Companies struggle to scale GenAI despite high interest

The low adoption of GenAI due to data, talent, and strategy challenges.

Despite the growing excitement surrounding GenAI, companies are facing significant challenges in implementing the technology, according to a recent study by Roland Berger. While 80% of businesses surveyed recognise GenAI as a strategic priority, only 19% consider themselves mature in their adoption, highlighting the disconnect between interest and execution.

Damien Dujacquier, Managing Partner at Roland Berger Southeast Asia, discussed these findings, noting that adoption rates are far below expectations. “When you look at companies that are really reporting that they are using Gen AI, it's down to 40% and only 19% of them are considering they are mature. It goes down to 4% for industrial and manufacturing.”

One of the key obstacles hindering GenAI adoption is poor data quality. “60 to 70% of enterprises consider that it's very difficult to have clean data and have a high quality enough to enable the Gen AI model,” Dujacquier explained.

Another major challenge is employee resistance, with 55% of workers expressing concerns about job security and the disruptions that GenAI might bring. Dujacquier highlighted this as a significant issue: “There are a number of people that are fearing for job security, so a re-skilling plan is quite important, as well as change management.”

Beyond data and workforce challenges, companies are also grappling with a shortage of AI talent. “More than 50% of companies consider that it's difficult for them to recruit AI talent and find it as a major obstacle,” Dujacquier added.

Dujacquier believes the real barrier lies in identifying the right use cases for GenAI. “The more critical reason why companies are facing difficulties in implementing Gen AI is that they have a lot of difficulties in identifying the appropriate use case, and that's a primary barrier for Gen AI adoption,” he said.

To overcome these hurdles and accelerate GenAI adoption, companies need to focus on three key elements: organisation setup, people, and infrastructure.

Additionally, re-skilling employees and building robust infrastructure are essential for scaling GenAI solutions. “The potential of AI is high when you are talking about scaling,” he said, emphasising the need for strong data foundations and flexible architecture.