AI Support Is Moving From Reactive To Anticipatory
Support used to wait for calls, tickets, and queues. Then digital platforms made teams more proactive. Now, AI-driven support predicts issues and resolves them instantly at scale. It's as much about new operating models as it is about new tech.
Uptime Under Pressure
Cloud migrations, AI rollouts, and modernization efforts raise the stakes. Downtime costs more than ever, and uninterrupted operations are non-negotiable. SAP's AI-driven support anticipates issues before they surface, keeping critical processes stable during peak demand.
Proof matters. During Cyber Week 2024, SAP Commerce Cloud customers achieved 100% uptime. For 2025's peak events, we again delivered 100% uptime and stronger results: Singles Day reached €7,108.72M GMV (+180.2% YoY) with 6,315.99K orders (+46.4% YoY), and El Buen Fin hit €12,341.70M GMV (+13.18% YoY) with 10,385.74K orders (+32.24% YoY).
Scaling Self-Service With Confidence
Structured knowledge and curated content let us build high-confidence AI and AI agents. Today, over 82% of customer issues are resolved through self-service. Users get instant answers across product use, implementation, and continuous improvement-without waiting on a queue.
Instant Response And Resolution
SAP's Auto Response Agent serves solutions only when confidence is high based on data and knowledge. The first contact resolution rate matches human-to-human interactions. That saves customers time and clears space for engineers to focus on complex cases.
Supportability For SAP Business AI
Making AI real for customers means reliable systems, clear processes, and early-stage support. As AI capabilities roll out across the SAP portfolio, we back deployments with hands-on guidance and tools so teams can scale with confidence.
Example: Incident Solution Matching is integrated with SAP Joule for Consultants. It accelerates support information retrieval and reduces the time spent searching across large documentation sets.
AI That Levels Up Your Engineers
AI removes repetitive work so engineers can apply deeper expertise. With AI-integrated self-service, four out of five issues are resolved instantly. AI recommendations in self-service prevent at least 10% of cases from being created in the first place.
Routing gets smarter: every third case is submitted with an AI-recommended product component for faster processing. Around 10% of engineer responses use AI-assisted language optimization to keep communications clear across a global, multilingual setup. We also apply agentic case resolution, AI-assisted Knowledge Base Article creation, and automatic error categorization to drive accuracy and quality.
As Dr. Benjamin Blau notes, this is "SAP runs SAP" in action. Our multi-agent AI runs on SAP Business Technology Platform with SAP AI Core and a service and support data lake-validating in real-world complexity before it reaches customers and delivering faster resolutions with responsible AI.
Will AI Replace Support Teams?
Short answer: No.
Instant response only triggers when the system is highly confident. No experiments on cases that need expert attention. SAP's 50-year track record and trust from 90% of Fortune 500 companies set the bar for relevant, reliable, and responsible use of AI.
For engineers, AI is about focus. It frees time and energy for high-impact work that needs critical thinking and human judgment. Customers benefit from the blend of machine efficiency and human insight.
Turning Data Into Outcomes
Partnerships matter. SAP works with platforms like Databricks to help developers convert business data and AI into real outcomes. As SAP's CTO Philipp Herzig puts it, AI is reshaping business at every level-but people turn change into progress.
What Support Leaders Can Do Now
- Identify your top 20 repeatable incident drivers. Turn them into searchable, structured knowledge and feed that into your AI.
- Set confidence thresholds and safety checks. Route low-confidence cases to humans by default.
- Instrument proactive signals across logs, telemetry, and commerce events. Rehearse peak scenarios and failovers.
- Track self-service deflection, first contact resolution, and time to mitigation weekly. Share results with product and engineering.
- Equip engineers with AI co-pilots for routing, summarization, and language clarity. Standardize prompts and review loops.
Skill Up Your Team
If you're building AI-augmented support skills by job role, this curated list can help: AI courses by job. Use it to align training with the metrics you care about-deflection, FCR, and faster time to resolution.
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