How SAP Deploys AI Across Enterprise Support Systems
Enterprise software companies traditionally relied on large teams of human support staff to manage complex technical queries, yet this has seen significant disruption from AI-powered automation tools and chatbots.
This means that enterprise software firms are facing mounting pressure to modernise their customer support operations as AI reshapes traditional service models, where businesses demand faster resolution times and 24-hour support coverage, while dealing with increasingly complex software implementations that span multiple departments and geographies.
Against this backdrop, enterprise software provider SAP has implemented AI across its customer support operations, integrating ML models and Gen AI into its core support processes.
The company, which supplies enterprise resource planning software to businesses globally, reports that its AI-enabled support systems handle more than one million customer queries daily, with over 35,000 users accessing these capabilities monthly.
SAP's AI integration marks a shift in knowledge management
SAP’s AI implementation proves the transformation in how enterprise software providers manage customer support, moving beyond traditional knowledge bases to automated systems that can interpret and respond to complex queries.
“SAP has developed more than 50 AI-driven use cases, showcasing the transformative power of AI in customer support.”
"As humans, our role in the economy is evolving as AI systems increasingly replicate human cognitive skills — retrieving and using the right knowledge at the right time," the company says in a statement about the transformation.
Additionally, the system uses robotic process automation and process mining, which analyses business processes through event logs and transaction data, to streamline support operations.
SAP extends AI capabilities across business functions
SAP has integrated AI technology across multiple business areas, including finance, supply chain, procurement, sales, marketing, human resources and IT departments.
- 1 million: daily AI-supported customer queries processed
- 35,000: monthly users of AI support capabilities
- 50+: AI use cases developed for customer support
- 3: key pillars in SAP's AI support strategy (domain-specific models, process insights, and integrated solutions)
- Multiple: business functions covered (finance, supply chain, procurement, sales, marketing, HR, IT)
These implementations enable support teams to allocate resources more efficiently while addressing complex scenarios through AI agents.
For example, the company's Customer Support & Cloud Lifecycle Management division uses AI to analyse system metrics and evaluate efficiency, identifying bottlenecks and opportunities for improvement in customer systems.
SAP customer support division deploys 50 AI use cases
SAP’s customer support division has developed more than 50 specific applications for AI, including automated ticket routing and proactive issue identification systems that detect potential problems before they affect customers.
These implementations include ML models that can categorise errors automatically and cluster support tickets with similar root causes, enabling faster resolution times.
The company's support system now further incorporates Gen AI for tasks including ticket summarisation and knowledge creation, while maintaining human oversight for complex issues requiring specialist intervention.
Additionally, real-time recommendations appear for customers as they type their support requests, alongside proactive suggestions for system health checks and trending content.
Furthermore, process mining tools from SAP Signavio, the company's business process intelligence platform, collect data on system performance and customer interactions to identify areas for improvement.
How SAP's strategy focuses on domain-specific AI models
The company has structured its AI support strategy around three main areas:
- Developing AI models specific to particular business domains
- Gathering process insights through analytics tools
- Integrating AI solutions into existing workflow
This approach enables the company to leverage its historical data and domain expertise to create machine learning models tailored to specific support challenges.
The implementation shows how enterprise software providers approach customer support, combining automated systems with human expertise for complex problem-solving.
Internal workflows have been enhanced through intelligent search capabilities and automated error categorisation systems, while expert teams are assembled automatically for complex issues requiring specialist knowledge.
The company reports that these changes have created efficiency gains for support engineers while improving the speed and quality of customer support responses.
“SAP has developed more than 50 AI-driven use cases, showcasing the transformative power of AI in customer support”, the company says.
"But there is one thing that AI will never replace: the empathy, care and passion of our support teams, ensuring every customer feels supported as we solve their challenges together," the company states.
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