing work by probing deep into its owners’ IT estate, identifying potential exposures, such as application programming interfaces (APIs), end-of-life edge networking kit or operational technology (OT) assets, and runs penetration tests on them. The green agent follows on by automating the triage process, something that can take ages for humans. Finally, the blue agent acts as a detective, doing the investigative work that can also be a lengthy process for human teams.
“These three agents together form a layer that is autonomous and automated. Its not revolutionary in that it aligns closely to how security teams have been working for many years, but now it allows each team to automate their workflows,” said Costica.
“It’s like living in the future in the eyes of security teams because it means that from the moment they find a risk, they can automate the process to find who owns it and deliver the code fix to complete and redeploy to production.”
A little over a month on from the closure of the $32bn acquisition of Wiz – Google’s largest purchase to date – the two organisations reaffirmed their commitment to providing a unified security platform, retaining Wiz’s brand, that will enhance the speed with which customers detect, prevent and respond to threats, especially emerging ones created using AI.
They duo also claim their combined capability will accelerate adoption of multicloud security and spur more confidence in innovation around cloud and AI. Wiz’s products are also to continue to be made available across other platforms, including Amazon Web Services (AWS), Microsoft Azure and Oracle Cloud. It also announced support for Databricks and agent studios like AWS Agentcore, Microsoft Azure Copilot Studio, and Salesforce Agentforce, as well as Gemini Enterprise Agent Platform of course, and continues to support security ecosystems with integrations to the outer layer of the cloud, including Google Cloud Apigee, Cloudflare AI Security for Apps, and the Vercel platform.
Behind the scenes, Wiz has also updated how it integrates security detections from Wiz Defend with Google Security Operations and Mandiant Threat Defence to make life easier for human analysts.
And it announced new capabilities to secure the AI-native deployment cycle. These include scanning vibe coded applications for issues; AI-generated code scanning and vulnerability remediation; agent-based remediation allowing teams to automate remediation workflows; and an AI bill of materials (AI-BOM) to keep on top of the use of shadow AI for coding.
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