Deciding to explore AI is just the starting point. For many CIOs, the hard work begins when the organisation tries to find ways to turn this emerging technology into a competitive advantage, with recent research from MIT NANDA reporting that just 5% of AI projects deliver value.
Rupal Karia, SVP for North America, UKI, and MEA at technology firm Celonis, is one executive who wants to help digital leaders turn AI explorations into profitable exploitations. Having worked in senior roles at Fujitsu, Adobe, and UIPath, Karia took his experience to the fast-growing AI specialist in early 2024. After a year and a half as GM for UKI and MEA, he added responsibility for North America at the start of September.
In this Q&A, edited for length and clarity, Karia talks to Tech Monitor about the challenges associated with implementing AI, regional variations, and cultural sensitivities, with Celonis research suggesting 81% of UK businesses are grappling with low morale and burnout. Here’s what Karia believes enterprises can do to make the most of AI.
What are the major challenges to delivering AI projects successfully?
The biggest issue right now is companies being able to use AI at all because of the amount of security governance and documentation you’ve got to fill out just to try it on your estate. Every country is a bit different, but in the UK, we talk about being an AI powerhouse. We can have all the technology in the world, but unless we make it easy for adoption and find ways to get through security quicker, we’re going to slow ourselves down.
From a public sector standpoint, we do a lot of work in the NHS, and for every single Trust, we’ve got to sign specific paperwork. It’s crazy, and it’s a topic where everyone says, ‘Oh, we should make it easier.’ But we have a contract with the highest level of security with BAE, and we still must go through all this paperwork. So, we’ve got to find a way for tech companies to be able to do things quicker.
How does AI adoption differ from the UK to Europe and the Middle East?
One thing I’ve noticed is the number of people who come to our events in the Middle East. We have openings in the UAE and Qatar, and there’s a real hunger for knowledge. We’re a much smaller company there, but we already have the same sort of take-up for events as in the UK. They haven’t got a lot of legacy IT, so they’re quicker to try new technology. Therefore, there is slightly more visionary thinking. That trend is also happening in Africa, not all of Africa, but certainly in South Africa.
The big European countries, such as France, Germany, and the UK, are quite similar. They’ve all got the same regulatory challenge. The subtle difference with the UK is that we still have many global companies headquartered here. We’ve still got the size and scale of companies, which we really need if we’re going to become an AI powerhouse.
And how do the UK and Europe compare to the US?
AI adoption on the West Coast is much higher because people are very technically savvy. I’d say the East Coast is similar, but more risk-averse, because the implementations often involve banks and insurance companies. Many people treat the US as one place, but it’s a bit like Europe. You’ve got to think about it in clusters. I think what will happen is that you’ll start to get tax benefits for certain states, which will make adoption higher.
Culturally, it is possibly easier to be entrepreneurial in the US than in the UK and Europe. More people are willing to try new things. There are so many companies in the US, and because a lot of them are backed by private equity, there’s probably more willingness to try new things.
What are the AI inefficiencies you’re seeing across major enterprises?
No one’s data sits in one system. You might have stuff in SAP, Workday, Snowflake, or Databricks. Even though some of those technology providers have good solutions, the answer is not on one path. You’ve got to have something that connects those systems to make an AI model the right solution for your business challenge. Unless you’ve got the end-to-end view, there isn’t much value.
We’ve set the IT industry up via big technology companies, but AI isn’t linear. That’s where Celonis will have an impact. We’re one of the few companies that can stitch multiple companies together. So, when you ask the AI model a question, we can give you an answer in real-time that’s meaningful. The companies that bring systems together will be the ones that power the next evolution of AI adoption and usage.
More generally, why do you think low morale and burnout are such a big challenge?
Enterprise executives went through a period after COVID where they said, ‘Work from home. Get a work/life balance. Come into the office one or two days a week.’ And then suddenly, in the last year or so, people have flipped and said, ‘We’re going to make you come back to the office.’ However, the people who’ve only been in the workplace for five years have never experienced going to the office every day.
We’re expecting people to change and not get fatigued. We’ve got to try and tackle this as an industry by making work a fun place to be. At Celonis, we run a free lunch and a social once a week. We also do a stand-up once a week, where I talk and build motivation. Too many companies mandate going back to the office rather than thinking, ‘What’s the benefit?’ For our next-generational workforce, that focus is crucial.
Will the implementation of AI create further morale challenges?
The talk track now is all about jobs being automated, particularly for mundane tasks. But we’ve been doing that for years – my previous employer was an automation company. I think the bit about AI that excites me more is the fact that you’ve got, for example, technology that can identify cancer quicker than any person. I can have the brain of every surgeon in a model and, in real-time, find answers much more quickly.
These changes in all kinds of industries will be hugely powerful, rather than the changes that everyone’s talking about right now, which is this middle layer of jobs that is going to be impacted. Just think what AI is going to do in terms of getting medicine to market quicker and helping to cure illnesses. That’s what excites me, because you can transform people’s lives.
What does successful AI adoption look like at the companies you work with?
Arm is doing some special things. It’s a very innovative company anyway, but they’re really thinking about AI at a different scale, and they’re doing well because they’re thinking about it as an end-to-end architecture. They’re stitching organisations together with support, which I think is compelling. Arm is an interesting use case because it has transformation in its DNA.
A totally different example is Smurfit Westrock, which is one of the biggest cardboard manufacturers in the world. They had spare parts issues and, as they had global factories, we found parts in different areas to ensure they had no downtime. They wouldn’t call that effort AI in their mindset, because it was just doing basic things right, but it was an important change. We just used our AI to give them the answers to their questions.
What key takeaways would you share with digital leaders?
We used to talk about five- or maybe even 10-year plans. I think we must get out of that mindset because no one can predict five years from now. I would be in the mindset of thinking of a one to two-year plan. However, be willing to change regularly. Yes, some of the big companies are always going to be around. But new technology is disrupting the industry. We’re only 14 years old, yet we’re used by many Fortune 500 companies.
As an executive, you’ve got to cope with change. Take my example – two weeks ago, I was running the UK, and two weeks on, I’m running America. You’ve got to pick things up and be able to adapt all the time. If you’re not good in that environment, which many traditional CIOs aren’t, you will struggle. Getting someone who’s got the potential to adapt and tweak, rather than the experience of doing something before, is now probably more important.
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