TLDR: Workday and SAP SuccessFactors now ship artificial intelligence agents across the employee lifecycle, and the teams that see returns first automate low-risk, high-volume employee questions before they touch candidate ranking.
Both suites moved from writing assistants to working agents in under three years
The first wave of artificial intelligence (AI) inside the two dominant human capital management (HCM) suites, the systems that human resources (HR) teams run on, was a writing aid. In September 2023, Workday announced generative AI that would let hiring managers and recruiters generate job descriptions in minutes versus hours, alongside knowledge articles and employee growth plans. A week later, SAP presented AI-assisted job descriptions for SAP SuccessFactors and a talent intelligence hub that creates a skills portfolio for each employee, inferred from data such as performance feedback. Both features drafted text for a human to approve.
The second wave, which arrived through 2025 and 2026, executes tasks. In February 2025, Workday unveiled an Agent System of Record to onboard AI agents with defined roles, skills and access rights, budget their cost, and enforce policy, together with a Policy Agent that reads a company’s latest policies and answers employees and managers directly. In October 2025, SAP announced a set of Joule agents for SAP SuccessFactors, among them a Performance and Goals Agent, an HR Service Agent, a Payroll Agent that explains pay by linking payslip lines to time data, and a People Intelligence Agent that lets managers ask workforce questions in their own words.
By the summer of 2026 those agents had reached production scale. Workday told investors on 27 August 2026 that more than 5,500 customers now use at least one of its organic agents, up more than 35% on the previous quarter, and that AI drives more than a quarter of its new annual contract value. As of September 2026, Workday Rising, the vendor’s annual customer conference, is set for 12 to 15 October 2026 under the banner of agentic HR. The product question for HR leaders has shifted from whether the suite can do it to which process should go first.
| Date | Vendor | What shipped or was announced |
|---|---|---|
| Sep 2023 | Workday | Generative job descriptions, knowledge articles, growth plans |
| Oct 2023 | SAP | AI-assisted job descriptions; talent intelligence hub skills portfolios |
| Feb 2025 | Workday | Agent System of Record; Policy Agent |
| Sep 2025 | SAP | SmartRecruiters acquisition completed |
| Oct 2025 | Workday | Paradox acquisition completed (candidate experience agent) |
| Oct 2025 | SAP | Joule agents: performance, HR service, payroll, people intelligence |
| Mar 2026 | Workday | Sana and the Sana Self-Service Agent (300+ skills) |
| Apr 2026 | SAP | First-half 2026 release: agent network, skills governance, SmartRecruiters integration |
| Jun 2026 | Workday | Agent Passport for agent testing and monitoring (early access, second half of 2026) |
| Jul 2026 | Workday | Workday Learning, powered by Sana, generally available |
Employee self-service is the first process HR teams hand to an agent
Self-service questions are the obvious starting point because they are frequent, repetitive and answerable from data the suite already holds. Workday’s March 2026 launch of Sana describes a Self-Service Agent with more than 300 skills across pay, time and absence, available to all Workday customers through Workday Flex Credits. Its example request, “Update my home address and show how this affects my tax forms and benefits”, shows the shift: the agent answers and then completes the transaction. In May 2026 Workday took the same agent into Microsoft 365 Copilot, where employees can check a vacation balance and request time off in natural language, while every request involving Workday data runs inside Workday under the organisation’s existing approvals and business rules.
SAP’s equivalent is the HR Service Agent, which SAP describes as a direct point of contact for routine employee questions, and the Payroll Agent, which handles the “explain my pay” conversation that fills HR inboxes after every overtime month. Both were scheduled for the first half of 2026 and sit inside what SAP’s first-half 2026 release calls a connected network of AI agents supporting recruiting, workforce administration and payroll.
The governance load of this first step is also the lightest. The European Union (EU) AI Act places stand-alone employment systems in its high-risk category, but the European Commission’s draft guidelines on the classification of high-risk AI systems, published on 19 May 2026 and summarised by Faegre Drinker in June 2026, list interview-scheduling assistants, attendance compilers and writing assistants as outside the high-risk scope. A policy and pay answer engine sits much closer to those examples than to a candidate-ranking tool, and its main obligation is transparency: employees must know they are talking to an AI system. Answer quality depends on policy content: an agent that reads policy documents answers with whatever the documents say, so outdated leave rules or conflicting cantonal annexes surface instantly as wrong answers.
Switzerland adds a language test that vendor demos rarely show. An employer with sites in Basel, Lausanne and Ticino often keeps the same leave or expense policy in German, French, Italian and English, and the versions drift apart over time. In Edward Galle’s view, the practical pilot design is to pick one employee population and one language, load only the controlled version of each policy, and sample a fixed number of agent answers every week against the source text. The pilot then produces two measures that HR leaders can defend in front of a works council or an auditor: the share of answers that match the controlled policy, and the share of questions the agent escalated to a person. Both measures come from the organisation’s own logs, which makes them stronger evidence for the next investment decision than any vendor benchmark.
Job descriptions and learning content go second because a human still signs every output
Job description generation, the second step, has been in both suites since 2023, and the risk profile is manageable because a recruiter or hiring manager approves each text before it is published. The Commission’s draft examples treat an inclusive-language checker for job adverts as outside the high-risk category, which signals where drafting support sits. For Swiss employers in pharmaceuticals and medical technology (MedTech), the main value lies in consistency: a governed template that carries the correct good manufacturing practice (GMP) responsibilities, the language requirements and the reporting line into every requisition.
Workday Learning, powered by Sana, applies the same human-sign-off logic to training content: it became generally available in July 2026 and converts uploaded documents and slide decks into structured, interactive courses in minutes, with customer-reported reductions of up to 98% in content creation time. SAP’s first-half 2026 release adds intelligent question-and-answer inside SAP SuccessFactors Learning, drawn from an organisation’s own learning content. In a regulated company, both features meet a validation question early: a standard operating procedure (SOP) course that an AI rewrote still has to match the controlled SOP version, so quality assurance belongs in the review loop from the first pilot.
Skills inventories are the hinge, and their data quality decides every later use case
Skills data connects everything the suites promise next: internal mobility, succession, learning recommendations and candidate matching. SAP’s April 2026 release adds skills governance to the talent intelligence hub, a central interface to manage skills, apply governance standards and keep skills data consistent across SAP SuccessFactors and partner applications. Workday positions its learning paths on the same foundation, recommending courses from each employee’s role, skills, organisation and location.
Inferred skills are powerful and legally sensitive in Switzerland. Article 328b of the Swiss Code of Obligations (CO) allows an employer to process employee data only to the extent that it concerns the employee’s suitability for the job or is necessary for the employment contract. A skills profile built from performance feedback, project history and learning records generally fits that purpose; a profile enriched with signals from outside the job requires a sharper justification. The Federal Data Protection and Information Commissioner (FDPIC) has stated since 2023, updated in May 2025, that the Federal Act on Data Protection (FADP) applies directly to AI, and that users must make the purpose, functionality and data sources of AI-based processing transparent, with a data protection impact assessment in high-risk cases. A skills inventory that employees can see and correct satisfies both rules and improves the data at the same time.
In pharmaceutical and MedTech companies, part of that skills data is also a quality record. Training on standard operating procedures, qualification for a cleanroom role and sign-off authority for a batch decision sit in the learning system and serve as evidence of competence during an inspection. Edward Galle’s view is that these qualification records belong in their own validated layer, separate from inferred skills: the agent recommends a course, and the validated learning record stays the single source for who is qualified to do what. Keeping the two layers apart lets HR experiment with skills inference while the quality unit keeps a record it can defend in front of an inspector.
Candidate matching belongs last, behind human review and documented testing
Recruiting attracts the largest vendor investment. SAP completed its acquisition of SmartRecruiters in September 2025, promising AI-enabled recruiting capabilities that result in faster time-to-hire, and its first-half 2026 release connects SmartRecruiters natively with Employee Central and Onboarding. Workday completed its purchase of Paradox on 1 October 2025, a candidate experience agent that uses conversational AI for high-volume and frontline hiring, with self-scheduling and interview coordination.
Ranking and shortlisting carry the heaviest obligations, which is why mature HR teams sequence them last. The Commission’s draft guidelines of 19 May 2026 name an automated job-matching and ranking tool that scores and shortlists candidates as a likely high-risk system. The Digital Omnibus moves these duties to 2 December 2027 (see European Union Artificial Intelligence Rules for Hiring Software Reach Swiss Employers Recruiting in Europe). Swiss law adds its own control: under Article 21 FADP, a candidate subject to a decision based exclusively on automated processing may request that the decision be reviewed by a natural person.
Litigation in the United States shows what an untested screening layer costs. In May 2025, a federal court in California granted preliminary certification of a nationwide age-discrimination collective action in Mobley v. Workday, covering applicants aged 40 and over; Workday disputes the claims. Workday’s answer is Agent Passport, announced in June 2026 for early access in the second half of the year, which tests each agent for prompt injection, data leaks and unsafe outputs against public standards such as the AI Risk Management Framework of the National Institute of Standards and Technology (NIST) in the United States, then monitors it in production.
In Edward Galle’s view, a Swiss pharma or MedTech employer that pilots candidate matching can publish the review route before the tool goes live. The candidate privacy notice names the Article 21 FADP right, gives one contact address for a review request and states who owns the review, typically a talent acquisition lead with the data protection officer as the escalation point. That owner keeps a short log of each request and its outcome, which gives the employer evidence of human oversight for any EU file and a clear answer when an applicant asks how a shortlist decision was made.
| Order | HR process | Main control |
|---|---|---|
| 1 | Self-service: policy, pay, absence answers | AI disclosure; policy content clean-up |
| 2 | Job descriptions and learning content | Human approval; SOP version check |
| 3 | Skills inventory and mobility | Art. 328b CO purpose test; employee correction |
| 4 | Candidate matching and shortlisting | High-risk file; bias testing; Art. 21 FADP human review |
The agent era creates HR roles that sit between the HR information system, the data and the law
The World Economic Forum’s Future of Jobs Report 2025 found that AI and big data top the list of fastest-growing skills, and that two-thirds of employers plan to hire talent with specific AI skills. Inside HR, that demand concentrates on four profiles that combine suite knowledge, data and regulation.
The HR information systems (HRIS) agent owner configures agents in Workday or SAP SuccessFactors, sets their roles and access rights, and reviews every half-yearly release for new agent behaviour. The people analytics lead with AI turns natural-language workforce questions into trusted answers, which requires clean definitions of headcount, attrition and cost before a People Intelligence Agent can answer with authority. The HR knowledge and content owner curates the policies and SOP-linked training that agents read, a job that resembles document control in quality assurance. The HR AI governance specialist maintains the inventory of agents, the impact assessments under the FADP, the high-risk documentation for EU operations and the human-review route for Article 21 requests.
In Edward Galle’s search work, few of these profiles exist on the open market at scale, because the combination of suite configuration, data literacy and Swiss labour law is rare. Many employers build them from inside: an HRIS analyst who learns governance, or a compliance specialist who learns the suite. Guidance on AI recruiting in regulated industries and on building a compliant hiring process covers the recruiting side of the same discipline.
For employers hiring into these roles, Edward Galle recommends screening on evidence that maps to the four-step sequence in Exhibit 2. An HRIS agent owner can walk through a vendor release note and explain which agent behaviour changed and how it was tested. A people analytics lead can show a metric definition document and the reconciliation behind one headcount figure. A content owner can describe how a policy moves from draft to controlled version. A governance specialist can show an agent inventory or an impact assessment, anonymised where needed. Candidates who bring one of these artefacts to an interview demonstrate the exact work the agent era creates.
Swiss HR teams that govern one process this quarter reach candidate matching in 2027 on solid ground
For HR leaders, the first decision is scope: switch on self-service and policy agents for one population, measure ticket volume and answer accuracy for a quarter, and clean the policy library before expanding. For HRIS and people analytics teams, the priority is the skills model and the data definitions, because every later agent inherits their quality. For legal and data protection officers, the task is an agent register that maps each use case to Article 328b CO, the FADP and, for EU entities, the AI Act timeline. Candidate ranking can then arrive in 2027 on a governed foundation and a documented pilot.
Edward Galle’s HR consulting and workforce systems (HR IS) team supports HR teams, alongside specialist search for HRIS, people analytics and brand-tech profiles. Professionals building a career at this intersection can submit a curriculum vitae (CV) ou browse current openings, and readers new to the topic can start with the guide to AI in hiring for candidates and HR leaders.
This article has been reviewed by Haider Alleg, Managing Partner at Kainjoo SA.
References
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