I asked ChatGPT to help me think about the big new opportunities for AI to help SAP customers get more value from their software, with key ingredients like faster insights, faster deployments, community, partner ecosystem, and AI for change management.
Here is the list it generated and I added my comment below each one. I’d be interested to hear your opinion!
1. AI-native expert networks and knowledge liquidity
Idea: “expert networks” selected and generated by AI that generate highly relevant information in real time.
- AI is built dynamically expert graphics from internal SAP knowledge, user interactions and external sources (such as LinkedIn, GitHub, SAP blogs).
- Clients get real-time, context-aware knowledge both from internal data (your own historical implementations) and from external experts.
- generated by AI “playbooks” Automatically update based on industry trends, compliance changes, and best practices from top-performing implementations.
My comment: This is a no-brainer and is already underway, e.g. SAP Consulting Capability for Joule – and will inevitably expand and improve over time
2. AI-powered change management as a service
Idea: AI models that predict resistance to change and proactively suggest strategies to increase adoption.
- AI scans Emails, collaboration tools, and SAP usage logs to detect friction points before they increase.
- Simulates the impact of different implementation strategies to determine the best way to introduce new SAP features.
- generated by AI personalized training plans depending on each user’s role, learning preferences, and historical resistance levels.
My comment: I think this is a great underrated opportunity and I already covered it as one of my “great ideas for 2025“
3. Pre-configured industrial cloud powered by AI
Idea: AI automatically brings together industry-specific configurations and process flows for SAP implementations.
- AI scans Company structure, industry trends and best practices. to pre-build optimal configurations.
- AI powered by SAP partner ecosystem to identify the most successful third party plugins for a given industry.
- No more “blank slate” SAP implementations: AI generates a System previously tested and configured at 80%..
My comment: I see this being combined with the 4 below
4. AI for partner-led growth and automated solution discovery
Idea: AI matches SAP partners with customer needs in real time.
- AI analyzes the customer ERP Usage Patterns suggest partner solutions that improve performance.
- AI dynamically partner solution packages in “best practice” packages.
- Customers no longer need to search for add-ons: AI selects the ones the best experience in the partner ecosystem.
My comment: another obvious thing that is already being put into practice. SAP Signavio calls it “Connect and win“, and the concepts are clearly part of the RAISE and GROW methodologies (although there is still much to do)
5. AI-powered standalone ERP optimization (second-order AI)
Idea: AI continuously optimizes SAP workflows without human intervention.
- AI observes user behavior and adjust workflows in real time for efficiency.
- Identify bottlenecks, redundant processes and data inconsistencies before they cause problems.
- predict upcoming failures in the process and proactively suggests solutions.
My comment: I have introduced this notion in the past, calling it “automated automation” or “innovation escalator” which contrasts with today’s painfully manual innovation escalators. I think it’s an extension of the framework in point 4 above. We’re not there yet 🙂
6. Generative AI for enterprise digital twins
Idea: AI creates “digital twins” of entire business processes to simulate different operating scenarios.
- AI automatically maps a company’s SAP configuration in a virtual simulation.
- Companies can test changes (pricing models, supply chain adjustments, workforce changes) before implementing them in real life.
- AI generates “What if” analysis to scale.
My comment: I covered part of this notion many years ago in relation to “total analytics” – the idea of having a system where you are so aware of what is happening that you can use it as an ongoing experimental testbed, where as you make changes you can immediately see what works or doesn’t work, and some of that technology is already available, for example. he What if scenarios in SAP Analytics Cloud?. This would take it a step further.