There are still so many questions about the use of artificial intelligence, and it feels like vendor patience is wearing thin.
For the second time in my life, I found myself in the Houses of Parliament last week.
I'll admit the first time was a school trip designed to inspire budding journalists to reach the top of the newsroom, where we watched a debate in the chamber and questioned the local MP about his constituency, a couple of hundred miles away.
On this occasion, I found myself in a Gazebo on the Terrace Pavilion of the House of Commons, 420 years after Guy Fawkes attempted to blow the whole thing up, To hear about the 2026 Work Style Monitor Year One report, titled “Building Connective Capability”.
The research, conducted by Workstyle CIC in partnership with King’s College London, overseen by Proffessor Michael Clinton and sponsored by Jabra, examines how work is evolving in the era of artificial intelligence, analyzing working conditions as an interconnected system, rather than making speculative forecasts.
In a nutshell, the report found that employee well-being and productivity grew when they were given greater autonomy, good experiences with technology go hand in hand with stronger employee outcomes, and that a hierarchical team structure can have negative impacts and can be an inhibitor to productivity.
If we were to take these findings to their logical conclusion, the hierarchical pyramid that every business in the world, I would bet, runs on, would be collapsing before us. Boosted by ‘super intelligence’, employees are able to be more productive without the bottlenecks of having to report to somebody higher up about their progress.
I think it would be foolish to suggest that we haven't all been here. Although it's important to keep control of tasks and what every employee is doing, hours and eventually days are wasted filling out spreadsheets and trackers just to essentially say, "I have done my job this week."
Enabler or Replacement?
Your perspective and where you come from when tackling the issue of artificial intelligence in the workplace, matter a lot.
The technology industry likes to believe that it is not in the business of replacing humans or jobs, but the fact is, it kind of does, and it kind of is.
This dichotomy is summed up perfectly at the end of Chapter 3 of the report, with a headline reading: "There is an opportunity to redesign work around human differences, not the average worker,” The idea being that, although the results are the same, different people apply themselves with different levels of effort, depending on who they are as a person.
These are the sort of ideas that come out of research that shows that productivity amongst younger people is higher when they have a positive experience with technology, in this instance, artificial intelligence. However, I’d wager that a lot of decision makers within businesses will see this as justification for investing in artificial intelligence: throwing a Co-pilot or Slack Bot at the employees who have just lost a member of their team.
The findings that younger people are more productive using AI is hardly a surprise. But bitter sweet fact is that as of May this year there are just shy of a million 16 to 24-year-olds not in employment, education or training, and unemployment in this age range has been on the rise since 2022, the year ChatGPT was made widely available.
What’s in the Box!?
It's not a surprise that opinions are softening around AI. The much-used and out-of-date quote from MIT saying that 95% of GenAI pilots fail is now being challenged, and surveys of employees are now finding that the majority can get along with an agent.
According to the AI Attitudes: A 12-Month Pulse Check report from Henley Business School, 58% are optimistic about AI at work and the UK Employee AI Sentiment report this year from PWC found that 70% feel confident about increasing AI use at work, 72% feel empowered, and 72% feel energised using AI Tools.
That enthusiasm will be music to the ears of those in the vendor community who seem to be almost begging MSPs and businesses to get going and invest in the AI tools they have added to their own solutions for fear of obsolescence.
My own sense is that businesses will be dragging their feet when it comes to AI. Not because of any limitations it has, but because of the hurdles that need to be overcome before any benefits are realised.
Artificial intelligence has caused such a stir because it is a tangible product. Anybody can go to ChatGPT and ask it to find what they're looking for. But before integrating it into a business IT teams need to sanitise the data that it will use, draw up their own AI policy and decide which tools can be used, train employees on how to use it and how not to use it, and continue to monitor the workforce to make sure the tools they have in place are being used correctly, if at all.
That's a hell of a lot of time, effort, and money that would be ploughed into what is, at the moment, essentially a productivity tool; A tool that some employees still have reservations about.
The research from the Henley Business School showed that 61% feel overwhelmed by the pace of AI development and 28% describe their overriding attitude towards workplace AI as cautious, indicating that adoption may be slow in some businesses. On top of that, 16% fear negative consequences if they experiment with AI, 13% say their employer restricts access to AI tools, and 13% are confused about their company's AI policy according to PWC.
To my mind, these factors only point towards more job cuts, and more unemployment. When the P&L is not looking too good, the first cut is to the workforce. That doesn't necessarily mean redundancies, but speaking to businesses and speaking to people within the technology sector, there is a practise of not replacing employees that leave going on at the moment.
Artificial intelligence will only seem to justify these moves. As AI takes away the "boring" jobs and, in theory, frees employees up to do the core work that they have been employed to do, they will be asked to take on their outgoing employees' jobs as well.
I'd love to be more optimistic, but unfortunately, I think we are in the over-reliance part of the adoption cycle. When profits are viewed as a result of AI adoption, we will truly see what an AI-enabled enterprise can do.
Building Resilience
This week’s outage has raised several questions across the private and public sectors, as it laid bare the over-reliance on cloud technologies.
Earlier this year, the Cyber Monitoring Centre and Parametrix published a report on UK exposure to cloud infrastructure failure. The study finds that more than 60% of UK companies depend on cloud services for critical functions, a figure that rises to 80% of FTSE 100 companies.
Dame Meg Hillier MP, Chair of the Treasury Committee, has written to the Bank of England and the Financial Conduct Authority requesting a timeline of events on Tuesday, how many banks and customers were disrupted, and a list of lessons learnt from the outage.
According to Dawson, this is an example of the “uncomfortable conversations” departments will have to have after this week.
“Banks and payment providers spend a fortune on keeping their systems running,” said Dawson, “but how many know whether their backup supplier is using the same Google infrastructure as their main one? That's something I'd want an answer to.
“We've known for years that cloud services can fail, and there's really no excuse for waiting until customers are locked out of their accounts to find out whether your contingency plans work.”
Pfaelzer described these outages as “inevitable”, adding, “The key question for every organisation is not just, ‘Can we recover our systems?’ It is, ‘Can we keep running the business while they’re unavailable?’
“That means defining a ‘Minimum Viable Business’, the essential processes, systems and data that must continue during an outage, and understanding which suppliers it depends on. Relying on one region or one provider is a risk to plan for, not assume away.”
“As the FCA has made clear, people need to be able to access their money and make payments. That takes a data resilience strategy with no single point of failure. Keep copies of critical data away from the main environment and be able to restore operations quickly to a known good state, somewhere else if necessary. That plan should be tested before a day like today, not during it.”
“Resilience may not be particularly glamorous, but it's something the industry needs to invest in and properly test,” said Dawson.
“You can have all the latest technology, but it's not much use to a merchant who can't take payments or a customer who can't access their money. Getting everything running again is one thing, but restoring confidence in a service people depend on is quite another.”
