Business & Technology
UK consumers wary of AI shopping agents & payments
ACI Worldwide has published UK survey findings showing low consumer trust in AI shopping agents and AI-powered payments. The research is based on responses from more than 2,000 UK adults collected by YouGov.
The survey found that 60% of consumers would stop using an AI shopping agent after a single mistake, highlighting how little tolerance users have for errors in purchasing decisions. It also found that 69% do not trust AI even when it follows rules they have set. Only 19% trust AI assistants to make everyday purchasing decisions, compared with 55% who trust a human expert or adviser.
AI shopping agents are tools that can search for products, compare options and complete purchases with a consumer’s permission. The findings suggest many UK consumers are willing to accept AI as a support tool, but draw a clear line at letting it make decisions or handle money without close oversight.
Half of those surveyed said they trust AI to find the best available price, and 43% said they trust it to follow spending limits. Trust fell sharply on more sensitive tasks: only 18% said they trust AI to act in their financial best interests, 17% to keep personal and payment information secure, and 15% to deal with problems when something goes wrong.
The study also suggests lower prices alone may not be enough to change minds. Some 44% of respondents said they would not trust an AI shopping agent regardless of any savings, while one in four said it would need to save them more than 15% before they would trust it.
Control concerns
Resistance increased when the survey tested more autonomous uses of AI. Seven in ten respondents said purchases made without asking would affect their willingness to use an AI shopping agent. Another 61% said linking it to a bank account would have an impact, and 54% said tracking everything they browse online would do the same.
These findings point to a broader concern about losing control over spending and personal data. They also highlight the challenge facing merchants, payment providers and technology groups as they try to move AI tools from helping users discover products to taking a more direct role in checkout and payment.
Trust in institutions was also weak. Nearly six in ten respondents, or 59%, said they would not trust any organisation to manage AI-powered shopping and payments.
Banks were the most trusted option, but only 20% of consumers chose them. Technology companies and retailers each drew support from just 4% of respondents, suggesting that no part of the market starts from a position of strength when asking users to hand over purchasing authority to AI systems.
Who gets blamed
Consumers place responsibility for mistakes mainly on the companies behind the AI tools rather than on retailers or financial providers. A majority of respondents, 54%, said the technology or AI company that built the shopping agent should be accountable for refunds.
By contrast, only 9% said the retailer should be blamed, while 3% pointed to banks or card issuers. That matters because questions around refunds, liability and accountability remain unresolved in many AI-led commerce models.
Adriana Iordan, Head of Merchant and Payments Intelligence at ACI Worldwide, said the results show that control remains central to whether consumers will use such tools. “The findings clearly show that consumers are open to AI helping them shop smarter, but only if they remain firmly in control of both the decision-making and their money,” she said.
She added that the industry will need to respond directly to those concerns if it wants wider use of AI in shopping and payments. “They’re telling us very clearly that they won’t hand control of their finances to an autonomous agent without safeguards. This isn’t a capability gap; it’s a trust and confidence gap. If the industry wants adoption, it must prioritise control over capability: explicit approvals, hard spending limits, protected payment details and clear accountability when things go wrong.”
The figures add to wider questions about how consumers will react as AI tools move closer to financial transactions rather than simply offering recommendations. In this survey, the strongest support was reserved for narrow, clearly defined tasks such as finding the best price, while confidence fell once the same systems were asked to handle money, hold sensitive data or make independent choices.
That leaves banks, merchants and technology groups facing a difficult balance as they test more automated shopping journeys. For now, the clearest message from respondents is that convenience alone will not overcome caution, with 59% saying they would not trust any organisation to manage AI-powered shopping and payments.
Business & Technology
Why the freelance economy might be the smartest tool a tech founder never considers
When people ask how I built a successful tech start up, they expect me to talk about, investors, funding and headhunting. What I actually talk about is a business model based on freelance expertise – a PHP developer I found on Upwork, a designer who showed up at a freelancer meetup, and a sole trader web developer.
I started Echo3 a decade ago with £1,500 and the aim of building a business that gave me the flexibility to travel to the US several times a year to visit my daughter. That constraint forced me to think differently about how to build.
What I found was Edinburgh’s freelance tech community – a group of people with a solution focused mindset, and a way of looking at highly effective modular collaboration.
The standard startup process is typically formulaic – you raise money, you employ staff and build a team. The freelance model inverts this. Instead of building capacity and hoping the work fills it, you bring in expertise precisely when you need it, at the level you need it.
This allows quality to be prioritised, without a cost overhead in the crucial early days.
Over the past decade, Echo3 has been built by a lean network of Edinburgh-based specialists; a backend developer, a UX designer, a growth strategist, a subject matter expert in ergonomics and workplace safety. None of them are on the payroll. All of them have been instrumental.
Edinburgh’s freelance tech scene has been the key to our growth. This is a professional community of people who know each other, refer each other and crucially, are selective with those referrals – as they want to work with people they like and respect.
One introduction led to another. The developer knew the designer. The designer had worked with the strategist. It’s almost like have a team with chemistry built in, before the work even starts.
There’s a broader point here about how we think about startup ecosystems. Scotland has invested meaningfully in the infrastructure around tech founders. The are a number of programmes and funding routes – Techscaler, the RBS Accelerator and university spin-out programmes.
But the informal layer underneath them, where expertise and knowledge are shared, often as people are still learning and growing, rarely gets discussed as a startup resource.
For an early-stage founder, access to a trusted freelance network has the potential to be incredibly valuable. Especially when that network has ideas and expertise that directly impacts growth. Good freelancers push back on bad ideas and are open to putting forward alternative solutions. The relationship is more like a collaboration between professionals than an employer-employee dynamic, and that changes the quality of the work.
Echo3 has now sold over 80,000 health and safety courses. Our clients include NHS Trusts, the Scottish Parliament and Rolls Royce. Seventy percent of our customers are individuals – freelancers, sole traders, people running small businesses who need affordable, accredited training.
It’s not lost on me that the business is, in a sense, a product of the same economy it serves. A business built by freelancers, for freelancers.
Business & Technology
TG Jones at risk of collapse due to £8 million shortfall
TG Jones, formerly known as WH Smith, could face insolvency without a rescue deal, according to a High Court hearing held on Monday (June 29).
The company is seeking approval for a restructuring plan that would unlock a further £15 million loan from its owners, Modella Capital, who already loaned £10 million in April.
TG Jones at risk of collapse due to £8 million shortfall
Tom Smith KC, representing TG Jones, said: “The business is highly distressed after suffering long-term sales decline.”
He told the court that without support, the company would face an £8 million shortfall this week after paying tax, rent, suppliers, and payroll.
He added: “As is well known, the UK retail sector has faced serious trading difficulties in recent years.
“The problems facing the sector have their roots in macroeconomic factors such as high inflation, the shift to online shopping, reduced consumer spending, higher labour costs and increased taxes.”
TG Jones, which employs 4,700 staff across 450 stores, rebranded last year after being acquired by Modella.
WH Smith retained its travel-focused outlets in airports and train stations.
If the restructuring plan is approved, around 150 shops are expected to close.
Mr Smith said: “That will assist in ensuring the future of the group.”
Landlords will have the choice to terminate leases rather than accept reduced rents under the proposed plan.
Ben Shaw KC, representing landlords, said they are not opposed to the restructuring following negotiations over deferred rent payments in the plan’s first year.
A decision from Mr Justice Hildyard is expected on Wednesday (July 1).
UK companies that have closed or entered administration/liquidation in 2026
It has been a tough year for the UK high street, with several retailers entering administration and others announcing widespread store closures.
Major high street brands LK Bennett and Claire’s both closed all their stores in April, having previously fallen into administration.
UK fashion retailers Leading Labels and Quiz have also closed down after falling into liquidation.
Other retailers forced to close stores this year include:
Recommended reading:
It’s also been reported that Morrisons is looking to sell some of its in-store pharmacies as it continues to cut costs.
Despite this, several major brands have announced new store openings for 2026, including Aldi, M&S, and Superdrug.
Which UK business that has closed this year were you most sad about? Let us know in the comments.
Business & Technology
Poor data quality is biggest barrier to AI adoption
SOFIAH NICHOLE SALIVIO
News Editor
Dayshape has published research suggesting poor data quality is the biggest barrier to effective AI adoption for many UK professional services firms, with 34% of senior leaders identifying it as the main obstacle.
The survey of 200 UK senior leaders in professional services found that investment in new technology has become a major management priority. Some 61% of organisations said it is now a top business priority, while 50% of respondents said it is their main personal focus for the year ahead.
The findings point to a gap between the sector’s appetite for AI and the operational conditions needed to support it. Integration with existing systems was cited by 32% of leaders as a barrier to effective AI use, while 28% pointed to cost and investment requirements and 22% to a lack of internal capability.
That puts data issues ahead of problems that often dominate discussion around AI adoption, including budgets and skills. The figures suggest firms are finding the quality and consistency of their underlying information a more immediate challenge than buying software or assigning staff to manage it.
Current use
More than half of respondents, 54%, said their organisations already use AI for data analytics. Another 47% said it is used for data entry, while 41% use it for innovation.
AI is also spreading into operational planning. The survey found that 39% of firms use it for workforce optimisation, 34% for project and resource planning, and 29% for capacity modelling.
These figures indicate that AI is moving beyond isolated experiments into areas that affect staffing, utilisation and client work. In professional services businesses, where margins and delivery schedules often depend on accurate planning, weak data quality can directly affect how useful AI tools prove to be.
Expansion plans
Leaders also expect AI use to increase in business areas tied closely to forecasting and service delivery. About 32% said they plan to expand its use in client delivery tools, 32% in capacity modelling, 31% in project and resource planning, and 30% in workforce optimisation.
The emphasis on these functions suggests firms are not treating AI simply as a back-office tool. Instead, they are looking to deploy it more widely in decision-making and operational management, where inaccurate or fragmented data can limit the value of automated systems.
The study was conducted by OnePoll on behalf of Dayshape. According to the company’s background notes, it surveyed senior leaders at professional services firms in the UK and US with more than 750 employees. The UK findings released by Dayshape focused on responses from 200 senior leaders.
The data comes as professional services groups face pressure to improve productivity while managing hiring costs and shifting client demands. Many firms have invested in digital tools in recent years, but the survey suggests that connecting systems and improving data standards remain unresolved challenges.
Andrew Bone, Vice President of Product at Dayshape, said the value of AI depends heavily on the quality of the business information beneath it. He said firms would fall short if they treated AI deployment as a standalone initiative without addressing broader operational weaknesses.
“Many people in professional services firms already struggle with poor data quality, disjointed systems and internal silos, placing a huge drag on operational effectiveness. Similarly, AI initiatives will not meet expectations if they are layered on top of those foundations. The organisations seeing the most value are the ones focusing not just on adopting AI, but on strengthening their data and building the internal capability to use these tools effectively. The findings highlight a shift in how organisations need to approach AI adoption, with greater emphasis on readiness as well as investment,” said Bone.
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