Why an AI-powered future needs human-powered reinvention

Agentic AI has the potential to fundamentally reshape business, not just in terms of tasks or roles, but in how organisations define their purpose, create value, and remain relevant. This is a moment of opportunity unlike any technology shift we have experienced. It requires more than process automation or tool integration. It demands a rethinking of the very foundation of the enterprise - its operating model, workforce structure, and reason for existing in a world where both ideation and execution can be machine-led.

This whitepaper explores what is crucial for all AI transformation efforts: the need for strategic reinvention grounded in organisational purpose. PwC’s perspective on reinvention defines it as a complete reimagining of how a company operates to create, deliver, and capture value, rather than simply improving or tweaking existing methods. This framing is particularly relevant in the context of agentic AI, which is not an incremental enhancement but a transformative force. Before redesigning roles, leaders should step back and ask: what is our unique contribution in an environment where autonomous systems can perform not only tasks, but also create, decide, and act with agency? Clarifying this purpose is the foundation for meaningful reinvention and a prerequisite for defining the human role in an AI-powered enterprise.

As outlined in PwC’s 2024 Value in Motion³ study, an estimated US$7.1 trillion in revenue is expected to migrate across companies in 2025 due to technology and structural disruption. These shifts will be driven in large part by organisations that can reinvent their business models - not just deploy new tools. Yet most are focusing only on incremental benefits. They are automating existing work rather than reimagining how work should be done. They are eliminating roles, particularly at the junior level, before creating new ones designed for the future.

There is still a journey ahead to help all executive teams understand what agentic AI can truly accomplish. This leads to a widening organisational lag: rather than designing future-oriented roles to harness the potential of these systems, companies are eliminating junior roles at a faster pace than they are creating new ones. In many cases, this displacement is happening without a well thought through workforce plan behind it – making it, in some cases, unseen and unaddressed. Without deliberate reinvention, organisations risk hollowing out the talent pipeline that is critical for long-term adaptability, leadership development, and sustained transformation.

The purpose of this paper is to define that gap, explain its implications, and offer a path forward. It calls on executives to shift focus from automation to reinvention, beginning with clarity of purpose and extending to the intentional design of new human roles, career models, and organisational structures fit for an AI-powered future.

Agentic AI refers to systems made up of multiple autonomous agents that can reason, act, and collaborate toward shared goals. These agents don’t simply respond to queries; they execute multi-step processes, make decisions based on context, interact with other agents or systems, and learn over time. Think of a system that can autonomously investigate potential fraudulent transactions, execute an entire middle office operations process or even run a marketing campaign across multiple platforms – end to end – with minimal oversight.

This is fundamentally different from current efforts to implement singular agents based on generative chat interfaces or even building workflow agents into processes as designed by humans. Those tools assist; agentic systems act. They shift the relationship between humans and work by taking over coordination, decision-making, and execution. As such, they demand a redesign of the business functions they support.

Yet many organisations treat AI as a feature – an enhancement to existing workflows – rather than a foundational redesign. We believe this misunderstanding is the root of the role transition gap.

Agentic AI is not simply a more powerful tool – it is a catalyst for a new way of working. These systems are already beginning to dismantle traditional roles, not by redistributing tasks to other people, but by replacing entire job functions with autonomous agents. This shift is happening quietly in many organisations. Work once done by junior staff or analysts is being absorbed by systems that can reason, coordinate, and act across complex processes. What is often framed as automation is, in practice, a structural replacement – one that is not being matched by deliberate creation of new human capabilities or responsibilities. 

Many executive teams are still working to understand the scale of this shift. In boardrooms, AI is still too often discussed in terms of incremental productivity gains or workflow augmentation. The conversation needs to extend to the fundamental rethinking of how work is structured and delivered. Agentic systems do not merely affect roles. They require reimagining entire workflows, reconfiguring teams, and designing new models of human-agent collaboration. These shifts challenge legacy assumptions about how decisions are made, how teams operate, and how value is created through collective effort. 

This opens a broader and more urgent set of questions around capability, leadership, and organisational design. Rethinking work in the agentic era is not about rewriting job descriptions. It is about redefining the systems through which people, machines, and decisions intersect. Organisations will have the opportunity to explore new models of teaming, where humans and agents operate in interdependent cycles. They will also need to develop capabilities that cannot be easily replicated by autonomous systems – including human judgment, cross-functional sensemaking, and trust-building in complex environments. 

In this context, reinvention becomes a leadership challenge as much as a technical one. Agentic AI will test leadership in new ways. It will require clarity of direction, the ability to lead through sustained ambiguity, and a commitment to building trust in both technology and organisational change. What worked in the past may no longer be relevant, and that can be deeply uncomfortable. Leaders will need to make decisions that go against instinct, tradition, and familiar models of management. As our colleague Matt Wood, PwC’s Global Chief Technology and Innovation Officer, PwC United States highlights in his recent book⁴, Both, And, the leaders of the future must hold space for tension and contradiction – balancing stability with change, continuity with disruption. Matt highlights that real leadership isn’t about resolving tension – it’s about learning to live inside it. Reinvention is not just about redesigning roles or workflows. It is about shaping culture, enabling people and guiding the organisation through a period of fundamental transformation. 

Transformative change will not emerge from the ranks alone. For many employees, agentic AI represents disruption to familiar work, identity, and career paths. Expecting the workforce to lead this change is unrealistic – and in some cases, counterproductive. It is leaders who must put a finger on the scale, guiding reinvention intentionally and visibly. This requires not only clarity about what agentic AI can do, but also courage to make decisions that may feel uncomfortable in the short term, in order to create long-term opportunity. 

Recent data from PwC’s 2024 Hopes & Fears² study underscores the stakes. Sixty-two percent of workers say the pace of change at work has accelerated, 45% report significantly increased workloads, and 44% do not understand the reason behind the changes they are experiencing. This signals more than a communication gap. It reflects the need to build the leadership frameworks and organisational scaffolding necessary to guide people through change with clarity, empathy, and trust. 

Each prior wave of technological disruption gave rise to new technical roles – but equally important were the business roles that emerged to operationalise, govern, and scale these innovations. These were not fringe roles; they became the new center of gravity in how organisations created value.

During the Industrial Revolution not only were technical roles like mechanical engineers and machinists created, but business roles like operations managers, production planners and quality control supervisors were also created. The era of Enterprise Software and Computing gave rise to technical roles like programmers and systems architects while also creating business analysts and process owners. With the dawn of the internet, we saw web developers and cybersecurity specialists while also seeing business roles like digital marketers and e-commerce specialists. And finally, the rise of cloud and software as a service create DevOps engineers and cloud architects while also creating customer success managers and agile coaches.

These examples are clearly non-exhaustive but make a key point. When compared to the Intelligence Era thus far we are seeing the emergence of many technical roles like LLM engineers, prompt engineers and AI systems architects, to name a few. But the emergence of business roles is conspicuously missing. Very few companies have embraced agentic systems and seen the creation of roles like agentic process designers, AI capability managers or the many human-agent interaction leads.

This imbalance signals a dangerous drift: we’re scaling technical innovation without designing the organisational structures that make it sustainable.

The most visible symptom of the current imbalance between AI deployment and organisational reinvention is the accelerating displacement of junior and mid-level roles – without corresponding creation of new roles elsewhere in the business. A 2024 Accenture report⁵ found that 40% of tasks performed by entry-level roles in HR, finance, and customer support are now automatable. The World Economic Forum⁶ projects 83 million jobs will be displaced by 2027, with only 69 million created, many of which will require significantly different skill sets. Research⁷ from MIT and Stanford (2024) also highlights that junior knowledge workers – such as analysts and coordinators – are now more susceptible to automation than many manual labour roles.

Yet this transition should not be understood solely through the lens of displacement. The emergence of agentic AI presents an opportunity to redesign, not just reduce, the workforce. As traditional roles disappear, new ones will emerge – often with very different expectations, capabilities, and forms of contribution. The challenge is not just about replacing one set of tasks with another, but about reimagining how human potential is organised, developed, and applied in the age of intelligent systems.

This makes workforce transition both a strategic and a cultural imperative. Organisations must move quickly to reskill, redeploy, and rethink career pathways. But speed alone is not enough. The disruption will be deeply personal for many employees, especially as familiar roles fade and new expectations arise. The skills needed in future roles will not always resemble those being automated, and the pathways to those roles may not be obvious. In this context, leadership has a vital role to play – not just in driving change, but in stewarding people through it.

To manage this transition responsibly, leaders must provide clarity, build trust, create pathways for growth and foster curiosity. This includes transparent communication about what is changing and why, as well as tangible investment in learning, coaching, and career development. How organisations handle this inflection point will shape not just future capability, but also culture, morale, and long-term credibility. People will remember whether they were included in the future – or left behind by it.

There is also a lot to be optimistic about. PwC’s Hopes and Fears 2024² survey found that 82% of daily Generative AI (GenAI) users expect AI to increase efficiency, and nearly half believe it will lead to higher pay. However, only 46% feel their employer is giving them the opportunity to learn new skills. This optimism, left unsupported, becomes a missed opportunity. Without deliberate action to redesign work and develop people in parallel, companies risk not only losing talent – but losing trust.

Organisations are not just automating roles but rather they are dismantling the scaffolding of future leadership. These junior roles being impacted have traditionally served as foundational training grounds for domain expertise, strategic thinking, and leadership development. Without new roles and pathways to replace them, organisations may find themselves lacking the mid-career strength and institutional memory needed to lead into the future.

Agentic AI isn’t just a technological change, it is a reconfiguration of how work is done. As such, it demands the creation of new human roles to guide, complement, and collaborate with AI systems. Roles like Agentic Process Designers, Human-Agent Interaction Leads, AI Capability Product Owners, Organisation Model Strategists, AI-Augmented Team Leads, Governance Stewards, and Translational Leaders are just a starting point. Others will emerge as organisations begin to experiment and learn what hybrid, human-agent teaming looks like in practice.

But the challenge is not just about naming new roles. It’s about designing them in ways that reflect how the workforce is changing. AI is arriving alongside other significant shifts in workforce dynamics. People are working longer, our workforce is ageing, career paths are less linear, and organisations are managing multi-generational teams with differing expectations around purpose, flexibility, and growth. At the same time, cognitive demands are increasing and trust in technology is not universal. Leaders must understand how these trends intersect with AI adoption and establish workforce strategies that are inclusive, responsive, and future-fit.

The creation of these new roles is not just a strategic choice, it is an economic imperative. PwC projects that global GDP could grow from US$105 trillion in 2023 to US$132 trillion by 2035, driven largely by the effective application of technologies like agentic AI. But these gains are contingent. Without new structures, governance roles to ensure responsible adoption of Agentic AI, and trust-building functions, that future value is at risk.

New roles must do more than manage AI systems. They must help organisations reimagine how humans contribute value in an intelligent enterprise. That means designing roles that support not only collaboration and oversight, but also human judgment, ethical stewardship, and the creative, contextual capabilities that agents alone cannot deliver. These roles will be essential in shaping not just how AI is used but how organisations evolve – operationally, culturally, and strategically in response to it.

To realise the full value of agentic AI, organisations must shift focus from short-term automation to long-term reinvention. This transformation is not simply about deploying smarter tools – it is about designing new ways of working, new workforce models, and new forms of value creation that are fit for a dynamic and intelligent era.

Crucially, AI is arriving alongside broader shifts in workforce dynamics. People are working longer, career paths are less linear, and organisations are managing multi-generational teams with diverse expectations around purpose, flexibility, and growth. Cognitive demands are intensifying, while trust in technology is still uneven. Leaders must understand how these trends intersect with AI and make certain that reinvention efforts are inclusive, responsive, and grounded in human realities.

At the same time, the future is increasingly unpredictable. Agentic AI is evolving faster than most organisations can plan for. Agility can no longer be viewed as a leadership trait alone – it must become a structural capability. That means designing workforce models that enable experimentation, rapid reskilling and flexible career pathways. It may also require expanding the boundaries of the workforce itself through alternative models such as external talent pools, gig-based contributions or AI-enabled services that allow organisations to scale capacity and capability without relying solely on traditional employment structures. Those that build for adaptability and optionality will define the future.

This moment also demands that organisations elevate the learning challenge. The pace of transformation requires more than new training modules. It calls for a rethinking of how people build capability, stay engaged, and retain relevance. While AI can dramatically increase productivity, it can also diminish active learning, motivation, and judgment if not introduced thoughtfully. The ability to learn, unlearn, and relearn – continuously and contextually – will be critical in a world where work is constantly shifting. Learning must be designed to foster curiosity, decision-making and meaningful human contribution in AI-enabled environments.

To lead through this transition, organisations should embrace the following principles:

• Educate executives on agentic AI as a systems-level reinvention, not a toolset
• Prototype new human-agent roles, workflows and teaming models through live business-led pilots
• Design agile workforce architectures, enabling flexible role evolution, cross-functional mobility, and adaptive talent sourcing
• Plan for the workforce changes thoughtfully by implementing strategic workforce planning and skills insights capabilities that will enable visibility and agility
• Elevate learning as a core capability, investing in methods that cultivate curiosity, judgment, and hands-on experimentation
• Link AI reinvention to trust, culture, and long-term value, recognising that transformation will not come from the bottom up. Leaders must actively set direction, provide visible sponsorship, and create the conditions for change, even when it challenges traditional models of work.

PwC’s Value in Motion³ research underscores that value is not only shifting – it is accelerating toward those who lead in structural reinvention. The potential US$27 trillion in added global GDP by 2035 will not be realised through efficiency gains alone. It will go to those who redesign their workforces, reimagine their business models, and cultivate human potential in step with technological change.

Agentic AI has the power to fundamentally reshape how organisations operate, but that transformation will not unfold automatically. Without deliberate reinvention – of roles, workflows and processes, leadership models, and learning systems – these technologies risk being implemented through outdated structures, delivering efficiency without resilience and automation without adaptability.

The future of work is being rewritten across multiple dimensions. People are working longer, career paths are less linear, and workforce expectations are evolving in real time. At the same time, AI is progressing faster than most organisations can restructure around it. This convergence requires a new approach – one rooted in agility, inclusion, and strategic imagination. Reinvention is not just about protecting relevance. It is about actively designing the next era of human and organisational contribution.

The current trajectory reveals a clear risk: we are dismantling more than we are building. We are displacing roles faster than we are defining what should come next. But this gap is not inevitable – it is a leadership choice. The organisations that will thrive are those that invest now in new role creation, new teaming models, new career pathways, and new ways of building capability and trust.

Reinvention will not happen passively. Left alone, organisations will default to incremental automation, not transformation. This moment offers leaders a unique opportunity to shape the future – by setting direction, making deliberate choices and championing reinvention as both a strategic and cultural necessity. Without that leadership, the risks are clear: efficiency gains without resilience, and automation without adaptability.

Leaders may want a playbook, but reinvention does not lend itself to fixed scripts. There is no one-size-fits-all manual – instead the path forward will require a willingness to experiment, learn and adapt together. This path needs to be grounded in the principles of agility, learning and trust. The future has uncertainty but those who act with curiosity, clarity of purpose and adaptability will help shape what comes next.

The solution is not to slow AI down. It is to speed up our collective capacity to imagine, design, and guide meaningful change. Reinvention is no longer optional. It is the operating requirement for the intelligent era.

References

^{1. PwC. (2024). Business Model Reinvention: A New Approach to Value Creation.}

^{2. PwC. (2024a). Hopes and Fears 2024: The Worker’s View.}

^{3. PwC. (2024b). Value in Motion: Capturing Growth in a Time of Disruption.}

^{4. Wood, M. (2025). Both, And: Leading Cultural and Technical Change with AI.}

^{5. Accenture. (2024). AI in the Enterprise 2024 Report.}

^{6. World Economic Forum. (2023). The Future of Jobs Report 2023.}

^{7. Brynjolfsson, E., Li, D., & Raymond, L. (2024). Generative AI at Work. Stanford Digital Economy Lab & MIT Sloan School of Management.}

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