The AI inflection point in HR: what CHROs must do now

According to the Gartner report, The Impact of AI on the HR Operating Model, by 2030, 50% of current HR activities will be AI-automated or performed by AI agents, fundamentally transforming HR’s work, roles, and workflow That is not a distant forecast. It sits within most CHROs' current tenure.

What makes this moment distinct is not the technology itself. It is the convergence of deployment speed, organisational expectation, and regulatory pressure. Agentic AI, the ability for software to perceive, decide and act without constant human instruction, is moving from pilot to production faster than most HR functions have built the foundations to absorb it. In many organisations, HR leaders now report being in advanced stages of implementing generative AI and are planning to deploy agentic capabilities over the coming year.

The gap between deploying AI and realising value from it remains significant. We feel the Gartner research indicates that only a minority of CHROs currently report significant or transformational returns from AI investments. In practice, most organisations are deploying AI on top of existing operating models rather than redesigning the model around AI. That is the crux of what follows.

The operating model is the lever, not the technology

Research on AI productivity outcomes makes the point clearly. Adapting the operating model to AI delivers much higher impact on productivity gains than AI knowledge sharing, literacy programmes or the presence of AI skills in isolation. The technology is necessary but not sufficient.

For CHROs, the real work is not in selecting tools or running pilots. It is in rethinking how HR creates value, how it organises work and where human judgement remains non negotiable.

The transformation touches three pillars of the HR function: operations, business partnering and centres of excellence. Each is affected in a meaningfully different way.

Three pillars of the HR operating model

HR operations: from service delivery to digital solutions

HR operations has historically carried the heaviest administrative load in the function: payroll, case management, employee queries and compliance administration. It is also where AI agents will have the most immediate and consequential impact.

Tier 0 and tier 1 support, the layer handling standard queries, self service requests, policy look ups and routine approvals, is well suited to AI agent capabilities. These agents can interact with employees through familiar channels such as Teams, Slack or mobile apps, surface the right policy, update the relevant system and close the case without human intervention. The gains in resolution speed, availability and consistency are tangible.

The deeper shift, however, is structural. As AI absorbs routine support, shared services as currently organised, typically built around country or region-specific hubs, will become more centralised and standardised. Some organisations will fold shared services into a global business services model alongside finance and IT. Others will outsource to managed service providers. For European businesses, both paths must be evaluated against the compliance obligations of the EU AI Act and GDPR, which introduce transparency, accountability and human oversight requirements that cannot be treated as an afterthought.

What remains in HR operations, and grows in strategic importance, is the function's role in enabling the technology itself. Data quality, process standardisation, system integration and the development of the team to manage AI prompt design, product delivery and scenario planning all move to the centre of the agenda.

The organisations Zalaris has worked with over the past 25 years that achieve the most from operational transformation share a consistent starting point. They invest in clean data and process discipline before the technology arrives, not after.

When Ryanair partnered with Zalaris to consolidate payroll across ten countries onto a single SAP SuccessFactors platform, the programme required significant data alignment work before any automation could deliver on its promise. The result was meaningful. Headcount reports that once demanded days of manual effort now generate in seconds, monthly reporting cycles became daily and annual pension renewals were cut from six to eight weeks to minutes. None of that was enabled by the technology alone. The rigour that preceded it made the difference.

The same principle applies to AI readiness.

The HRBP role: from relationship maintenance to strategic counsel

Of the three pillars, the HR business partner role is often considered less exposed to AI displacement. HRBPs build relationships, navigate organisational dynamics and bring human judgement to complex talent decisions. That assessment is broadly right, but it understates how significantly the role will need to evolve.

Today, many HRBPs spend a disproportionate share of their time on work that AI performs more efficiently: summarising survey data, drafting communications, preparing management briefings and tracking performance patterns. As AI takes on that layer, two things happen. HRBPs gain capacity for deeper strategic work. At the same time, AI agents gradually become the first point of contact for lower complexity management queries: the routine nudges, performance check ins and onboarding reminders that currently consume HRBP time.

As AI takes on more routine tasks the typical HRBP to employee span of control is expected to increase. In practical terms, that means individual HRBPs are likely to support significantly larger segments of the workforce than they do today, with a much higher proportion of their time devoted to genuinely complex issues.

HRBP span of control shift

The structural implication is significant. Rather than being permanently aligned to specific business units or geographies, many HRBPs will operate in dynamic pools, deployed flexibly based on where strategic talent challenges are most acute, supported by real time AI generated insight. Senior executives will continue working with individually aligned partners. The difference is that those partners will spend the majority of their time on genuinely difficult questions, not on information gathering.

The capability shift required is substantial. Analytical fluency, business acumen and the ability to apply critical judgement to AI generated insight will define the effective HRBP of the next decade. Organisations that treat this as a retraining problem rather than a redesign problem will systematically under invest in the structural changes needed to realise the value.

Centres of excellence: from process management to HR product design

The transformation of centres of excellence is perhaps the least visible of the three, but it is among the most strategically significant.

COEs have traditionally operated as functional specialists: talent acquisition, learning and development, total rewards and performance management. AI does not eliminate that specialisation. It changes what the specialisation produces.

With access to more timely and granular employee data, COEs can move from designing standardised programmes to building more personalised HR products: adaptive onboarding journeys, tailored learning paths, targeted career recommendations and more relevant wellbeing interventions. AI enables the analysis and the personalisation. The COE provides the design intelligence and the judgement about which human moments must remain human: a first conversation with a new hire, a difficult performance discussion, support through a significant life event.

As routine tasks are automated and headcount requirements in some COE areas decline, the remaining teams will increasingly operate across horizontal value streams rather than within functional silos. Projects will be reprioritised continuously based on business and talent impact, with cross functional teams combining HR product managers, delivery specialists and business representatives.

This requires a different kind of COE professional. They need to think in products, manage stakeholders across functions and articulate the business value of each HR initiative with the discipline of a product owner.

What AI readiness looks like in practice

Across its work with organisations in financial services, energy, manufacturing and the public sector, Zalaris has observed that the most successful HR transformations follow a consistent sequence.

Clean, consistent people data is the foundation. Without it, AI outputs are unreliable and adoption stalls. Scalable, integrated technology infrastructure follows. Processes that are standardised and simplified before automation begins, rather than merely automated as they exist, create the conditions for genuine efficiency gains.

Danske Bank's programme to move from fragmented, country specific payroll systems to a unified cloud based HR and payroll model across the Nordics illustrates this well. The transformation required Zalaris to act as a single strategic partner across jurisdictions, standardising processes and governance before any automation layer could be reliably built on top. Today, the bank operates from a shared data foundation, a modern mobile ready employee experience and a consistent compliance posture across geographies. Those are the conditions that make AI augmentation viable rather than precarious.

AI readiness is not a binary state. It is a maturity journey. CHROs who wait for perfect conditions before beginning will find the pace of change has already moved on.

A note on the European context

HR transformation in Europe carries obligations that add complexity to the AI agenda without diminishing its urgency. The EU AI Act classifies a number of HR applications, including certain recruitment and performance management tools, as high risk. These require documented impact assessments, human oversight mechanisms and audit trails. GDPR continues to govern how employee data is collected, processed and retained, with direct implications for the data architectures that AI depends on.

These are not obstacles to transformation. They are design constraints. Addressed early, they build the trust and governance foundations that make sustainable AI adoption possible. Organisations that treat compliance as an afterthought tend to retrofit it at significant cost. Those that design for it from the outset move faster and more durably in the long run.

The way forward for AI in HR Operations

The direction of travel is not in question. AI will reshape how HR operations function, how business partners are deployed and how centres of excellence create value. The organisations that lead this transformation will be those that treat it as a structural redesign rather than a technology rollout, and that build the foundations of data quality, process discipline and human capability before asking AI to carry the load.

Zalaris has spent over 25 years helping organisations across Europe and beyond build HR and payroll operations that are efficient, compliant and future-ready. We understand the complexity of multi-country environments, the demands of regulatory compliance and the human dimensions of large-scale change. That experience is what we bring to every engagement.

This Gartner® research guides CHROs on rethinking HR’s work, roles and ways of working in an AI-driven environment. You can download it below.

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Gartner, The Impact of AI on the HR Operating Model, By Hanne Nieberg, 26 February 2026.