AI focus | VP of AI Workforce Transformation: The newest addition to senior leadership teams
AI is often described as a stack of enabling layers: energy, chips, infrastructure, models, and applications. This framing helps explain how AI is built and scaled, but the current set of layers does not capture how AI translates into meaningful enterprise value. An additional layer—one that is less clearly defined—is leadership: the intentional redesign of jobs, skills, management routines, incentives, governance, and trust so that AI meaningfully changes how work gets done and how organizations perform over time.1
AI in the workplace still feels new, but many organizations are now several years into their AI journeys and have made substantial investments in tools, platforms, and use cases. Despite this progress, the path to consistent, scalable value creation remains uneven overall. Some organizations are seeing encouraging early results; others find themselves in “pilot purgatory,” with fragmented initiatives that are difficult to scale.
Much of this variability has little to do with the technology itself. Instead, it reflects how organizations are structuring their adoption and use of AI. Too often, AI adoption within an organization becomes a responsibility that no one and everyone owns. Today, responsibility for AI adoption is often distributed across multiple functions. Technology teams focus on building and deploying solutions. Business units prioritize use cases tied to immediate operational needs. HR supports elements such as skills, hiring, and employee experience. However, the most complex and consequential questions—how AI leads to sustainable performance improvements, and, to get there, how roles evolve, how work is redesigned, and how managers lead—do not sit neatly within any single function. Decisions about automation versus augmentation, changes in spans of control, and the evolution of managerial responsibilities often require input from multiple stakeholders.
Organizations are beginning to recognize this, and to ask themselves: How do we best structure our executive teams to accelerate AI adoption and impact?
Many organizations are turning to CHROs to lead on AI adoption. Our research shows that more than half of CEOs now involve their CHRO in AI-related workforce transformation efforts. However, CHROs already carry a broad set of responsibilities, often have limited direct AI experience, and may not have the capacity to drive this agenda end-to-end.
One emerging approach we have seen companies take is the creation of a new senior role dedicated to translating AI investments into productivity gains, capability building, and sustainable performance improvements. While the role can take different forms, many organizations are gravitating toward titles such as Vice President of AI Workforce Transformation. Below, we explore how organizations are shaping this role and offer considerations for those weighing if this approach is right for them.
Why a VP of AI Workforce Transformation may be the right move
AI adoption requires intentional, cross-functional leadership. Organizations increasingly recognize the need to redesign jobs, skills, management routines, incentives, governance, and trust mechanisms so that AI meaningfully changes how work gets done and how the organization performs over time.
The creation of a VP of AI Workforce Transformation represents one way to bring focused leadership to this effort. Positioned within HR but working in close partnership with technology, finance, and business leaders, the VP of AI Workforce Transformation helps coordinate and align cross-functional efforts. But beyond that, the role sets the organization’s AI adoption agenda: redesigning skills, management routines, incentives, governance, and trust mechanisms so that AI meaningfully changes how work gets done and how the organization performs over time.
The primary value of this role lies in providing dedicated capacity to focus on workforce transformation, complementing the broader responsibilities of the CHRO.
What the VP of AI Workforce Transformation could own
For organizations that choose to establish this role, the VP of AI Workforce Transformation can provide a focal point for several areas that often suffer from lack of coordination.
One area is work redesign at scale. Many organizations are investing in AI tools but are still in the early stages of systematically rethinking how work is structured to take advantage of those tools. A dedicated leader can bring greater consistency and rigor to decisions about which tasks should be automated, which should be augmented, and how roles should evolve over time.
Another area is workforce planning and capability development. As AI reshapes demand for skills and roles, organizations can benefit from more integrated approaches to forecasting, reskilling, and redeployment, linking workforce planning more closely to business strategy and technology investments.
Adoption and trust are also critical. AI adoption depends not only on access to tools but on how employees and managers integrate those tools into their daily work. Providing clarity, support, and transparency plays a significant role in enabling that transition. The VP of AI Workforce Transformation, by virtue of their dedicated role and cross-functional oversight, is well placed to provide that clarity.
In addition, the person in this role can contribute to governance and risk management, particularly as AI becomes more embedded in workforce decision-making. Questions related to fairness, explainability, and human oversight often intersect with employee experience and organizational culture, again lending itself to the type of cross-functional remit that this role would hold.
Finally, the VP of AI Workforce Transformation can support the evolution of HR itself, aligning capabilities across talent acquisition, learning, analytics, and business partnering to drive a more integrated transformation agenda.
First-year priorities and measures of progress
In organizations that introduce this role, early efforts focus on a small number of high-impact initiatives. For example, the VP can identify areas where AI has the potential to materially improve performance and work with business leaders to redesign work in those areas.
Other priorities include building a clearer understanding of how roles and skills are evolving and establishing guiding principles for human–AI collaboration.
Progress should be evaluated through a combination of indicators. In addition to tracking activity, organizations should assess outcomes, including productivity improvements, cycle-time reductions, employee adoption, and levels of trust and engagement. Over time, linking these indicators to business performance will provide a clearer view of impact.
Conclusion
AI is already reshaping how work gets done across industries. The question many organizations are now exploring is how to translate that change into sustained improvements in performance, capability, and growth.
Creating a VP of AI Workforce Transformation is one potentially powerful approach. For some organizations, this role can provide additional focus, coordination, and execution capacity, helping connect AI investments more directly to workforce and business outcomes.
At its core, effective AI adoption requires clear and intentional ownership, ensuring that the workforce dimension of AI is addressed with the same level of rigor as the technology itself. This role is one way to provide that ownership.
That said, it is not the only path forward. Some organizations may instead rely on cross-functional teams or expanded mandates for existing leaders. This approach will not be right for everyone. However, for organizations finding that even the most advanced AI does not translate into impact on its own, introducing greater coordination and leadership focus may be an important next step.
If the AI stack explains how intelligence is built, then leadership, whether through a dedicated role or another model, determines how that intelligence is ultimately translated into performance.
About the authors
Ryan Bulkoski (rbulkoski@heidrick.com) is co-global managing partner of the Technology & AI Officers Practice; he is based in the San Francisco office.
Brian Kropp (bkropp@heidrick.com) is the vice president of global insights; he is based in the Washington, DC office.
Brad Warga (bwarga@heidrick.com) is co-head of the global Human Resource Officers Practice; he is based in the San Francisco office.
Jennifer Wilson (jwilson@heidrick.com) is co-head of the global Human Resource Officers Practice; she is based in the Dallas office.
References
1 For further exploration of the human leadership capabilities central to success with AI, see “Finding the human core of competitive advantage in the AI era: Avoiding the Pygmalion trap,” Heidrick & Struggles,April 22, 2026, heidrick.com.