After attending SAP SuccessFactors’ post-Success Connect Analyst Exchange, one word stayed with me more than autonomous. It was redesign.
There was plenty of AI to discuss. SAP outlined its expanding portfolio of Joule Assistants and agents, its vision for Autonomous HCM, workforce planning capabilities, the planned acquisition of TechWolf and a broader product strategy increasingly organized around business outcomes instead of individual modules. But the larger message was not simply that AI can automate more HR work. It was that organizations now have an opportunity, and almost a requirement, to reconsider how the work itself should be structured.
That difference matters because organizations have spent many years digitizing processes that were designed for a different workforce, a different technology environment and, in many cases, a different business reality. SAP’s framing for Autonomous HCM centers on three connected ideas: automate work to create capacity, redesign work to maximize the potential of a strengthened workforce and reinvent talent to close capability gaps and prepare for what comes next.
I believe the middle of that progression, redesign, may ultimately determine how much value organizations actually realize from the other two.
Automation Is the Beginning, Not the Business Case
SAP’s own Future of Work Research Lab provides some useful context. According to research shared by SAP, 72% of executives believe organizations claiming to transform work with AI are primarily automating existing processes rather than fundamentally redesigning how the work gets done. At the same time, 88% say redesigning work and roles creates significant enterprise value, with HR positioned as the No. 1 owner of that work.
That is an important gap. Automating an inefficient process may make it faster, but it does not necessarily make the process better. The more pressing questions still exist: Which tasks still need to exist? Which decisions should remain human? Where can AI improve speed or consistency? Where does human judgment add value that technology cannot? And if roles change because of that redistribution of work, what capabilities will employees and leaders need next? Those questions move AI from a technology conversation into a workforce and operating-model conversation.
Brandon Hall Group’s HR Outlook 2026 describes this year as the Year of Progression, where AI crosses the threshold from tool to teammate. Our research similarly points to a workplace where AI adoption, skills transformation, workforce planning and human connection can no longer be addressed sequentially. Organizations have to develop those capabilities together. SAP’s Autonomous HCM direction fits squarely into that challenge.
The Real Differentiator May Be Context
The number of AI agents in an HCM environment will continue to grow. That alone will eventually become less interesting. What matters more is what those agents understand.
SAP is positioning Joule Assistants and Joule Work around access to connected workforce data, business processes and enterprise context. Publicly announced assistants cover recruiting, onboarding, payroll, HR operations, learning and career development, among other areas. SAP’s 2H 2026 release describes these not as isolated AI tools but as assistants working across applications and processes to support end-to-end HR work and decision-making.
That is an important distinction. An AI assistant that knows an employee’s skills is useful. An AI environment that can understand those skills alongside business demand, workforce capacity, financial constraints, contingent labor, succession risk and the work that actually needs to get done can support an elevated decision-making level. Context is what turns information into intelligence.
That principle applies well beyond SAP. Organizations increasingly have more workforce data than they know what to do with. The competitive question is becoming whether they can connect those signals quickly enough to make better decisions.
Workforce Planning Is Where the Strategy Gets Very Real
One of the developments that caught my attention most was SAP’s Workforce Planning Assistant. SAP says the capability will bring together workforce, contingent labor and financial data from SAP SuccessFactors, SAP Fieldglass and SAP Cloud ERP to help HR and business leaders forecast workforce needs and evaluate the appropriate combination of hiring, reskilling, redeployment and external talent. SAP News
That is exactly where workforce planning needs to go. From my own experience as a former CFO in healthcare, workforce planning was never an HR-only exercise. A vacancy did not remain a vacancy on an HR report. It could quickly become overtime, agency expense, schedule disruption, manager strain, employee burnout, service risk and eventually another retention problem. Those decisions also rarely had only one solution. Do we hire? Can we develop someone internally? Can we redeploy talent from another area? Do we need temporary labor? Is the underlying job designed correctly? Are we addressing a short-term staffing problem or a longer-term capability gap?
The ability to bring workforce and financial information into the same decision environment can help organizations have a much more mature and relevant conversation about talent investment.
“From a CFO seat, workforce planning was never simply about headcount. A vacancy could become overtime, agency spend, burnout, service risk and another retention problem. The value of AI is not simply predicting the gap. It is helping leaders see the tradeoffs early enough to decide whether to hire, reskill, redeploy or redesign the work before the cost shows up somewhere else.”
— Dr. Marline C. Duroseau, CPA, Managing Director, HR and Leadership Development, Brandon Hall Group™
That is specifically relevant for frontline-intensive industries such as healthcare, hospitality, retail, manufacturing and transportation, where workforce availability can affect business performance almost immediately.
Skills Intelligence Has to Reflect the Work People Actually Do
SAP’s planned acquisition of TechWolf is another development worth watching. The transaction, which remains subject to customary closing conditions and regulatory approval, is intended to bring TechWolf’s work and skills intelligence into the SAP SuccessFactors ecosystem. TechWolf creates a continuously updated view across the work employees perform, the skills they have and use, and external labor-market information.
What interests me here is not simply the acquisition. It is the problem SAP is attempting to solve. Organizations have been talking about becoming skills-based for years, but a skills strategy is only as useful as the information underneath it. Static job descriptions, self-reported profiles or outdated competency libraries cannot by themselves tell leaders how work is changing in real time.
If AI is changing tasks inside jobs, then organizations need a much more dynamic understanding of: What work is actually being performed? Which skills are being applied? Which capabilities are becoming more important? Where can existing employees move? And where does the organization genuinely need to acquire new talent? That intelligence becomes foundational for workforce planning, internal mobility, learning and development, succession and organizational design.
The boundaries among those functions are already becoming less meaningful. Brandon Hall Group’s research similarly points to talent acquisition, talent management, development and workforce planning converging into a more connected talent ecosystem rather than operating as separate HR processes.
Autonomous HCM Still Requires Very Human Leadership
The word autonomous can easily create the impression that people become less important. I believe the opposite is more likely to happen. As technology handles more analysis, administration and coordination, leaders will carry greater responsibility for judgment, governance, interpretation and change. Someone still has to decide whether an AI recommendation makes sense in the context of the business. Someone still has to explain why a role is changing. Someone has to prepare employees for new expectations, determine where reskilling is realistic, address fear and resistance, protect fairness and ensure that efficiency does not become the only definition of success.
Automation can create capacity but it cannot determine what an organization should do with that capacity. That remains leadership work. This is also why organizations should resist measuring autonomous HR mainly by the number of agents deployed or transactions automated. The more meaningful measures will include whether decisions happen faster, whether administrative costs decline, whether managers gain useful capacity, whether hiring and internal movement improve, whether capability gaps close and whether the workforce becomes more adaptable without sacrificing trust.
That is where the ROI conversation becomes much more interesting.
Organizing Around Outcomes Is a Meaningful Shift
Another part of SAP’s message that deserves attention is its movement away from thinking about innovation strictly through individual products or modules. SAP says it is gradually organizing innovation around the customer outcomes organizations are trying to achieve, using connected data, workflows and processes across the SAP portfolio. The company also plans to co-innovate with customers to define, validate and measure the relationship between workforce decisions and business results. SAP News
That direction makes sense because workforce problems rarely care about software boundaries. A retention problem may involve compensation, manager effectiveness, scheduling, development and career mobility. A staffing problem can involve recruiting, contingent labor, workforce planning, finance and learning. Payroll accuracy can involve time, scheduling, employee data, compliance and operations.
Customers do not experience those as modules. They experience them as business problems. The providers that make the next leap in HCM will increasingly need to solve for that reality.
Brandon Hall Group™ Perspective
What I took away from the SAP Success Connect Analyst Exchange was not simply that SAP is introducing more AI into SuccessFactors. The more consequential story is SAP’s attempt to connect workforce intelligence, enterprise data, agentic capability and business processes closely enough that organizations can move from responding to workforce conditions to anticipating and reshaping them.
There is considerable potential in that vision, particularly because SAP operates across HR, finance, ERP and contingent workforce environments. That breadth can provide business context that stand-alone HR intelligence cannot always access. But the technology alone will not create an Autonomous HCM organization. Organizations will still need sound data, clear governance, AI literacy, change capability, leadership judgment and a willingness to redesign work rather than simply automate what already exists. They will also need to prove value through outcomes rather than adoption alone.
That is the test I will continue to watch. Can organizations use this intelligence to make better talent investments? Can they move people before losing them? Can they see capability gaps before they become business constraints? Can they redesign roles intelligently as AI changes the work? Can they connect workforce decisions to measurable operational and financial outcomes? Those are not merely HR technology questions. They are business questions.
And perhaps that is the most important evolution represented by SAP’s Autonomous HCM vision: HR technology is moving closer to the decisions that determine how the business will actually operate next.
