SAP Sapphire 2025 – Gigaom

I have just returned from the SAP Sapphire 2025 in Orlando, and while drawing a compelling vision of an AI -supported future, I couldn’t think of the gap between bright new announcements and most SAP customers today. Let me cut the marketing hype and give you an analyst perspective of what really matters.

Cloud migration in the room elephant

The biggest challenge of SAP is not to create cool AI properties-the majority of the sequence base still manages in-house ERP systems. While SAP was busy exhibiting AI Foundation and its advanced Joule capabilities, I still continued to think about thousands of companies in SAP ECC 6.0 or older versions, some of them have not been updated over the years.

Here is Reality Control: Almost every exciting AI announcement in Sapphire requires cloud solutions of SAP. AI Foundation? Cloud -based. Advanced joule with proactive properties? It needs cloud infrastructure. New Business Data Cloud Intelligence offers? You guessed – just cloud.

For the average SAP shop that runs in -house systems, these announcements may also be science fiction. They deal with basic integration challenges, struggle with old user interfaces, and fight to get reliable reports from their existing systems. The idea of ​​managing the supply chains of AI agents autonomously seems ridiculous.

AI: Useful vehicle is not a magic wand

Don’t get me wrong – the AI ​​skills of SAP are really impressive. Joule’s ability to predict user needs and provide contextual information can really increase productivity. However, let’s pump the brakes on SAP’s claim that ıcı productivity up to 30% ”.

I have been analyzing corporate software applications for years, and productivity gains of this size come not only from adding AI to the existing inefficiency, but often from process improvements and workflow optimization. If your supply process is broken, a AI does not correct the AI ​​- it only automates the fracture process more quickly.

More realistic gains will come from these:

• Reduce the time spent to search for information in multiple systems
• Automating routine data analysis and report production
• Providing better decision support through the predictive analytical
• Facilitating recurrent tasks in finance, HR and supply chain operations

These are valuable developments, but not evolutionary, but not revolutionary.

Partnership Strategy: Protecting Betting

SAP’s partnerships tell an interesting story. The Accenture Advance Program acknowledges that many middle market companies need to hold an important hand to modernize their SAP environments. Palantir integration, SAP’s data analysis, claims that everything can happen for everyone in the field. Surprise cooperation admits that their artificial intelligence needs external sources of data to be really useful.

These partnerships are smart business movements, but they also emphasize the dependencies of SAP. If you plan a handle conversion, you just don’t buy SAP, but you also buy a common and integration ecosystem that adds complexity and cost.

What does this mean for your SAP strategy?

If you are currently working in SAP, Sapphire 2025 should strengthen a key message: the innovation train leaves the station and goes to the cloud. However, before panic to miss the AI ​​skills, take these pragmatic steps into consideration:

For in -company SAP customers:

• First check your current status. Most of the companies I work with do not maximize existing SAP capabilities without preparing AI improvements.
• Plan your cloud carrying timeline. SAP has no 2030 supported date for old systems. Use this as your forcing function.
• Focus on data quality. AI is just as good as the data it works. If your main data is a mess, AI does not help.
• Start small with cloud integration. Think of hybrid approaches that connect your in -house kernel to cloud -based analytical and AI tools.

Already for companies in SAP Cloud:

• Evaluate which AI features are not the theoretical future use, but the business problems you have experienced today.
• Pilot before the scaling. Efficiency claims are great, but test them in your environment with your data.
• Invest in change management. The biggest obstacle of adopting artificial intelligence is not technique – to make people change the way they work.

Conclusion: Evolution, Not Revolution

SAP Sapphire 2025 has exhibited legitimate innovations to improve the functioning of businesses, but let’s keep the expectations realistic. The companies that will benefit the most of these AI capabilities are companies that have already modernized their SAP infrastructure and cleanses business processes.

The majority of SAP customers are still not in Legacy Systems, the real question is whether AI will transform their work – they will not be able to carry out a successful modernization program that positions them to take advantage of these capabilities.

Your next steps

I recommend you to do this week:

• Evaluate where you stand on your SAP modernization journey. Are you ready for the cloud or do you have technical debt for years to deal with it?
• Map your business cases for AI skills that attract your attention. Can you measure the value they offer in your private environment?
• Create a realistic road map that accepts both the exciting possibilities and practical restrictions of your existing handle views.
• Start talking to your leadership about the long -term handle strategy. The decisions you make in the next two years will benefit from the AI ​​Revolution or determine whether you have left behind with old systems.

AI Future SAP finally promises the future, but for most companies, the road is going through cloud transition, data management and process optimization. First, focus on creating this basis and will follow the AI ​​skills when you are ready to use them effectively.