SAP Sapphire 2026: The AI direction is gaining recognition, but execution speed is becoming the key test

Overview

This report is Bernstein's quick take after attending SAP Sapphire and the Financial Analyst Meetings. It notes that AI remained the core theme of this year's conference, but compared with last year, SAP presented a more mature and integrated AI path: it continues to act as an ERP and HCM applications company, while also returning to its role as a platform technology company, pushing enterprise AI adoption through the SAP Business AI Platform, Joule Studio, Business Data Cloud, and the partner ecosystem.

Core views

The central view is 'the direction is right, but execution and speed are crucial.' SAP's strengths lie in deep ERP, HCM, business process data, and semantic knowledge, allowing it to embed AI into real back-office workflows; however, competition in the AI orchestration layer is intense, and hyperscalers have advantages in tooling, scalability, and neutrality. Customers and partners are broadly positive on SAP's AI product suite, but they also want SAP to accelerate delivery, reduce migration costs, and make AI efficiency gains more directly visible in project costs and go-live timelines.

Analysis framework

The report combines conference observations, management commentary, customer and partner interviews, product announcement interpretation, and an valuation framework. The focus is not on adding new financial guidance, but on assessing how SAP's AI roadmap, business model, S/4 migration momentum, BDC open ecosystem, and partner FDE deployment capabilities affect medium-term growth and valuation.

Methodology notes

• Conference feedbackSAP Sapphire and FAM attendee feedback

  Use conference现场 feedback from customers and partners to validate the credibility of the product roadmap.

  The report repeatedly cites feedback from customers, service providers, and hyperscaler partners to assess acceptance of SAP's AI products, migration tools, FDE deployments, and BDC ecosystem.

• Product competition analysisAI orchestration layer competition framework

  One of the key battlegrounds in enterprise software competition in the AI era is the orchestration layer.

  SAP argues that it has a natural advantage in back-end ERP, HCM, and business semantic layers, but the report also warns that hyperscalers are strong competitors in tooling, scale, and platform neutrality.

• Valuation methodP/E multiple method

  Derive target price using forward 12-month EPS estimate, target P/E multiple, and net cash per share.

  For SAP.GR, the report uses one-year-forward 12-month EPS of €9.37, a 29x P/E, and net cash per share of €3.81 to derive a €276 target price; the SAP ADR target price of $323 is based on the SAP.GR target price and EUR/USD conversion.

Asset mapping & comparison

Structured mapping from thesis to named assets (strengths, weaknesses, peers, risks).

• SAP SE

  Core coverage company

  Strengths

  It has deep data and semantic knowledge across ERP, HCM, and back-office workflows, strong momentum in S/4 migration, a more mature AI product line, and positive feedback on its partner ecosystem and FDE investment.

  Weaknesses

  Some customers think the messaging is not impactful enough, some service providers think the AI release pace lags competitors, and migration efficiency gains have not yet fully translated into lower customer project costs.

  Comparison

  Compared with hyperscalers, SAP has a greater right to win in business semantics and back-office workflows; compared with cloud platform vendors, it still needs to strengthen tooling, scale, and neutrality.

  Risks

  S/4HANA adoption slower than expected, SaaS growth below expectations, slow progress in migrating cloud products to hyperscale providers, and margin improvement falling short of expectations.

• Hyperscalers

  AI orchestration layer competitors and partners

  Strengths

  They have advantages in development tools, scalability, platform neutrality, and the customer's AI technology stack.

  Weaknesses

  They lack SAP's native depth in ERP, HCM, and enterprise back-office workflow semantics.

  Comparison

  The report sees the AI orchestration layer as a highly competitive battleground, and customers may use both SAP AI and hyperscaler AI tools.

  Risks

  If hyperscalers dominate enterprise AI orchestration, SAP's AI platform monetization opportunity could be compressed.

• Databricks, Snowflake, Google BigQuery, Microsoft Fabric, AWS

  Business Data Cloud ecosystem and data-layer connection targets

  Strengths

  BDC connect supports linking SAP and non-SAP data in a unified semantic layer, helping the open ecosystem and enterprise AI agents understand cross-system data.

  Weaknesses

  The open ecosystem requires sustained execution and partner integration, and actual customer adoption still needs to be monitored.

  Comparison

  Compared with last year, SAP is placing greater emphasis on openness at the data layer, with connections already established to Databricks and Snowflake and planned expansion to Google BigQuery, Microsoft Fabric, and AWS.

  Risks

  If open connectivity and the unified semantic layer advance slowly, the value of BDC for AI agents and customer data strategy may be lower than expected.

• Anthropic

  SAP AI partner

  Strengths

  Service providers consistently view SAP's partnership with Anthropic positively and believe it will help accelerate customer AI deployment.

  Weaknesses

  The report does not provide specific data on commercial contribution or revenue impact.

  Comparison

  The partnership is seen as an important external capability that helps SAP accelerate AI adoption.

  Risks

  The effectiveness of the partnership depends on whether SAP can embed the model capabilities effectively into Joule and customer workflows.

Key data

• Rating and target priceOutperform; SAP.GR target price €276; SAP ADR target price $323The report believes the market's negative price reaction after the conference is not justified.
• SAP AI agents and assistants scale200+ AI agents; 50+ AI assistantsUsed to support SAP Autonomous Enterprise Suite, covering Finance, SCM, Spend, HCM, and CX.
• Joule for Consultants usage13-14k daily usage; average savings of 1.5 hours per dayThe report says this tool helps improve efficiency in migration and scalability projects.
• SMB revenue shareAbout 30%SAP is mainly targeting upper-end SMB customers with annual revenue from $250m to $1bn.
• Cloud revenue seat dependencyLess than 30% of cloud revenue is seat-based; about two-thirds of cloud revenue is already unrelated to seatsManagement used this information to respond to market concerns about the seat-based software model.
• Migration efficiency improvementEfficiency improves by more than 30% after migration is completedPartner feedback suggests that the primary driver for S/4 migration remains operational efficiency rather than AI as a standalone catalyst.
• AI release pace debateSome service providers believe SAP is 3 to 6 months behind competitorsJoule Studio 2.0 is addressing gaps in development tools and openness, but more feedback is still needed to validate the improvement.

Impact & implications

For investors, the implication is that SAP's AI strategy is moving from vision toward more concrete products, a data layer, and a business model. If Joule Studio 2.0, BDC, the Anthropic partnership, and the FDE framework can be translated into customer production deployments, this should help strengthen the cloud migration, AI monetization, and long-term growth story. But if delivery lags, migration cost improvement remains insufficient, or the AI orchestration layer becomes dominated by hyperscalers, the market may continue to question SAP's ability to deliver on its AI premium.

Risks

• S/4HANA adoption is slower than expected.
• Upselling additional modules and SaaS solutions to existing customers is below expectations.
• SAP SaaS product growth is below expectations.
• Adoption of the SaaS version of S/4HANA is below expectations.
• Migration of SAP cloud products to hyperscale providers is slower than expected.
• SAP encounters issues in driving margin improvement.
• Competition in the AI orchestration layer is intense, and hyperscalers may become more attractive on tooling, scale, and neutrality.
• If efficiency gains from AI tools do not translate into visible cost and cycle-time reductions for customers, adoption momentum could weaken.

What to watch

• Customer and partner feedback after Joule Studio 2.0 launches in June.
• The pace at which 200+ agents and 50+ assistants in SAP Business AI Platform move from demo to production environments.
• Actual adoption of Business Data Cloud with Databricks, Snowflake, Google BigQuery, Microsoft Fabric, and AWS.
• Whether the FDE framework and large service partners can help customers launch AI projects faster.
• Whether the Anthropic partnership clearly accelerates SAP AI deployments on the customer side.
• Whether AI and migration tools can materially reduce S/4 migration cost and time.
• Whether consumption-based, outcome-based, and value-based pricing models can expand AI monetization and ease market concerns about seat-based revenue.
• Whether CCB remains the most relevant cloud business metric after consumption-based and outcome-based revenue rises.