Why SAP Is Rethinking Its AI Strategy

SAP is moving towards customer-specific AI support to deliver more meaningful business transformation. In a recent push outlined through internal case studies and industry data, SAP argues that the next phase of enterprise AI isn’t about adding automation for its own sake. According to the company, it’s about embedding AI into the DNA of individual business processes.

Why Generic AI Isn’t Cutting It 

While every company is adopting AI today, its return on investment is still inconsistent. If we go by the McKinsey report from 2024 it shows that although 72% of businesses use AI in at least one area, only 23% have seen significant bottom-line benefits. A related IDC study found that nearly half of enterprise leaders cite the lack of domain-specific solutions as a major barrier to ROI. 

There’s another survey by Notion that says that nearly 57% of decision-makers are focused on improving workplace productivity, and half of them are turning to AI for help. But they’re hitting integration roadblocks. The reason is work is scattered across too many disconnected tools, making it tough to embed AI into daily workflows.

Despite the excitement around AI, there’s still a wide gap between what companies want from AI and what they’re actually able to implement.

SAP’s interpretation of this data is straightforward: businesses aren’t just looking for tools; they’re looking for tailored outcomes. The only way to achieve that is through deeply contextual solutions built with the customer, not just for them. 

Built with the Business, Not Just for It

As a result, SAP seems to be changing its AI approach based on three principles: context-rich insights, strong governance, and co-innovation. This means using SAP’s vast access to industry data to ground AI in real operations, embedding trust through responsible AI practices, and building solutions side-by-side with enterprise customers. 

According to the shared press releases, this approach is already being used in the field. Accenture, one of SAP’s partners, worked with the company to overhaul a fragmented, manual billing process that handles nearly a million invoices a year. By using SAP’s Business Technology Platform and generative AI, Accenture created an app that allows account execs to manage invoicing independently, cutting setup times in half and improving billing efficiency by 32%, all while reducing reliance on internal billing experts.

The Bigger Picture: AI as a Differentiator 

However, what SAP is hinting at is a broader industry shift. As enterprises mature in their AI journey, their competitive edge will no longer come from simply using AI but from how well it aligns with their operational needs. Whether it’s last-mile logistics, regulatory compliance, or customer service, AI must adapt to the specific rhythms of each business.

The Takeaway 

It seems like SAP wants to redefine enterprise AI by focusing on co-created, use-case-driven innovation. Instead of chasing trends or layering generic models over complex workflows. As the AI market moves from hype to accountability, this shift toward customer-specific solutions could prove to be a differentiator.