SAP Bets Big on Cloud and Prompt Engineering for AI Success

SAP is reorganizing and focusing more on AI to enable quicker delivery and adoption of AI capabilities across all products and lines of business. Cloud deployments are considered superior for achieving AI results due to ease of data access and reduced complexity. Prompt engineering will be an important skill for customizing AI output without needing data scientists.

Summary

  • SAP has formed an end-to-end AI growth area across all lines of business to enable quicker AI delivery and adoption. The AI strategy remains the same.
  • SAP's AI ethics policies already aligned well with the new EU AI Act regulations. HR is treated as a high risk area by SAP also.
  • Out-of-the-box AI with embedded capabilities has the highest user adoption. Requiring extra training or data curation creates barriers.
  • Most of SAP's 24,000+ AI customers are on cloud deployments because AI relies on cloud services and ease of data access. Standardized data aids out-of-the-box use cases.
  • Prompt engineering will be key for customizing AI output to user needs, without requiring data scientists. Skills include SQL, collaborating with business users, optimizing prompts.
  • First retrieval augmented generation (RAG) AI use case launched in SuccessFactors, summarizing SAP documentation in context of the application screens.
  • SAP's foundational model and knowledge graph are still in development. Near term value will come from out-of-the-box AI, prompt engineering, and some RAG use cases.
  • Cloud deployments currently seen as superior for AI, but debates continue on limiting AI access only to RISE customers. User groups advocate making AI available via SAP BTP.
  • Longer conversation needed on customer AI readiness. SAP working on this via university partnerships, reskilling, etc. But success factors like prompt engineering skills need more attention.

READ MORE

Related post

Blockchain

The Critical Role of Prompt Engineering in Blockchain's Future

Prompt engineering plays a crucial role in ensuring the efficiency, security, scalability, and innovation of blockchain networks and applications. It enables projects to deliver features faster, enhance competitiveness, optimize performance, address evolving needs, and drive adoption. Prompt engineering enables agility, adaptability to changing requirements, faster time-to-market, and better user experiences…

AI assistants

GitHub's Request for Prompt Tips Triggers Engineering Debate

The key takeaway is that "prompt engineering" has gone through ups and downs in perception, with many developers poking fun at it, but it still has value if done properly. GitHub's request for tips on prompt engineering sparked jokes about it not being real engineering, but also some legitimate guidance.