HR must own the Total Workforce to drive business outcomes

Throughout the discussions, leaders repeatedly returned to a common challenge: organizational structures were built around jobs, while the future of work increasingly demands visibility into skills.

Many organizations continue to manage talent through thousands of job titles, legacy job descriptions, and fragmented role structures. While those constructs may remain useful for administration, participants questioned whether they remain useful for workforce planning.

The emerging view is that work must be broken down into the underlying skills and activities that create value.

Organizations must "melt the ice cube" of roles and job descriptions. Rather than treating jobs as fixed collections of responsibilities, leaders are beginning to deconstruct roles into pools of skills, tasks, and capabilities that can be dynamically assembled and redeployed as business needs change.

The goal is not simply to create cleaner job architectures. It is to build the visibility required to understand workforce supply and demand, accelerate talent mobility, identify capability gaps, and create more agile workforce planning models.

Several leaders also emphasized that skills initiatives create value only when coupled with governance. Skills taxonomies, proficiency standards, capability clusters, and workforce data require ongoing management to prevent fragmentation and maintain credibility.

In the future, workforce planning may increasingly revolve around capabilities rather than positions, creating organizations that can adapt more quickly as business priorities evolve.

“Stop thinking about rigid jobs, titles, and roles. We must melt the ice cube, shifting to a fluid collection of skills, and reshape the water to design a truly hybrid human-agent workforce.”

- Leila Shin, Principal, Workforce Advisory, KPMG LLP

While AI was a focal point throughout the day, participants repeatedly cautioned against pursuing technology without a corresponding focus on trust, governance, and accountability.

Leaders acknowledged significant excitement about the potential of AI and digital labor. At the same time, discussions consistently returned to questions that technology alone cannot answer.

• Who is accountable when AI influences an important decision?
• How should organizations govern digital workers?
• What decisions require human oversight?
• How should leaders manage risk, transparency, and trust?

Participants broadly agreed that successful AI adoption depends less on deploying models and more on creating the governance frameworks that allow people to use them confidently.

Many leaders challenged the tendency to view AI primarily through the lens of productivity. Instead, they emphasized that organizations should begin by understanding the business outcome they are trying to achieve and then determine where technology can support that objective.

In practice, this means expanding governance discussions beyond regulatory compliance. Trust affects employee adoption, leader confidence, customer perception, and organizational resilience. Without trust, even technically successful deployments may struggle to create meaningful value.

As organizations move toward increasingly hybrid workforces, governance is becoming not a control mechanism, but a prerequisite for scale.

“Where does liability sit when a digital team makes an error that impacts a customer contract? If we place an AI agent on the org chart under my name, am I legally signing up to manage and govern that model’s performance just like a human?”

- CHRO, Global Manufacturer of Automotive Components

Transformation itself is not new. What many participants highlighted, however, is that employees and leaders appear to have less capacity to absorb change than they did in previous periods of disruption.

Economic uncertainty, technological acceleration, competing priorities, and overlapping transformation initiatives have created an environment where employees frequently feel overwhelmed before the next change initiative begins.

In this environment, successful organizations are shifting their focus from managing individual transformations to increasing organizational capacity for adaptation.

Participants repeatedly described the need for greater discipline around prioritization, communication, simplification, and leadership alignment. Rather than launching more initiatives, leaders spoke about helping employees understand which changes matter most and how those changes connect to a broader vision.

Several organizations have begun creating predictable operating rhythms for transformation, establishing regular cadences, structured communication channels, and repeatable deployment mechanisms. The objective is to reduce uncertainty surrounding the process of change so employees can focus their attention on the substance of change itself. It also sets an expectation that change is actually embedded in work, and it becomes a more predictable part of the day to day rhythm.

Leaders also discussed replacing the language of "test and fail" with "test and adapt." The distinction reflects a belief that continuous evolution requires experimentation, but also requires learning, adjustment, and accountability.

“The next chapter of HR is not about automating people out of the system. It is about using AI to amplify human performance, elevate the effectiveness of every manager, and systematically shift workforce performance toward the top quartile. That is how HR moves from a support function to a lever for growth.”

- Evan Metter, Principal, Workforce Advisory, KPMG LLP

Amid conversations about AI, automation, workforce redesign, and digital labor, participants consistently returned to a seemingly contradictory conclusion: the more capable technology becomes, the more important uniquely human capabilities become.

As routine work becomes increasingly automated, organizations will rely more heavily on judgment, curiosity, adaptability, empathy, communication, and leadership.

Participants noted that technology can accelerate work, but it cannot establish trust. It can generate information, but it cannot provide accountability. It can support decision-making, but it cannot replace leadership.

Many leaders also pointed to growing anxiety throughout the workforce. Employees are managing greater uncertainty around career paths, changing job expectations, and the implications of emerging technologies. In this environment, people increasingly need leaders who can create clarity without pretending to have every answer.

The discussion suggested that the future workforce will require a different leadership profile. Technical expertise remains important, but it may become less differentiating than the ability to guide organizations through ambiguity, foster trust, and help people navigate change.

Rather than reducing the importance of human leadership, AI may ultimately elevate it.

“Everything we did were linked back to being restless, which meant I'm interested in learning. Empathetic. Everything I do is about you as the employee. And devoted to your success so that we can be devoted together to our customer shared success.”

- Former CHRO, Technology Services Organization