Celonis - British Government could calm tax concerns by supporting AI adoption

It’s no secret that productivity in the UK has been flatlining for a decade or more. The British Government has deployed numerous strategies to stimulate growth, but a combination of the COVID-19 pandemic, Brexit and multiple economic headwinds has meant that the economy has remained stagnant. An election earlier this year saw the Labour Party take power, which presented an opportunity for change, but the new Chancellor’s first budget has resulted in growing concern from the business community that increased taxes - particularly the rise in National Insurance contributions - will make economic growth harder still. 

Businesses claim that the rise in taxes will either lead to suppressed salaries, force a reduction in their headcount, or result in higher prices. However, as Chancellor Rachel Reeves has argued, there is an alternative option: improving efficiency amongst businesses to lower their cost base. 

This is ultimately the takeaway from some new research released today by process intelligence vendor Celonis, which surveyed 500 UK business leaders, and found that there is appetite for more support to invest in new technologies - including Artificial Intelligence (AI). 

The survey found that 85% of UK business leaders feel that their productivity efforts are being held back, citing economic headwinds, employee stress and difficulty implementing new tools as the three core issues. This comes against a backdrop of 57% of UK companies reporting turnover challenges in October 2024, according to the ONS. 

An argument that has been made previously, one which Celonis VP and Leader for the UK & Ireland Rupal Karia agrees with, is that the AI arms race doesn’t necessarily need to be won by the country that develops the largest AI companies - but could in fact be won by nations that adopt AI the most effectively. Speaking with Karia, he said:  

If you think through many technologies over the years, the country or place it was founded wasn't where it's been most successful. The challenge with AI, although hugely adopted already, as the research shows, is there's not many people yet that feel like it has completely revolutionized their business. 

Respondents to the survey said that AI (46%) is more than twice as effective at driving employee productivity than return-to-office mandates (19%); but over a third (36%) say they still struggle to extract the expected value. Commenting on the latter figure, Karia added: 

I was actually surprised that it was that low. I thought it would be higher than that. 

Speaking to the new government’s recent budget, the complaints from the business community and the role that AI could play, Karia said: 

You could argue that the UK Government can really help companies with that. There’s been challenges with the budget - should we be doing things to help companies get ahead [with AI] in terms of knowledge? Maybe even in helping fund AI projects, because there is a first mover advantage. And genuinely, if we get that right, our productivity levels, which we've been so far behind in the UK, could be advantageous. 

AI on the ground

According to the Celonis survey, employees are currently spending 154 hours per year manually troubleshooting processes which could be automated. It found that almost half (48%) of business leaders are already investing in AI-driven solutions to improve productivity, with 39% saying that these investments are having an impact. Despite these investments, almost one in three (31%) cite a disconnect between senior management and staff as hindering morale, and a lack of digital skills adding to this productivity conundrum is reported at one in four companies (24%).

Karia said that these findings, coupled with the recent Budget in the UK, could also force the hand of companies to invest in AI more quickly: 

I had dinner with some of my team yesterday and they had actually been with one of the big grocers - and of course, they are hugely impacted by the National Insurance contribution. We're talking to them already about doing stuff, but I think that might accelerate their choice now. What are they going to do to try and bridge the gap in terms of that big hole that they’ve got to fill? In some ways, whether it's AI, or any other technology, they're going to have to double down if they want to try and keep their people in the business.

However, Karia was keen to state that AI isn’t a “silver bullet” and that whilst the technology industry is coming out of a very intense period of hype, work and thought now needs to be put into how and where AI is adopted: 

AI is so broad, you can get yourself scared, because you can say. ‘we're going to deploy AI’, but what are you trying to do with it? Are you trying to automate processes? Are you trying to give it predictive models? What's the thing you're trying to address? And therefore, I think the first thing is, what's the business problem you're trying to solve with the AI models? You need to know the purpose for deploying the technology, rather than just deploying the technology. 

Very comforting to hear this line coming from a vendor, given that a lot of others in the market are pushing AI into the enterprise seemingly with little thought as to what problems it is aiming to fix. As Karia said, often the outcome is “lipstick on a pig”:

There are companies that try to go quite bold and do quite meaningful things, but it's actually quite expensive. If you look at the cost of failure, it is pretty high as well. I think the thing which is important is picking a particular use case to go after. 

Rather than using AI to try and fix the whole world, [think about] is your problem supply chain? Is it customer value? Is it customer acquisition? What is the thing? Try and do one thing well and then look at how you try and deploy. 

A differentiator 

Karia notes how Celonis actually took its time - seven or so months after other vendors - to lay out its positioning for AI in the market. The vendor is arguing that process intelligence is going to be key to effective generative AI deployment. According to Karia, it didn’t want to rush to market without a coherent proposition - not taking the path of rebranding ‘everything AI’ like some other vendors. 

However, he suggests that companies should be thinking about their AI adoption in terms of how it can differentiate them in the market. Whilst recent technology waves, such as cloud or mobile, have broadly been about how technology services are delivered - Karia argues that AI is about how you use your data to differentiate. It’s less operational by nature: 

Cloud was basic infrastructure - it is just what data centers did for a long time, right? You didn't really need to know about it if you were in a customer facing role or in the front of the business. 

AI is the opposite. If you think about chatbots, if you think about your interfaces to customers, this really could become your IP to make you more differentiated in the market. 

For me, the ones that will do well are not the ones that just use it in the back office to automate some stuff - RPA has been around for years. The users that are going to be most exciting are the ones that use it at the front end of their business to transform and be different - the next generation of customer care. 

Looking ahead, Karia said that as a UK citizen, as part of a company that’s growing rapidly in the UK, the government hasn’t made it easy for the adoption of new technologies (particularly when compared to some other nations). The UK&I leader argues that the government should take a more holistic, proactive approach to ensure that we, as a nation, adopt AI not only quickly, but effectively: 

If we forget about Celonis for a second, forget every other tech company - if we want to be ahead of every other nation, which we should be, how do we get ahead? Part of that will be getting people trained, all the way through from school to university age. 

Part of that is helping technology companies deploy the technology at a much cheaper cost base. Part of that is also considering tax benefits, if you do certain things in certain ways. 

But there's a whole series of end to end ideas, that needs to be a package of work, to really deploy - not just AI, but any technology - to take us to a productivity level that is completely different to where we are today.  We've got to have something that's legislative to help get ourselves ahead of everyone else. 

My take

Surveys proclaiming the productivity benefits of AI are not hard to come by, but if you dig a little deeper into what Celonis is proposing - particularly when looking at Karia’s comments - it’s a much more thoughtful and measured approach than we are typically seeing in the market at the moment. It’s welcome that Celonis is talking about thinking through use cases and starting small, coupled with effective governance and seeking support for differentiated adoption in the market. What’s also clear is that it’s early days for AI and organizations are still figuring out where the meaningful gains are.