This week's WFM developments is revealing movement toward AI being given more responsibility in understanding the work behind customer interactions in order to automate predictable demand and redeploy people into higher-value roles.
CX leaders are now being challenged to avoid reducing contact volumes or operating costs with decreasing employee count and instead redesign work that fits faster-moving skills requirements and new revenue, retention, and customer expectations.
That places greater pressure on WFM, quality, learning and talent teams to work from a shared view of demand, performance and capability.
The competitive divide will increasingly be between organizations that use automation as a cost-cutting tool and those that use it to build more capable, engaged workforces.
To ensure success this week, leaders should be assessing which interactions benefit from AI or human expertise to evolve roles and whether their data and governance can support this move.
SAP to Acquire TechWolf to Enhance Work Intelligence Strategy
SAP has announced its decision to acquire TechWolf as part of its HR and workforce AI strategy.
Revealing the news during SAP Connect 2026, this "work intelligence" strategy aims to replace job-title-based workforce decisions with a live picture of work, capability and demand.
TechWolf’s platform continuously maps the tasks people perform, the skills they use and possess, and external labour-market signals.
Its context graph for work connects that data to business strategy, giving leaders a more detailed view of how to redesign the workforce.
Manoj Swaminathan, president and chief product officer for SAP Autonomous Suite and member of the Extended Board of SAP SE, argued the platform would provide a grounding layer for WFM-specific AI agents.
“TechWolf’s proprietary context graph for skills and work provides an excellent grounding layer for agent queries regarding work and skills planning and talent management,” he said.
“This grounding layer perfectly matches our strategy. It makes token usage more efficient, lowers the cost of deploying workforce agents and will make Joule more intelligent in AI-driven HR scenarios such as skills-based hiring, workforce planning and role redesign.”
In contact centres, this could help leaders identify the skills behind successful customer interactions to uncover adjacent capabilities for new roles and target management closely.
SAP reportedly plans to use TechWolf to strengthen SuccessFactors and Joule in skills-based hiring, workforce planning and role redesign.
Grounding workforce AI agents in real business context can make recommendations feel more useful and less costly to run.
