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<\/p>\nThere was a time when introducing new technology into a business meant buying a faster computer, installing some software and hoping nobody broke the printer. Artificial intelligence (AI) has rather more ambitious plans.<\/p>\n
It is already summarising documents, processing invoices, taking meeting notes, helping with calculations and automating tasks that once swallowed hours of someone’s working day.<\/p>\n
And for businesses, the attraction is obvious. If a job takes four hours and AI can get you most of the way there in 20 minutes, it is difficult not to take notice. <\/p>\n
But around at a roundtable hosted by Parsons Accountants, the conversation quickly moved beyond the shiny promise of AI and into the messier reality of actually using it.<\/p>\n
Who checks what it produces? What happens to confidential information? Can businesses trust the answer? And what happens to the people whose jobs currently involve doing the things machines are getting increasingly good at?<\/p>\n
Dean Spencer, founder of MSP company Eitex, said businesses were increasingly asking how AI could solve very specific problems.<\/p>\n
In some cases, the productivity gains can be dramatic. \u201cWhat used to take 2, 3, 4, 5 hours can take 20, 30 minutes sometimes,\u201d he said.<\/p>\n
For Dean, however, the attraction is not simply about cutting headcount or shaving costs. Automation can free people from repetitive work and allow businesses to make better use of the people they already have.<\/p>\n
But nobody is ripping out the workforce and replacing it with robots just yet. The current approach, he said, is more about \u201cbaby steps\u201d \u2013 trying tools against real business problems and working out where they genuinely add value.<\/p>\n
That pragmatism ran through much of the discussion. The businesses around the table were not talking about AI as some futuristic concept waiting to arrive. They were already using it. The question was whether they were using the right technology for the right job.<\/p>\n
The examples ranged from summarising documents to processing invoices. Ringo Scheithauer, who runs an organic food business with his wife, said his finance team was already using automated tools to process invoices.<\/p>\n
But he was keen to make a distinction between automation and AI. Not every process involving a clever piece of software is necessarily artificial intelligence, he pointed out.<\/p>\n
That distinction matters because the best technology for a business problem may not be the most fashionable one. There was discussion about whether businesses will increasingly turn to specialist systems designed to do one job particularly well rather than broad AI tools expected to answer almost any question thrown at them.<\/p>\n
There is also a rather more awkward question hanging over the current AI boom. How long will cheap or apparently free access last?<\/p>\n
Behind the apparently effortless answers is an enormous amount of computing power, infrastructure and investment.<\/p>\n
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At some point, somebody has to pay for it. For businesses, that makes the decision about AI rather less straightforward than simply signing up for a free trial and seeing what happens.<\/p>\n
The great selling point of generative AI is speed. The great weakness is that it can be wrong. Ian Parsons, founder of Parsons Accountants, said AI could be extremely useful for summarising documents and taking meeting notes.<\/p>\n
But useful does not mean infallible. The person receiving the answer still needs to check it.<\/p>\n
Damian Walsh, whose family architectural business works across a range of sectors, raised an even more uncomfortable example.<\/p>\n
AI can produce an answer which sounds completely convincing while being completely wrong. It can, he said, even invent legal cases to support its conclusions.<\/p>\n
And architecture provides an excellent illustration of the problem. A computer can produce an image that looks fantastic. That does not mean somebody can actually build it. \u201cWhere it may look good, but behind the scenes, the building regulation part physically couldn\u2019t exist,\u201d Damian said.<\/p>\n
That is the wider problem businesses are wrestling with. AI is very good at producing something that looks finished.<\/p>\n
It is not necessarily very good at knowing whether it is right. In sectors where an error can have legal, financial or safety consequences, that distinction is rather important.<\/p>\n
Which brings the conversation neatly back to people. Somebody still needs to know enough to spot the mistake.<\/p>\n
Accuracy is only one part of the AI headache. The other is information. Businesses are increasingly asking staff to use AI tools, often without fully understanding what happens to the information being fed into them.<\/p>\n
Tanya Goldthorpe, sales and marketing director at Blacker Hall Farm Shop, said employees were already using different tools for different tasks.<\/p>\n
Some staff were using AI for everyday office work, while its butchery manager had used it to help with yields and inputs.<\/p>\n
The business had begun looking at policies and procedures to establish clearer rules. Because there is a fine line between asking AI to tidy up an email and putting commercially sensitive information into a system without thinking about where that information goes.<\/p>\n
\u201cOur biggest concern as a business that we\u2019re inputting our personal data,\u201d Tanya said.<\/p>\n
And that is a moving target. The technology is changing quickly, which means the policy written today can look rather old-fashioned by next Tuesday.<\/p>\n
Dean said a company-wide policy could help replace the current free-for-all, where individual employees decide for themselves which tools to use and what information to put into them.<\/p>\n
The group also discussed a cautionary example involving commercially sensitive tender information being entered into an AI service during a last-minute document check.<\/p>\n
Employees need to know what they are allowed to put into AI tools, which systems have been approved and what happens to information once it has been uploaded.<\/p>\n
For Katie Town , chief executive of\u00a0 Royal Theatre Wakefield, the issue is particularly sensitive because the organisation’s relationship with its audience is arguably one of its most valuable assets.<\/p>\n
\u201cOur relationships with our patrons is the biggest bit of IP that we\u2019ve got,\u201d she said.<\/p>\n
The theatre already has an AI policy. But for Katie, the bigger question is not simply how technology can make the organisation more efficient.<\/p>\n
It is how to make sure efficiency does not strip out the human connection which makes going to the theatre worthwhile in the first place.<\/p>\n
And then came the question that tends to make conversations about AI slightly more uncomfortable. Jobs.<\/p>\n
Don Stewart, strategic director at Britcon, said AI proficiency was increasingly becoming a consideration when recruiting.<\/p>\n
But he was also worried about what happens if automation moves beyond taking away the dull jobs and starts removing the entry-level roles through which people traditionally learn a profession.<\/p>\n
\u201cIt does scare me because \u2026 I think we\u2019re underestimating it,\u201d he said.<\/p>\n
The concern is particularly relevant for graduates and young people entering the workforce. A career often starts with the routine stuff.<\/p>\n
You answer the emails. You process the paperwork. You do the basic research. You learn the ropes. mIf AI does all of that, where does the next generation get its experience?<\/p>\n
Andy Lucas, head of audit at Parsons took a more optimistic view.<\/p>\n
Rather than assuming technology will simply eliminate jobs, he argued that employees could be repurposed and trained to work alongside AI.<\/p>\n
The skill becomes less about doing the task from scratch and more about understanding what the machine has produced and whether it makes sense. \u201cHow do we check it, and how do we teach them to check it in an appropriate way?\u201d he asked.<\/p>\n
That could create new roles around judgement, oversight and customer service. But it also creates another challenge.<\/p>\n
People cannot necessarily move seamlessly from one job into another simply because an AI tool has made their old role redundant.<\/p>\n
Ringo pointed out that it would not be realistic to move every customer-service worker into research and development. Repurposing the workforce depends on what people already know, what they can learn and how much support employers are prepared to provide.<\/p>\n
Tanya said she hoped businesses and communities would choose to use AI to support people rather than simply replace them.<\/p>\n
\u201cIf young people harness that and their least favourite tasks, and we use it as something to help us in our roles and not take our roles,\u201d she said, \u201cI think it\u2019s up to us as people, as a community, as a world to use AI how we want it to be used.\u201d<\/p>\n
That last bit may ultimately be the biggest question of all. Technology does not decide how it is deployed. Businesses do.<\/p>\n
If AI is going to change the workplace, the businesses around the table agreed that the education system needs to change with it.<\/p>\n
Damian believes industry should have a much bigger say in what young people are taught. \u201cI don\u2019t think industry are involved enough with the education side of things,\u201d he said. \u201cThey should have a far better input into syllabuses.\u201d<\/p>\n
It is a familiar complaint from employers. Businesses say they cannot find the skills they need. Education providers point to the changing demands of employers.<\/p>\n
And somewhere in between sits a young person wondering what on earth they should study if nobody can agree what the jobs of the future will look like.<\/p>\n
Damian’s own business has seen the benefits of getting involved early. \u201cOne of the directors at our place came as a work experience kid, and he\u2019s now a director,\u201d he said.<\/p>\n
For him, work experience is about more than giving a teenager something to put on a CV. It gives young people a chance to discover what a job actually involves while giving businesses the opportunity to spot and develop talent.<\/p>\n
Katie described a similar approach. Technical theatre is not necessarily a single-skill profession.<\/p>\n
People can be expected to understand sound, lighting and stage engineering, effectively becoming generalists who can turn their hand to several different jobs. The theatre has recruited local young people interested in the industry and trained them to develop the skills it needs.<\/p>\n
That is one answer to the skills problem. Rather than waiting for the perfect candidate to appear, build one.<\/p>\n
Don said construction faces a particularly significant challenge. \u201cThe industry needs 200,000 more people by 2030,\u201d he said.<\/p>\n
That makes apprenticeships, vocational training and clearer career paths increasingly important.<\/p>\n
Construction has spent years trying to shake off the image of being a sector where the only route in involves turning up on site in a hard hat. There are highly skilled, technology-driven jobs across the industry. The challenge is making sure young people know they exist.<\/p>\n
Lindsay Payne, finance director at Hartwell Manufacturing, said the skills problem is particularly obvious in manufacturing. There are tasks which automation can handle. There are others which are considerably more difficult.<\/p>\n
\u00a0For Lindsay, some back-office functions offer more obvious opportunities for automation than skilled work on the shop floor.<\/p>\n
That distinction matters. There is a tendency to talk about AI as though every job is equally vulnerable.<\/p>\n
It plainly is not. Some work consists largely of repeatable processes. Some requires judgement, dexterity, relationships, creativity or a combination of all four. The technology will not affect all of those jobs in the same way.<\/p>\n
Craig Lawyer, senior tax manager at Parsons, sees professional development as part of the answer. He said he was optimistic about AI and wanted to embrace it personally, including through a qualification in AI and tax technique which he expected to become available.<\/p>\n
He hoped to start after Christmas and then bring what he learned back into the business. That may prove to be one of the more important shifts in the workplace.<\/p>\n
AI skills will not necessarily belong to a small team of technology specialists. They could become part of the basic toolkit for accountants, architects, manufacturers, marketers and pretty much everyone else.<\/p>\n
For Katie, there is another reason not to get too carried away with the efficiency argument. Sometimes people want to deal with people.<\/p>\n
She described a cinema visit where customers could book their tickets, check in and buy refreshments without speaking to a single member of staff.<\/p>\n
It was efficient. It was also, perhaps, a little soulless.<\/p>\n
And that matters for businesses whose proposition is based on experience. Theatre, live entertainment and other in-person activities could become more valuable as technology takes over more transactional interactions.<\/p>\n
If everything else becomes automated, the human bit starts to stand out. Tanya made a similar point about retail.<\/p>\n
Customers may visit a farm shop not simply because they need something from the shelves, but because they want a meal, an outing or an experience.<\/p>\n
Ian’s view of the future also comes back to relationships. At his accountancy firm, service, communication and getting work done on time remain central to retaining clients.<\/p>\n
AI may change how some of that work gets done. It does not necessarily change why a client trusts the person doing it. And perhaps that is where the AI debate gets more interesting.<\/p>\n
The question is not really whether artificial intelligence is going to change work. It already is.<\/p>\n
The questions are how quickly, in which jobs and what businesses choose to do about it. Nobody around the table had a crystal ball capable of settling whether AI will ultimately destroy more jobs than it creates.<\/p>\n
But there was broad recognition of the immediate issues businesses can control.<\/p>\n
They can decide which tasks AI should handle.They can decide what information employees are allowed to share.<\/p>\n
They can decide which systems are approved. And, crucially, they can decide who is responsible for checking the answer when the machine gets it wrong. They also need to train people \u2013 not simply to use AI, but to question it.<\/p>\n
Because the most valuable skill in an AI-powered workplace may not be knowing how to get a machine to produce an answer.<\/p>\n
It may be knowing when not to believe it. AI can take away some of the boring work.<\/p>\n
It may make businesses faster and more productive. But the businesses around the table made one thing clear.<\/p>\n
The future of work is unlikely to be humans versus machines. It is much more likely to be about how well the two work together.<\/p>\n","protected":false},"excerpt":{"rendered":"
Artificial intelligence is already changing the way businesses work, but the real debate is not simply about what machines can do. It is about who checks them, who trains the workforce and whether technology will ultimately replace people or make them better at their jobs<\/p>\n","protected":false},"author":271992,"featured_media":2161048,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[53262,50204],"coauthors":[137100],"class_list":["post-2161044","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-business-news","category-technology","tag-featured-story","tag-yorkshire"],"yoast_head":"\n