SAP customers see S/4HANA and AI as top digital transformation drivers

Feeling a sense of urgency to migrate to the cloud and digitally transform, SAP customers find themselves nearing a point of inflection, with skills shortages and data reservations poised to impact their outcomes.

Two of the biggest sources of pressure are the looming 2027 end of SAP’s mainstream maintenance for SAP Business Suite 7 — giving members a two-year window to adopt its successor, SAP S/4HANA — and the desire to embrace emerging technologies like AI. That’s the story writ large by the 2024 Pulse of the SAP Customer Research, released by the American SAP User Group earlier this year.

“When you look at the emergence of generative AI and what we’ve seen through Gemini on the Google platform, Joule from SAP, ChatGPT, and Copilot from Microsoft, it’s all about these new and emerging AI models,” said Geoff Scott, ASUG CEO and chief community champion, in a podcast conversation with ASUG research director Marissa Gilbert. “There’s one thing they have an insatiable appetite for, and that’s data. If you really want these models to perform well over time, they’re going to require digital transformation.”

And SAP customers’ appetite to do so is increasing, with 48% of ASUG members saying that moving to S/4HANA was a top area of focus, up from 42% in 2023. SAP’s S/4HANA ERP software was first launched in 2015, and as of 2024, 47% of ASUG members are either already using it or have started the implementation process. The survey also found that 69% expect to have implemented S/4HANA within two years.

ASUG members moving to S/4HANA are also largely migrating from on-premises ERP environments to cloud environments. In 2024, 62% of ASUG survey respondents said they’re running or will run S/4HANA in the cloud: 40% in a private cloud, 16% in a managed cloud, and 6% in public cloud.

“Fifty-seven percent of ASUG members continue to view migration to the cloud as having a significant impact on their organization’s digital transformation efforts,” Gilbert said, “and that’s just preceded as a top driver by data analytics and dashboards, which came in at 62%.”

Members who’ve been slow to make the shift say they’re struggling with outdated and highly customized legacy systems.

“For many who’ve been on SAP for a long time, it can feel a little daunting to potentially unwind years of customizations,” Scott said. “How do you make sure your business processes are really tuned to a future environment? For those individuals, I’d say the need to change is probably greatest for them, and they’re probably the ones finding it hardest to do.”

Meanwhile, SAP customers from the DSAG community in Germany, Austria, and Switzerland have been critical of SAP’s S/4HANA cloud strategy, with just 13% expressing a positive opinion and nearly half expressing a negative one, according to Jens Hungershausen, DSAG chairman.

The case for AI

The annual survey found that members are increasingly looking at AI and machine learning as among the top technologies impacting digital transformation efforts, surging from 23% of respondents in 2023 to 38% of respondents in 2024. Members say they want to solve numerous challenges with AI, including 42% who want to use it for dashboards and analytics, 22% for customer experience, 21% for transitioning from manual to digital processes, and 21% looking to leverage it for integration between SAP and non-SAP systems.

While there’s been a great deal of excitement around gen AI, further results of the Pulse survey show that concerns over data continue to be an inhibitor to adoption, as only 13% of respondents indicated they were currently willing to load data into a gen AI model.

“Companies are reluctant to add their content as they’re concerned about their IP leaking out through the models,” says Robert Parker, SVP of industry, software, and services research at IDC. “The concern is a bit overblown now as the major vendors have private implementations that keep company content confined to company use. It is pretty safe.”

However, Parker says, there are major challenges around data organization. Companies need to overlay their data sources — unstructured, structured, and instrumentation — with a semantic graph that recognizes the relationship between data elements, something he says is necessary for inference, noting that companies still remain largely immature in this area.

A question of skills

The drive toward S/4HANA and AI are also playing a key role in what ASUG calls “the great reskilling,” adding that nearly a third of its members plan to implement new technology this year, but 27% said they’re struggling to keep up with the pace of change related to technology. Plus, 28% said they’re struggling to find the right internal candidates with the skills to manage new projects. The specific skills members highlighted as most in-demand were for S/4HANA, followed by AI, optimizing emerging technologies, and business process management.

Since gen AI is so new, now is the time when the technology is at its worst, says Scott, but it will get progressively better. “Keeping up with the pace of technology changes, in my opinion, will follow a very similar route, so this is only going to get faster,” he says.

IDC’s Parker agrees about the skills gap, but notes that companies need to think about soft skills as much as technology skills to successfully make the transition.

“One CEO told us that AI wasn’t going to replace people, but people with AI skills were going to replace those without,” he says. “I think there are two critical elements: Companies have to think about their current career ladder with the two bottom rungs gone, which will dictate how they influence higher education and recruiting. Second, they have to shift skills that largely support middle management roles to skills that are related to good judgment.”

Successfully making the transition means flatter organizations with more empowerment for decision makers working with AI models, he adds.

“Maybe one bonus is that senior executives will have to be savvier when it comes to understanding technology, particularly the value of data and AI models,” he says.