As AI continues to reshape how work is performed across industries and functions, the role of the CHRO is undergoing one of the most significant transformations in decades. No longer just the steward of human capital, CHROs are fast becoming the architect of a hybrid workforce. This shift increases both the scope and complexity of the role, as CHROs must shape a workforce that integrates people with AI agents while advancing enterprise-wide capability building, organizational redesign, and cultural evolution.
To successfully drive this shift, today’s CHROs will address AI’s role in the organization on two fronts: looking for opportunities where the technology can make a difference and reorganizing the HR function to support those opportunities, as well as taking a leading role in the broader enterprise transformation.
The Implications of AI on the HR Function
The Opportunity for HR. HR organizations are leveraging AI to break the historical compromise between efficiency and experience, enabling new solutions and workflows to deliver across the three facets of value from AI: productivity, engagement, and quality. We’ve seen that early adopters tend to start with solutions in recruiting and sourcing, learning and development, people analytics, and HR administration. These areas share common, AI-friendly characteristics: abundant, often text-based data; highly repeatable and rules-driven processes; and clear and measurable KPIs. Introducing AI in these domains has offered fast, low-risk opportunities to automate work and improve the employee experience.
With data from our Built for the Future study, we see that the top workflows HR teams are addressing are automating HR service desks, precision recruiting and talent matching, personalized learning and career paths, and payroll processing and anomaly detection. Companies are seeing 20% to 30% efficiency gains across these opportunities, with a similar degree of improvement in the employee experience.
Besides the obvious areas, many teams are developing solutions across other components of the HR value chain and employee life cycle. Consider a company that deployed a GPT-based tool to automate manager performance reviews. Within months, managers cut review-writing time by 45%, review quality improved by 22%, and 90% of users reported a better experience—all without overhauling legacy systems. Broader data confirms similar gains across organizations that pair strong HR leadership with targeted AI investment.
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Reorganizing HR for an AI-Driven Future. Traditional HR structures, including siloed teams, transactional service centers, and broad HR business partners are not suited to accommodate such changes. Current ways of working are not agile enough for an environment where AI is transforming how work is done.
The new model relies on adaptive, multidisciplinary teams with end-to-end accountability for designing and delivering optimal employee experiences. The role of HR business partners will become more strategic as AI takes routine administrative work off their plates. The focus is shifting from processes efficiency to business outcomes, with greater emphasis on work design, data analytics, workforce and skill planning, and change management. Teams will need upskilling, and perhaps new roles, to meet the needs of the future HR organization.
The role of HR business partners is becoming more strategic as focus shifts from processes efficiency to business outcomes.
A Two-Speed Agenda for HR. Meeting an expanded mandate requires CHROs to lead their own transformations on two parallel fronts:
- Speed 1: Strengthening the Fundamentals. This includes future-proofing core HR systems, ensuring data is trustworthy, processes are consistent, and employees receive a reliable and seamless experience. Many HR organizations still rely on manual workarounds, fragmented technology stacks, and uneven service delivery. Without redesigning these basics, AI-driven reinvention will stall before it starts.
- Speed 2: Embracing a Forward-Looking Ambition. This includes redesigning HR roles and operating models for an AI-first environment, embedding agents into workflows, and shaping the culture, governance, and skills required to support responsible enterprise-wide AI adoption.
To support innovation while strenghtening the fundamentals, organizations can consider returning to the concept of “skunkworks” teams—cross-functional groups with dedicated resources to quickly test and implement new ideas. These teams can explore emerging technologies, design solutions with end users, run rapid experiments, and champion the changes through a community of practice.
Managing these two agendas in parallel is imperative. AI disruption is redefining talent strategies, organizational architectures, and leadership expectations at unprecedented pace and ubiquitous scale. A recent study conducted by MIT Sloan Management Review and BCG revealed that 66% of AI agentic leaders expect a redefinition of roles and responsibilities, 58% anticipate changes to governance and decision-making rights, and 45% expect to see a reduction in middle management layers. HR must build the muscle to deliver near-term reliability while advancing long-term transformation.
All of this means that HR’s own AI adoption journey is only the starting point. The technology is revealing deeper organizational challenges across the enterprise that determine whether companies capture value at scale—and these are challenges HR is best positioned to solve.
HR Supporting AI Transformation Across the Enterprise
HR’s Critical Role in Enterprise-Wide AI Transformation: Activating the 70%. Although many organizations are actively investing in AI, the greatest barriers to realizing value are not technological. The most common AI roadblocks—lack of knowledge and skills, tech adoption and daily AI usage, shortage of AI talent, and cross-functional collaboration barriers—are organizational and fall squarely within HR’s domain. BCG’s rule of thumb (supported by extensive experience in this space) is that only 10% of AI value creation comes from algorithms and 20% from the technology and data infrastructure, while 70% comes from meaningful transformation of people, organization, and processes. Of the 10/20/70 model, understanding and galvanizing the 70% is where companies really unlock the value of AI.
The most common AI roadblocks are organizational and fall squarely within HR's domain.
HR’s Role in AI-Driven Organizational Change. Tasks, talent, and teams evolve as organizations progress through AI maturity. Early on, individuals use AI to speed up existing tasks without fundamentally changing workflows or roles. As organizations mature, AI becomes embedded in team processes, shifting work from manual execution to hybrid human-AI co-creation and requiring new skills in data, oversight, and system collaboration. At the highest level of maturity, AI agents orchestrate end-to-end workflows, taking on full tasks while humans supervise, set strategy, and manage exceptions. Correspondingly, roles evolve, some are phased out, and organizational structures flatten as the hybrid teams emerge.
Forward-thinking companies are already proactively reimagining how work gets done. Some are changing traditional assumptions, defaulting to AI for work unless there is a uniquely compelling reason to hire a human. Others are merging technology and HR departments to design truly integrated teams. A few are even placing AI agents on organizational charts as full participants rather than just tools.
HR leaders have both opportunity and responsibility to lead this organizational reimagining. They’re in the best position to shape AI-centric structures, take the lead on AI governance and fairness, and redefine work, talent, and the workforce. By embracing this challenge, HR can make the most of AI and help the business succeed through change.
Five Actions CHROs Should Take Now
For CHROs ready to seize these opportunities, the following five priorities should top their list for the next 12 months:
- Make HR one of the first enterprise areas to scale GenAI and agents. Use HR workflows to build proof of value and internal fluency; HR must learn fast enough to teach the rest of the organization.
- Establish AI narrative and change capabilities. Get ahead of employee concerns with the case for change focused on benefits to them (e.g., removing repetitive or routine tasks, driving impact) rather than leading with cost reductions. HR must not miss the opportunity to establish and guard employee trust.
- Refresh skills-based strategic workforce plan for each function. Assess AI impact on roles and skills, activities, and functional organization; lead efforts to redesign 2030 labor models.
- Enable HR leaders to drive AI-enabled organization and people transformation. Train HR in AI tool fluency, work redesign, and enterprise influence, including change management capabilities, establish upskilling and mobility platforms to support employees as they adapt to their new role requirements.
- Drive cross-functional alignment on AI usage norms. Establish clear recommendations for where, how, and when AI is used in decisions; and publish them for use within the broader enterprise.
These priorities are designed to be actionable and to reinforce one another. Together, they position HR as both a builder of internal capability and a trusted advisor on enterprise-wide transformation.
We’d like to thank Liz Lucero, Jordan Lockhart, and Bill Beaver for their support in the development of these materials.
