“It’s not hype anymore, it [AI] is really a game-changer, [and] it will change our lives nowadays and in the next some years,” Tamás Kórász, a KPMG Hungary partner for management consulting, declared opening a joint forum with the British Chamber of Commerce in Hungary on Sep. 11.
Estimates by the professional services firm conclude that back-office workers employed, for example, in HR payments or procurement administration, if equipped with AI solutions, may save between “40-50% of their time in the next years,” Kórász said. “This is an absolute game changer […], so you have to think how you can change the different job descriptions because it [will be] absolutely different from nowadays.”
However, AI appears in many guises, from controlling drones and self-driving cars to ChatGPT helping half-literate students write impressive (and often exaggeratedly literate) CVs. Such are all seemingly far removed from the hum-drum, daily processes of the business world.
Ágnes Rakó, KPMG Hungary’s partner in risk consulting, offered some historical context to illustrate the background. Starting as an auditor with KPMG 25 years ago, Rakó steadily expanded her experience across boundaries into finance, modeling and mathematical skills.
“About seven or eight years ago, we started to see that these areas are very nice and very useful, and there is a need for these services, but the kind of mindset and requirements of our clients were changing,” she said.
Clients still needed well-written advice but increasingly needed and valued solutions capable of being immediately usable in their operations.
“Where we started, based on our very basic service, which is outsourcing, we started to experiment with data and automation tools, and based on that, we built a data and automation team,” she recalled. This step-by-step approach led, in turn, to experiment with AI from about three years ago.
“We started to set up our AI team. It was easy in the sense that we had lots of people with multiple skills, so we had a base, and we recruited many people over time, and now we have a very sizeable team of AI machine-learning, data scientist people,” she said.
However, for Rakó, the crucial point is not to have separate AI “experts” underpinning progress in the new age of digitalization but to spread the knowledge and use of AI into all the traditional business professions to become part of the standard skill set.
“What we believe is useful for the future [is to] have this kind of natural approach to AI, […] to have that kind of mindset within our teams and colleagues, regardless of our basic fields […] to bring forth smarter solutions with savings in time, efficiency and also creating new products and new services,” she argued.
Péter Ignácz, KPMG’s manager for data analytics and modeling, reinforced the message that, despite the massive progress attained so far, the use of AI is still in its formation stage; even “experts” are still exploring systems for their potential and limitations.
If this applies to the “experts,” it certainly applies to businesses seeking to adopt AI in everyday life.
“What’s important is that without actually trying these tools, you won’t be able to comprehend what the upside is for you, so as Agi [Rakó] mentioned, you have to start experimenting on a small scale, […] otherwise you will know the cost because they are going to tell you, but, the benefit that you are going to get out of these tools or models or applications, that’s for you to figure out because it varies from client to client and use case to use case,” Ignácz stressed.
It’s also important not to get caught up in the stampede, seeking to use AI when it’s not necessary.
“If there is a problem that can be solved by automation or simple applications, please do that because then you don’t need machine learning. [But], if you are unable to define or solve your problems with rules or simple applications, that’s where you need examples, and on those examples, you will train your machine-learning model up to 95%, 90% or 85%. You will see what the end result is,” he said.
Ignácz admitted that the results from employing predictive AI are often still imperfect, with systems capable of producing “hallucinations,” that is, false results. However, even with these glitches, teams can still use AI applications to make extensive progress quickly into complex data fields and reports. As for less complex tasks, many solutions already exist.
“For example, if you get an email, you can automate the whole process, asking the status and the next payment installment and everything, and generate an answer letter for that client inquiry so that almost all of the process is automatic, and probably there will be a human in the loop to check whether this is factually correct and send the email,” he said. “This is not science fiction; this is a viable solution today.”
Working to develop AI for business solutions has led Ágnes Rakó, KPMG partner for risk consulting, to conclude that Hungarian universities are “not up to speed,” she told the KPMG-BCCH forum in post-presentation question time.
“What I’m honestly a bit worried about, looking ahead [… is that] overall, the education system is definitely not up to speed. We hire many graduates, but honestly, it doesn’t really matter what they learned at university because we have to start from scratch,” she said.
Reacting to an audience suggestion that better soft skills were needed, Rakó remained adamant, quickly stressing that the issues begin at an even more basic level.
“Not just soft skills, but also technical ones, because […] whatever they learned is outdated, very much outdated and, basically, we have to start from zero,” she underlined.
As for recruitment, she said: “Whenever we hire someone new, we rather hire [based on] the personality, the potential capabilities, and of course, the way of thinking, but we have to accept that we start from zero.”
Expanding on this issue, marketing and communication director Gabriella Liptay noted that KPMG Hungary had recently signed a strategic agreement with the Budapest University of Economics (BGE) to alleviate this problem.
“We have experienced that [with] the knowledge we create here, not only us at KPMG, but the companies and us together have the wish and opportunity to go further with this education and knowledge sharing,” she said.
This article was first published in the Budapest Business Journal print issue of September 20, 2024.
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