The way organizations find, develop, deploy, and support talent has transformed through the use of artificial intelligence (AI). The chief human resources officer (CHRO) role is moving from steward of people operations to enterprise leader of human-AI strategy. Key shifts include positioning AI governance as a strategic priority at the board level, reimagining talent and skills strategies to drive continuous and adaptive learning, embedding accountability for fairness, ethics, and transparency in algorithmic decisions, and designing integrated operating models where HR partners closely with data, legal, and technology leaders to enable human-AI collaboration. This article explores how the CHRO role is evolving, what tools and competencies are critical, and how leaders can prepare for this shift through real-world examples, risk insights, and actionable strategies.
Traditionally focused on administrative tasks, HR, even in cases where it has been at the heart of people and culture processes, now faces a fundamental transformation driven by AI.
Traditionally focused on administrative tasks, HR, even in cases where it has been at the heart of people and culture processes, now faces a fundamental transformation driven by AI. The urgency to adapt to this new playing field is striking: according to the 2026 CHRO Survey by the CHRO Association and the University of South Carolina’s Darla Moore School of Business, 91% of CHROs rank AI and digitization of the workplace as their top concern, far outpacing governance, engagement, and talent combined. SHRM’s State of AI in HR 2026 report, drawing on nearly 1,900 HR professionals surveyed in December 2025, confirms that 62% of organizations are currently deploying AI somewhere in their operations, with 39% having already adopted it within the HR function itself.
Yet readiness lags strategy: 92% of CHROs responding to the SHRM survey anticipate greater AI integration in workforce operations, while 84% expect upskilling in AI-specific skills to increase, signaling a gap between ambition and execution.
By 2030, the World Economic Forum projects 170 million new jobs and 92 million displaced, a net gain of 78 million, underscoring both disruption and opportunity. AI’s effects vary by role and function (MIT Sloan Management Review, 2025), while Deloitte notes work itself is becoming “boundaryless” as AI reshapes task flows and team structures. CHROs must manage both workflows and workforce, not just headcount. With 39% of current skills expected to be obsolete by 2030, HR must drive continuous learning while supporting employees through transitions with empathy.
This disruption is accelerating, with examples like Novo Nordisk employees saving two hours weekly using Microsoft Copilot 365 (MIT Sloan Management Review, 2025). Yet the urgency for HR to move from reacting to leading has never been greater: harnessing AI deliberately and strategically is what will separate organizations that merely adopt new tools from those that genuinely redefine what human leadership means in an intelligent world.
AI is no longer a peripheral tool in HR; it has become a core driver reshaping nearly every stage of the employee experience.
AI is no longer a peripheral tool in HR; it has become a core driver reshaping nearly every stage of the employee experience. From talent acquisition, where AI identifies, assesses, and prequalifies candidates, to workforce development and internal mobility, algorithms enable decisions with speed and precision beyond human capacity. Beyond hiring, AI personalizes learning, supports adaptive performance evaluations, optimizes scheduling, and even improves workplace safety. Intelligent assistants handle routine queries, freeing HR teams to focus on empathy, strategy, and culture-building.
According to BCG, generative AI can boost HR productivity by up to 30%, largely by automating repetitive tasks and accelerating high-quality outputs. But the impact goes deeper than efficiency: freeing HR from low-value work enables focus on elevating employee experience, shaping culture, and aligning talent strategies with business goals. This transition moves HR from a process-heavy back-office role into a strategic, forward-looking engine driving competitiveness and innovation.
A significant emerging dimension is the rise of agentic AI in workforce management. According to Korn Ferry, more than half of talent leaders are already planning to add autonomous AI agents to their teams in 2026: a shift from using AI to assist HR professionals to deploying AI as an active participant in workforce operations. This development carries profound implications: as agentic systems take over routine HR workflows, the CHRO must decide where autonomy genuinely adds value, where human judgment must remain central, and how to govern systems that act with increasing independence. Compounding this, an overwhelming 82% of boards and CEOs say they plan to reduce up to 20% of their workforces over the next three years because of AI, with many flattening structures by eliminating middle management and entry-level roles, creating leadership pipeline risks that no other C-suite leader is better positioned than the CHRO to address (Korn Ferry CEO & Board Survey, 2026).
AI-powered tools are reshaping every stage of the HR value chain. In recruitment, platforms like Phenom and Greenhouse use advanced AI for resume parsing, candidate matching, and bias reduction; HireVue applies AI to video interview assessment; and Pymetrics (now part of Harver) uses neuroscience-based games and AI to assess cognitive and emotional fit, reducing bias in candidate evaluation. For talent intelligence and internal mobility, Eightfold AI offers a deep-learning platform that maps employee skills and career trajectories across the full talent lifecycle, helping enterprises identify hidden-fit candidates, surface internal mobility opportunities, and plan workforce capabilities based on skills rather than job titles. For conversational HR support, Moveworks deploys intelligent virtual assistants to resolve employee queries and automate HR workflows. In performance management and engagement, Culture Amp and BetterUp provide continuous feedback, performance analytics, and personalized coaching. For workforce planning and analytics, Workday Adaptive Planning and Oracle Cloud HCM use AI to forecast skill needs, model workforce scenarios, and optimize talent allocation. Together, these platforms are enabling more data-driven, agile, and human-centered HR functions.
Unilever has been among the most documented adopters in recruitment.
Your learning strategy – a key driver of growth
The range of applications already in use across leading organizations illustrates how broadly AI is reshaping the HR function, from hiring to pay equity.
Unilever has been among the most documented adopters in recruitment. Working with HireVue and Pymetrics, Unilever uses AI-powered video interviews and game-based psychometric assessments to screen candidates at scale, processing up to 1.8 million applications annually. The results have been striking: a 90% reduction in time to hire, more than 50,000 hours of candidate interview time saved, and a 16% increase in diversity hires (HireVue/Unilever, 2021; Bernard Marr, 2021). The case is instructive not only for what AI can achieve in recruitment but also for how it must be governed: HireVue discontinued its facial expression analysis feature in 2020 after internal research and public concern raised questions about its validity and bias risk, a reminder that capability must always be weighed against fairness. Chipotle offers a high-volume complement: its AI assistant Ava Cado helped hire 20,000 seasonal workers, lifting application completion rates from 50% to 85% and cutting processing time from twelve days to four (MarketWatch).
Mastercard’s “Unlocked” platform illustrates what enterprise-wide AI-enabled talent development can look like at scale. Launched globally to its 35,000-strong workforce in 2022, Unlocked matches employees to internal roles, projects, mentoring relationships, and learning pathways based on the skills they have and the skills they want to build. Today, 93% of Mastercard’s workforce is registered on the platform, employees have collectively logged one million project hours, and a third of those who engaged saw a career move or promotion: a direct business outcome, not merely an engagement metric (Mastercard.com, 2026; Time/Charter, 2025). When the fraud detection team urgently needed AI talent, Unlocked enabled the rapid redeployment of employees with adjacent data skills. As the Chief Talent Officer noted: “Learning isn’t an HR metric anymore; it’s a business performance driver.”
IBM’s AskHR platform offers one of the most thoroughly documented examples of agentic AI transforming an HR function at scale. Built on IBM watsonx Orchestrate, AskHR handles over 80 automated HR tasks, from payroll queries and vacation requests to manager workflows and employee letters. In 2024 alone, the system managed 11.5 million employee interactions, with a 94% containment rate, meaning only 6% of queries required a human HR partner. Over four years, IBM has reported a 40% reduction in its HR operating costs. The story is instructive not only for its outcomes but for its journey: when IBM first forced adoption by shutting down its HR phone lines and email addresses overnight in 2018, employee Net Promoter Score for HR collapsed from +19 to -35. Only through sustained listening, iteration, and genuine change management did the score recover to +74 by 2025 (IBM.com, 2025; Fortune, 2024). As IBM CHRO Nickle LaMoreaux said at HR Tech 2025: “AI is not magic. It takes hard work, behavior change, culture change, business process change, and sometimes leadership change.” (HR Executive, 2025)
Salesforce has been a benchmark since 2015, when it became one of the first major companies to conduct an AI-assisted annual pay audit across its global workforce. The analysis identifies unexplained disparities in base salary, bonuses, and equity grants across gender globally and race and ethnicity in the US. In its most recent assessment, published in 2024, 3% of employees received pay adjustments, and after corrections, employees performing similar jobs were paid on par across all genders globally and all races and ethnicities in the US. Since the program’s inception, Salesforce has spent more than $22m correcting pay gaps (Salesforce.com, 2024), and this case demonstrates that AI is not only a tool for productivity but also for institutional fairness, making visible what manual processes routinely miss.
Moderna’s decision to merge HR and IT under a unified leadership model is also instructive: faced with AI’s rising influence in talent management, Moderna integrated the people and technology domains to align workforce planning with tech-readiness. This move raised important questions about preserving the human-centered focus of HR (The Wall Street Journal, 2025) and the potential pitfalls of merging domains with distinct mandates and values.
As AI’s influence grows, so do the stakes. Without ethical guardrails, AI systems can amplify bias and erode trust. The Amazon case is perhaps the most cited example: a CV screening tool built between 2014 and 2017 was found to systematically downgrade resumes containing the word “women’s” and to penalize graduates of women’s colleges, because the model had been trained on a decade of hiring data that reflected existing male dominance in technical roles. Amazon scrapped the project when it could not guarantee the system would not learn other discriminatory patterns (MIT Technology Review, 2018). The lesson is not that AI cannot be used in recruitment, but that training data encodes history, and history in hiring has rarely been neutral. Excessive automation risks robbing HR of its human-centered edge. The example of Moderna also warns of the perils of merging HR and tech mindsets, with distinct mandates and values, risking skewed outcomes if not carefully balanced. At the same time, boards and CEOs expect disciplined AI deployment and oversight. In 2024, surveys of directors show boards elevating AI governance, asking management (often via the CHRO and CIO) to evidence controls for ethics, workforce impacts, and culture (Harvard Law School Forum on Corporate Governance, 2024). CHROs must actively safeguard the human in human resources.
Equally important, CHROs are becoming policy makers in enterprise AI governance, operating in a rapidly shifting and increasingly complex regulatory landscape.
The Act entered into force on 1 August, 2024, establishing a risk-based framework for AI use across the EU. For HR, the most immediate impact has already arrived: since 2 February 2025, certain AI practices in the workplace have been outright banned, including emotion recognition during hiring interviews and biometric categorization of candidates. The pivotal compliance deadline for HR is 2 August 2026, when the full suite of high-risk system obligations becomes enforceable for all employment-related AI, covering recruitment, screening, candidate evaluation, performance monitoring, and promotion decisions. Requirements include mandatory risk assessments, bias testing, technical documentation, human oversight mechanisms, transparency disclosures to candidates, and continuous monitoring. Non-compliance can carry fines of up to €35m ($40.98m) or 7% of global annual turnover for the most serious violations (European Commission, 2024; Ogletree, 2025). The Act carries extraterritorial reach: US employers using AI tools to recruit EU-based candidates or manage EU-based workers are subject to these obligations even without a physical EU presence.
The US federal regulatory picture has shifted significantly. In January 2025, the Trump administration revoked Biden-era executive orders on AI governance, and the EEOC subsequently removed its 2023 guidance on responsible AI use in employment selection from its website. However, employers remain fully liable under Title VII and other existing federal laws if their AI tools produce a disparate impact on protected groups, regardless of whether the tool was purchased from a third-party vendor. At the state level, the regulatory patchwork is tightening: Colorado’s Senate Bill 24-205, effective February 2026, mandates bias audits for high-risk AI used in employment decisions; California’s Civil Rights Council has extended anti-discrimination rules to AI tools, requiring employers to retain automated decision data for four years; and New York City, Illinois, and other jurisdictions have layered additional notice, audit, and human-review requirements onto HR AI use (Holland & Knight, 2025; Lexology, 2026).
Taken together, these developments place CHROs squarely at the center of algorithmic risk management, owning adverse-impact testing, accommodation processes, transparency obligations, and vendor due diligence in an environment where regulatory requirements are simultaneously tightening globally and fragmenting domestically. As Kalin Anev Janse, CFO of the European Stability Mechanism, underscored, “Every leader, including CFOs, must champion AI and understand the systemic risks of generative AI in finance”, a principle that applies with equal force to HR (World Economic Forum, 2025).
There is a dual imperative for CHROs: building AI fluency across HR teams while simultaneously doubling down on the distinctly human capabilities: empathy, judgment, and contextual leadership, that AI cannot replicate.
CHROs must combine data fluency with human-centered leadership, moving from intuition-driven decision-making toward evidence-based and data-informed strategies. It requires a shift from a compliance-first mindset to one that embraces ethical stewardship of algorithms and employee data. Workforce planning must evolve from static, annual exercises to continuous and agile processes of reskilling and redeployment. Most importantly, HR must no longer be treated as a siloed function, but as an enterprise-wide partner that drives and sustains transformation.
The skills gap within HR itself is a critical challenge to address. Korn Ferry’s research finds that 40% of CHROs cite insufficient AI-related knowledge and skills within HR teams as the biggest obstacle to integrating AI into talent management. At the same time, as AI handles more technical work, human capabilities become the differentiator: nearly three in five employers say soft skills are more important today than five years ago, and demand for social and emotional skills is expected to grow 26% by 2030 (Gartner, 2025). There is a dual imperative for CHROs: building AI fluency across HR teams while simultaneously doubling down on the distinctly human capabilities: empathy, judgment, and contextual leadership, that AI cannot replicate.
New hybrid roles are emerging in response. Finance professionals now combine domain expertise with fluency in AI tools and data storytelling. CHROs must cultivate equivalent roles in HR, fostering AI literacy as a baseline competence across their function.
The challenge facing CHROs is not simply to adopt AI tools but to deliberately reshape how the HR function operates, governs, and develops people in a world where humans and machines increasingly work side by side.
In the AI era, the CHRO is no longer just a steward of people processes; the CHRO is an architect of the future of work itself. The organizations that thrive will be those where HR leaders reimagine their mandate: embedding ethical AI, enabling lifelong learning, and fostering trust in human-machine systems. The future belongs to CHROs who can harmonize the intelligence of algorithms with the creativity and empathy of people, creating workplaces that are not just more efficient, but also more human.
This article is part of a continuing series of insights on ‘AI and the CxO’.
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