# Talent Reinventors

## Authors

**Karalee Close** Global Lead, Talent & Organization, Accenture

**Stephen Wroblewski** Global Talent Lead, Talent & Organization, Accenture

**Jessica Van Singel** Global Resources Industry Group Lead and Americas Strategy Practice Lead, Talent & Organization, Accenture

**Sumreen Ahmad** Managing Director, Middle East, Talent & Organization, Accenture

**Mamta Kapur** Senior Principal & Europe Research Lead, Talent & Organization, Accenture Research

"The future of AI and companies is human in the lead, not just in the loop."

— Julie Sweet, Chair and CEO, Accenture

## Introduction

The last few years have revealed AI's enormous potential and a simple truth: Real value shows up when people and technology advance together.

As AI adoption accelerates, returns are uneven. Many organizations are investing heavily in AI, but have not updated their talent strategy accordingly.

Our latest research uncovers new opportunities to deliver innovation with talent. We surveyed 1,320 C-suite executives and 4,560 employees across 20 industries and 12 countries between August and September 2025 and found an elite group—just 18% of organizations—that are taking a different approach to talent and delivering real value.

We call them Talent Reinventors.

Compared to their peers, Talent Reinventors are 7x more likely to strengthen organizational culture, 6x more likely to improve employee experience, and 4x more likely to enhance workforce adaptability. They also report an 11% uplift in innovation-related skills. Those gains can drive real value: Decades of academic research show that adaptive culture, psychological safety and innovation readiness are among the strongest predictors of long-term financial performance.[^1]

Talent Reinventors prove the point. According to our research, this group of companies grew revenue 1.8 percentage points higher and grew profit 1.4 percentage points higher than their peers in 2025.

### Research snapshot

We surveyed:

- 1,320 C-suite executives and 4,560 employees

- across 20 industries and 12 countries

### Key insight

**18%** of organizations studied—Talent Reinventors—are delivering real value.

See About the Research at the end of this report for details on our methodology. Unless otherwise noted, all data included in this report is from this study.

## Outcomes

**Talent Reinventors are:**

- **4x** More likely to improve workforce adaptability

- **7x** More likely to strengthen organizational culture

- **6x** More likely to create great employee experiences

**In 2025, they experienced:**

- **1.8%** Higher revenue growth

- **1.4%** Higher profit growth

- **11%** Uplift in innovation skills

What sets these organizations apart is a distinctive and more integrated approach to talent—a human+ AI talent strategy—that reshapes work and the workforce around a shared set of goals.

This strategy is powered by AI and data, but its purpose is deeply human: to reinvent what and how work gets done and help people grow their careers.

It gives organizations unprecedented visibility into which tasks deserve focus, which skills will matter next and how people and technology can elevate each other's performance.

This report breaks down six characteristics that are shared by Talent Reinventors. Together, these characteristics allow them to build a workforce that drives value by helping people unlock new potential with technology.

### Talent Reinventors share six characteristics that create value

Talent Reinventors share six characteristics that create value for their organizations by continually redesigning work and reshaping the workforce to align around shared goals and emerging opportunities. They enable people and technology to grow, contribute and thrive together.

## The six characteristics of Talent Reinventors

- Clarity

- Intelligent teaming

- Talent mobility

- Co-learning

- Breakthrough leadership

- Personalized experiences

Taken together, these six characteristics represent a new mindset for leaders in the AI era and provide a framework for building a workforce of the future:

| Clarity | Intelligent teaming | Talent mobility | Co-learning | Breakthrough leadership | Personalized experiences |
| --- | --- | --- | --- | --- | --- |
| Creating a common view of value across talent, technology and strategy to focus on measurable outcomes | Using AI to understand team health, skills and performance, giving leaders greater visibility into workforce capabilities, needs and potential | Placing people where they are most needed based on business strategy, skills and emerging roles | Enabling people and AI to evolve together in the flow of work | Cultivating leaders who prioritize coaching over control, lead with humility, elevate human potential and create a culture of curiosity | Creating tailored career development and learning pathways anchored in meaningful work, for every employee |

Most organizations have strengths in some of these areas and gaps in others. What sets Talent Reinventors apart is their effort to strengthen each characteristic and, concurrently, knit all six together. By focusing on progress over perfection, they create more integrated talent foundations that support the needs of today and the vision for tomorrow.

## Clarity

Alignment across functions allows a single definition of value and shared priorities to create a north star for reinvention.

In most organizations, different functional areas set their own goals and priorities, often working in silos with little cross-functional interaction. Inevitably, upskilling and technology adoption advance at different rates, creating gaps that prevent teams from working together toward shared goals.

Only one-third of the respondents to our survey indicated their talent strategy is fully aligned with their technology and AI strategy. This misalignment makes it difficult for organizations to capture value from AI, let alone scale it.

The consequences are increasingly visible at the employee level. Only 24% report having full access to AI tools, just over one in five strongly agree that experimentation with AI is rewarded and only 21% feel they have a voice in how AI is introduced.[^2]

When access, permissions and expectations are unclear, agency erodes and progress stalls. This lack of clarity also undermines confidence and trust. While many leaders express empathy for workforce concerns, that empathy is not translating into confidence or alignment: only 18% of employees strongly agree that leadership has clearly communicated how the organization will navigate change in 2026.[^3](Ibid.) Without a credible roadmap, reassurance rings hollow and the confidence gap between leaders and employees continues to widen.

"AI has exposed the gap between how fast the business and technology are evolving and how slowly talent systems adapt. Workforce planning was once static; now skills and roles are shifting in real time, and alignment remains partial."

— Senior Technology Leader, Global Energy Company

Talent Reinventors, in contrast, bring teams together around shared priorities. This alignment sharpens talent decisions—clarifying how roles evolve, which skills to scale and what training is required. By aligning HR, technology, data, operations and business functions, Talent Reinventors see measurable improvements in areas like growth, innovation, revenue, costs, productivity, workforce agility and time to market.

That same clarity benefits the organization and its people, helping employees advance their skills and careers—and motivating them to embrace the technology that's making it possible. AI and data integration is key, providing visibility into workflows so Talent Reinventors know what's working, which processes need to be improved and where value is really being created.

Almost all Talent Reinventors (96%) have a talent strategy that is fully integrated with technology and AI through strong HR and IT collaboration. And although AI adoption is a priority at many organizations, 93% of Talent Reinventors are actively redefining talent strategy to support AI adoption, including operating model shifts. Meanwhile, 76% of Talent Reinventors use AI-enabled systems to dynamically adjust goals in real time. They are 7.6x more likely to ensure that employees are doing work that matters and aligns to evolving business goals.

**Case in point:** Volkswagen Group is in the midst of a reinvention shaped by a clear ambition: to evolve from a traditional automaker into a global automotive technology leader. Central to this journey is the belief that AI must become an enterprise capability—embedded into how vehicles are designed, how factories are run and how people work—rather than a series of isolated pilots.[^4]

To support this ambition, Volkswagen is bringing its teams and systems together by using shared platforms, common data foundations and coordinated governance. Initiatives such as its Digital Production Platform are designed to connect factories globally, delivering AI-enabled insights, quality improvements and efficiency gains across brands and regions.[^5]

Talent is a defining pillar of the transformation. Through its WE & AI initiative, launched in 2024, Volkswagen has established one of its largest internal education and qualification programs to date.[^6] The initiative is designed to enable employees at all levels to engage with AI responsibly and practically, reinforcing the idea that AI literacy is an enterprise expectation, not a niche technical skill. More than 130,000 employees worldwide have already been reached, signaling a cultural shift toward human-AI collaboration.

Volkswagen is also strengthening its ecosystem through its globally networked AI Lab, regional engineering hubs and partnerships that expand access to data, engineering and AI capabilities, aligning talent pipelines with technology delivery to accelerate learning and skills development.[^7]

Together, these moves signal a transformation still underway: one focused on clarity of intent, disciplined scaling and the deliberate design of an operating model built for innovation, resilience and long-term competitive advantage.

### What Talent Reinventors are getting right

**HR, IT and the business share objectives** 96% have a talent strategy that is fully integrated with technology and AI, versus 16% of others.

**Talent strategy supports AI adoption** 93% have actively redefined their talent strategy to support AI adoption, including operating model shifts, versus 18% of others.

**Dynamic goal-setting drives value** 76% use AI-enabled systems to dynamically adjust goals in real time, versus 10% of others.

## Intelligent teaming

Human-AI pairing provides deep insights into skills, team dynamics and human potential, helping organizations create stronger teams and new ways of working.

As AI becomes embedded in daily workflows, teams—not just individuals—are increasingly using data and insights to strengthen execution, innovation and decision-making.

Work is becoming more fluid, spreading across functional areas and technology platforms, so it's crucial that organizations help teams adapt their ways of working together. Most organizations are not there yet.

Only 19% of employees say they work in teams that experiment with AI and digital tools to develop, learn and improve together. And only 17% of employees feel psychologically safe speaking up or sharing ideas within their teams, a barrier that erodes collaboration and innovation.

Today, only 25% of C-suite executives use advanced AI analytics to track team collaboration and measure innovation. Talent Reinventors are the exception, making AI's role in the workflow explicit and enabling people to see how their work evolves alongside technology. They are 1.6x more likely than peers to track behavioral adoption with advanced AI tools. They also leverage AI-generated matching to assess team fit, guide assignments and proactively flag risks such as burnout or exclusion, using data not just to monitor performance, but to strengthen team health and judgment (Figure 1).

### Figure 1: Talent Reinventors use AI to elevate team judgment and effectiveness

| Category | Talent Reinventors | Others | Multiplier |
| --- | --- | --- | --- |
| Use AI-generated matching to assess team fit, guide assignments and flag risks | 84% | 49% | 1.7x |
| Say AI enhances collective judgment | 25% | 9% | 2.8x |
| Prioritize emotional intelligence and AI fluency | 55% | 33% | 1.7x |

Source: Accenture talent reinvention CXO survey, 2025 (N = 1,320)

"A clear, company-wide plan for AI would make a real difference. Right now, teams are moving at different speeds, using different tools, and largely figuring things out on their own. A shared direction would help teams learn and grow together and lift the organization as a whole."

— Marketing Manager, Health and Nutrition, Global Chemicals Company

By tapping into a continuous flow of data, Talent Reinventors better understand what their people need to feel safe and valued, and they tailor experiences accordingly.

Compared to peers, their teams are healthier, with 75% reporting reduced stress and improved well-being. They are 1.5x more likely to say AI improves skill development and 1.7x more likely to prioritize emotional intelligence and AI fluency, with 55% citing both skills as important. Using AI and data, they have the insights they need to understand how teams are functioning today and how humans and AI can collaborate better tomorrow.

"We collect continuous employee feedback through [our] organization health survey, 360-degree assessments, and sentiment analysis from team interactions. With [Microsoft] Copilot embedded in Teams, leaders can access real-time sentiment reports."

— Neha Donald, Director, Global Transformation Strategy & Innovation, PepsiCo

**Case in point:** When Microsoft undertook a large engineering reorganization, its leaders needed a sharper understanding of how—and how well—their teams were working together. Acting as "customer zero," they used their own AI-enabled employee engagement platforms, Microsoft Viva Insights and Microsoft Viva Glint, to capture key intelligence.[^8] These platforms apply machine learning and organizational network analytics to millions of collaboration signals in emails, meetings and Microsoft Teams chats and combine them with sentiment data to see how information flowed before and after the re-org. They were able to see which teams became too insular or were overstretched after restructuring and where cross-team collaboration increased or dropped off, enabling them to adjust team design, clarify roles and target support faster than traditional methods allowed.

Their teams now use Viva Insights to align on things like meeting-free days, focus-time blocks and agreed collaboration hours, and track whether those norms improve well-being and productivity for their people. By creating a continuous feedback loop where AI-enabled analytics amplify human judgment, Microsoft team leaders now spot issues early, align cross-functional work and build healthier, stronger teams.

### What Talent Reinventors are getting right

**Human-AI collaboration boosts team performance** Talent Reinventors are 1.5x more likely to report faster, higher-quality team decision-making and 2.8x more likely to say AI meaningfully enhances collective judgment.

**Trust and connection are stronger** Talent Reinventors create environments where AI enhances teams' interpersonal relationships. They are 1.8x more likely to report stronger trust and human connection.

**AI improves team health** Talent Reinventors are 1.7x more likely to say human-AI collaboration reduces stress and improves team well-being, a critical foundation for sustained performance.

**Data drives team design** Talent Reinventors are 1.7x more likely to use AI-generated matching for role fit, assignments and burnout detection, and 1.4x more likely to use team health data to guide coaching and remove friction points.

**AI accelerates upskilling** Human-AI collaboration helps teams build skills faster. Talent Reinventors are 1.5x more likely to say that AI strengthens skill development.

## Talent mobility

Highly adaptable workforces create more opportunities for people to do meaningful work, delivering value for the organization while driving career growth.

Many organizations lack the visibility into their workforce that would allow them to match the right people with the right opportunities. Without this visibility, they may end up hiring and training external resources when the talent they need can often be developed in-house.

In fact, 69% of organizations still rely on external hiring or limited, ad hoc internal hiring with little visibility into skills or career pathways. Internal mobility remains largely disconnected from any data-driven talent strategy—only 7% of organizations use AI-enabled platforms to power an internal-first mobility strategy.

Employees recognize the challenge. Forty-five percent say it's difficult to find internal roles, projects or learning opportunities, and 76% report that career pathways are unclear. Asked what would most accelerate their careers in the next one to two years, employees prioritize targeted training to build future-relevant skills (56%), clear internal pathways (34%) and greater autonomy and flexibility (30%).

Figure 2 highlights the scale of this gap. Talent Reinventors are 16.5x more likely to have dynamic, AI-informed skills data embedded in their workforce systems. They use AI to create a living, continuously updated inventory of employee skills, capabilities and interests across the enterprise.

This gives leaders the visibility to match people to opportunities with greater precision—and to help them develop skills for future roles, not just roles that already exist.

### Figure 2: Talent Reinventors lead with dynamic, AI-powered skills visibility

| Category | Talent Reinventors | Others | Multiplier |
| --- | --- | --- | --- |
| Dynamic, AI-informed skills data embedded | 44% | 3% | 16.5x |
| Real-time, AI-driven platforms to match internal and external skills | 66% | 20% | 3.3x |
| Prioritize internal hiring with AI platforms to match employees to roles and learning opportunities | 88% | 12% | 7.2x |

Source: Accenture talent reinvention CXO survey, 2025 (N = 1,320)

"Our internal job marketplace is fundamentally broken. We have hundreds of internal postings that are unattended, redundant or just not meant to be applied by internal applicants, creating friction instead of opportunity. This requires a complete rethink."

— Demand & Market Planning Manager, Global Consumer Goods Company

Our research shows that Talent Reinventors are 4.4x more likely than peers to build an adaptable workforce that can shift quickly across roles. They are 8x more likely to use AI-powered platforms to adjust goals and match people to opportunities in real time, ensuring that skills stay aligned with shifting business needs and creating more career opportunities for the existing workforce. This matters even more as younger generations enter the workforce.

By targeting skills development where it matters most, Talent Reinventors are creating career pathways that feel attainable and support smoother transitions into meaningful, future-ready roles. They're helping employees pursue opportunities that fit their skills and ambitions, creating environments where people feel more fulfilled and can do meaningful work that advances their careers. The result is a workforce that pivots quickly, stays engaged and is far less dependent on external hiring.

Talent Reinventors are 4.4x more likely to have an internally mobile workforce that can pivot to different roles or teams as new challenges and opportunities arise.

**Case in point:** For more than a century, Caterpillar has been synonymous with heavy equipment and industrial engineering. Today, however, the company is redefining itself—not only as a manufacturer but as a digitally-enabled solutions provider. Workforce mobility is at the heart of this evolution. So, in 2025, Caterpillar committed $100 million over five years to upskill and retrain its workers with a focus on digital, automation, artificial intelligence and advanced technical capabilities.[^9]

This investment represents a deep commitment to talent at Caterpillar. The company's leadership is preparing employees for "what comes next," an essential strategy for creating quality jobs and sustaining manufacturing competitiveness. Rather than relying primarily on external hiring to secure digital skills, Caterpillar is investing in its existing workforce—creating structured pathways for employees to transition into emerging roles.

AI is both catalyst and context for this shift. At CES 2026, Caterpillar unveiled its Cat AI Assistant, a generative AI-powered solution that translates equipment data into actionable insights.[^10] Designed to enhance customer value, this innovation requires new competencies in data interpretation, AI oversight and digital systems integration.[^11] As these types of AI capabilities expand across Caterpillar's product and service offerings, the company is concurrently advancing workforce mobility by clearly defining future skill requirements, offering workforce development programs to build skills internally, and redeploying talent into AI-enabled growth areas. This evolution also extends to technician apprenticeships, manufacturing academies and partnerships with educational institutions focused on robotics, automation and digital manufacturing.

These types of programs enable Caterpillar employees to move laterally and vertically into higher-skill roles that align with the company's evolving business needs. It represents a broad strategic shift from job-based workforce planning to skills-based mobility, demonstrating that even in heavy industry, talent mobility can be a strategic engine for sustained competitiveness in an AI-enabled future.

### What Talent Reinventors are getting right

**Skills visibility opens opportunity** Talent Reinventors are 16.5x more likely to have deep visibility into current and emerging skills, enabling employees to pivot into roles that enhance both career growth and business value.

**AI powers internal talent flow** They are 3.3x more likely to match internal and external candidates to roles in real time using predictive AI, keeping talent aligned to shifting priorities.

**Internal mobility becomes a growth engine** Talent Reinventors are 7.2x more likely to hire from within, preserving institutional knowledge and maximizing returns on upskilling investments.

**AI transforms recruiting and retention** 59% use AI to assess large candidate pools for skills and fit—making them 1.3x more likely to hire people who succeed and stay.

"The focus has shifted from job security to skill security. Our AI Career Copilot helps employees build capabilities, find mentors and access personalized development … creating a skills-first, AI-augmented workforce that can match people to opportunities at speed."

— Managing Director, Fortune 500 Bank

## Co-learning

People and AI evolve together in the flow of work, learning from each other to reach their full potential.

Employees and executives agree that AI and data fluency are the top skills employees must develop in the next one to two years—yet most organizations lack the systems, time and support to help people build these capabilities.

Among employees, only 19% strongly agree they have the skills they need to succeed with AI. Figure 3 shows how this plays out across learning environments. Only one in four executives say learning is truly embedded in their organization's culture and workflows, and just 36% use real-time AI nudges frequently to motivate employees. While 86% of firms plan to increase AI spending, only 43% plan to upskill their people.[^12]

Their people are not waiting. According to our Pulse of Change report, 32% of employees say they regularly work with AI agents, up significantly over the past year. Clearly, access to the technology is increasing—but fluency and confidence are not keeping up. Just 27% of employees strongly agree they are comfortable delegating tasks to AI.[^13](Ibid.) That gap will close only when learning is fully embedded in the flow of work.

### Figure 3: Only one in four organizations embed learning into daily workflows

| Category | Percentage |
| --- | --- |
| Little or no structured learning | 5% |
| Learning is available but limited | 24% |
| Learning is linked to development goals but still limited | 46% |
| Learning is embedded in culture and workflows | 25% |

Source: Accenture talent reinvention CXO survey, 2025 (N = 1,320)

"My biggest challenge isn't access to AI tools—it's the lack of practical, role-specific training to apply them in everyday work. Without clear guidance, many tools fall short of their potential."

— Technical Specialist, Software and Platforms

Employees feel the strain. While 86% have had positive experiences working with current AI tools (Figure 4), 50% report being too busy to build new skills and 46% say limited organizational support or leadership buy-in prevents them from learning effectively. Learning itself remains fragmented: 52% of employees say learning is tied to development goals but not personalized, and in most organizations, it still occurs outside the flow of work.

Many employees simply do not know where to start their learning journey: 36% cite unclear learning pathways as a barrier to upskilling and 35% say this lack of guidance is a key reason they struggle to learn and progress.

And yet, employees are not waiting. They are already capturing value through hands-on use of AI: 68% say AI saves time on routine tasks, nearly 59% say it improves work quality and 31% now use AI primarily because it helps them work faster or more efficiently.[^14]

Adoption is increasingly performance-driven, not experimental. This reveals an important truth: people learn most effectively with AI while doing their jobs—not through formal training alone.

### Figure 4: Employee sentiment toward gen AI is largely positive

| Sentiment Category | Percentage |
| --- | --- |
| Generally positive | 46% |
| Integrated and enabling | 28% |
| Empowering and intuitive | 12% |
| Employee-driven, but misaligned | 6% |
| Minimal exposure | 5% |
| Inconsistent and siloed | 2% |
| Frustrating or ineffective | 1% |

Source: Accenture talent reinvention employee survey, 2025 (N = 4,560)

### Closing the AI skills gap

Talent Reinventors embed co-learning in workflows, creating deep relationships where humans and AI continuously learn and adapt to one another. For example, co-learning can look like two teammates handling a call together, with a human representative in the lead and an autonomous AI agent listening and providing recommendations in the background. As the rep speaks, AI transcribes the dialogue and provides compliant, next-best responses in real time. When the rep edits a phrase, skips a prompt or rates a suggestion, AI treats that as feedback—retraining its guidance for future calls. Thus, every human-AI interaction becomes a capability-building moment that strengthens individuals, teams and AI systems.

Since hands-on learning is most effective, Talent Reinventors create "development playgrounds" that encourage experimentation. Our research shows that organizations that create the conditions for human-AI co-learning see 5x higher workforce engagement, 4x faster skill development, 8x greater trust in leadership and 2x higher confidence among workers in adapting to AI. Yet today, only 11% of organizations have created these conditions.[^15](Ibid.)

"Close to 9,000 associates actively use our AI Playground daily… a safe environment to experiment that's become the gateway to comfort with AI."

— Senior Tech Transformation Expert, Fortune 500 Energy Company

**Case in point:** Leaders at global pharmaceutical company Merck & Co., known as MSD outside of the United States and Canada, wanted employees to master AI by getting practical experience working with the tools. With more than 75,000 employees in more than 140 countries, they needed a nuanced approach that could work across cultures, disciplines and teams. So they embedded AI literacy and human–AI collaboration into daily workflows on their enterprise AI platform, GPTeal.

Today, more than 80% of its workforce uses its proprietary AI platform to automate, simplify and digitize processes.[^16] The gains have been particularly evident in the organization's knowledge-intensive domains, such as clinical R&D, where teams now use gen AI to draft clinical study reports to reduce average time from 180 hours to 80 hours while reducing documentation errors by around 50%.[^17]

Further savings accrue from routine tasks: if each knowledge worker saves even 30 minutes per week on document editing, across 50,000 users that is ~25,000 hours weekly. Across the organization, these savings allow scientists, analysts and teams to focus on higher-value problem-solving and innovation.[^18]

Importantly, the company's leadership frames AI knowledge and co-learning as a cultural imperative and supports it with AI- and data-led professional development. Employees and team leaders have access to advanced learning platforms for continuous skill-building, role discovery, mentoring and analytics to help them drive their careers forward.

### What Talent Reinventors are getting right

**Learning is embedded in the flow of work** 92% of Talent Reinventors embed learning in daily work, making them 8.5x more likely to treat upskilling as a habit, not an event.

**AI accelerates personalized development** 84% use AI to tailor learning and career pathways, making them 1.3x more likely to personalize growth at scale.

**Nudges sustain progress** 73% use real-time AI nudges to keep people moving along their learning journeys, 1.7x more than peers.

**People are skilled for the future** With adaptability and AI fluency as cultural norms, employees feel more future-ready: 48% feel secure in their jobs and 46% find AI tools genuinely helpful in their daily work.[^19]

## Breakthrough leadership

Leaders prioritize coaching over control, leading with humility and elevating human potential.

Expectations in the workplace are changing quickly (Figure 5). Employees now expect their company's leaders to support new career pathways and reskilling (29%), provide more transparency and inclusion in decision-making (28%) and protect individual dignity and respect in how work is designed (24%).

Organizations that meet those expectations have a tremendous opportunity to forge strong bonds with their people and distance themselves from peers. This is where Talent Reinventors excel.

Their C-suites have high levels of technical fluency so leaders understand the work being done, how it can be improved with AI and how to guide their teams. They model the behaviors needed for a human-AI workforce, reflecting a global trend among C-suite leaders: Our Pulse of Change report shows that 32% of executives now use AI tools in their daily work, up from just 8% in March 2024.

### Figure 5: AI adoption is driving new expectations for how leaders design work and develop people

| Category | Percentage |
| --- | --- |
| Desire for more flexibility in roles and responsibilities | 34% |
| Leaders expected to uphold dignity and respect in work design | 26% |
| No significant change | 19% |
| Increased demand for transparency and inclusive decision-making | 17% |
| Greater focus on career development and reskilling | 4% |

Source: Accenture talent reinvention employee survey, 2025 (N = 4,560)

In their daily work with AI tools, these leaders help drive adoption and confidence with their employees. And by fully understanding the technology and its impacts on their people, they bring empathy to their teams and are better equipped to address the emotional strain of the transition to a human-AI workforce.

Strategic hiring helps them build on that momentum. Nearly half (49%) of the leadership job postings for Talent Reinventors require AI and machine learning skills, far surpassing their peers.[^20] By pairing curiosity and continuous learning with ethical uses of AI, Talent Reinventors are developing leaders who coach more than command, lead with humility and involve their teams in shaping the work. They share their learning experiences—the wins as well as the failures—building trust and nurturing a culture of experimentation.

Talent Reinventors lift up their teams—creating environments where people can do meaningful work, thrive alongside AI and fulfill their personal and professional ambitions.

"If my organization could change one thing, it would be to build a culture that values the intelligent use of AI—seeing it as innovation, not just a tool. With that kind of appreciation, I feel motivated to experiment, more confident in my abilities and reassured that my expertise still matters."

— Senior Solutions Architect, IT Services Company

"Leadership is shifting from a directive style toward one that is more facilitative—helping teams interpret AI-generated insights and complex data. Leaders are also emphasizing the importance of data-informed decisions, using real-time dashboards, predictive modeling and AI agents to embed data into everyday decision-making."

— Senior Director, Strategic Partnerships & GTM Strategy, Sanofi

**Case in point:** BASF Group is redefining leadership as a strategic capability for an environment of constant change. That means treating leadership not as a role or a trait, but as a core strategic imperative—one designed to operate under constant change. Under its Winning Ways strategy, the company fundamentally reset what leadership means across a global organization of more than 111,000 employees.[^21] At the core of its approach is a shared, enterprise-wide standard for effective leadership, signaling a decisive shift: adaptability, accountability and execution are no longer optional qualities or personal strengths, but capabilities the organization expects to build consistently and deliberately at scale.

This reset represents a breakthrough in how leadership is understood and deployed. By making leadership explicit, observable and teachable, BASF moved it out of the realm of abstraction and into the operating model of the company. Leadership became less about who you are and more about how you lead—creating a common language that enables alignment, faster decision-making and coordinated action across regions, functions and levels.

To ensure this standard could be lived, not just stated, BASF paired clarity with development at scale. Its Leadership Essentials framework provides a consistent foundation for feedback, performance coaching and growth, while immersive programs rolled out in the organization's divisions—such as Activate and Connect for Growth—focus senior leaders and emerging talent on navigating complexity, leading through change and driving impact across global teams.[^22] Together, these types of programs support leadership as a repeatable discipline rather than a one-time intervention or episodic training effort.

The result is a leadership model designed for continuous reinvention. By embedding leadership expectations into systems, development pathways and everyday behaviors, BASF is building an organization where leaders are equipped to guide transformation as an ongoing capability—strengthening shared accountability, reinforcing engagement and enabling the company to execute through uncertainty with coherence and confidence.

### What Talent Reinventors are getting right

**Lead with humility and purpose** They are 1.9x more likely to foster dignity and respect, involving teams in defining roadmaps and encouraging exploration.

**Prioritize culture** 67% treat culture as a strategic asset and are 1.8x more likely to actively measure and adapt their culture to create better outcomes.

**Use AI to build stronger and healthier teams** They are 1.4x more likely to invest in development, well-being and inclusive practices and 1.5x more likely to use AI insights to inform decisions.

**Focus on lasting growth over short-term outputs** They are 1.3x more likely to delegate, develop and coach talent—even if it slows execution—signaling that building capability matters more than short-term output.

**Communicate with empathy and clarity** They design communication and experiences to reduce fear and build trust—an important consideration since 55% of employees are experiencing cognitive overload and 49% are anxious about job displacement.

**Lift up teams** They are 6.8x more likely to positively shape culture, 4.7x more inclusive and 6.1x more likely to create strong employee experiences, leading to a 40% reduction in turnover.

## Personalized experiences

Tailored experiences make day-to-day workflows more engaging so individuals thrive and innovation flourishes.

Many organizations still rely on a one-size-fits-all approach to career development that does not address individual strengths or aspirations. The consequences are visible across the workforce: employees feel limited in their careers, disconnected from meaningful work and increasingly overwhelmed by the pace of change.

More than one-third say they spend most of their energy simply adapting to constant change and 20% report feeling undervalued. Only about one-third strongly believe their employer is committed to helping them stay relevant—or will act in their best interest as new technologies are introduced. Without personalized guidance and transparent pathways, reinvention feels like something being done to employees rather than with them.

Figure 6 shows that more than half of C-suite executives report cognitive overload within their workforce as employees struggle to manage rising complexity in their work. Nearly as many leaders observe anxiety about job displacement. Others experience burnout (31%), a reduced sense of dignity in their work (26%) or a loss of agency in decision-making (23%). These are not just numbers or marginal sentiments. They expose a widening disconnect between the promise of AI and the lived reality of people expected to use it.

### Figure 6: The emotional toll of AI adoption on the human workforce

| Emotional Toll | Percentage |
| --- | --- |
| Cognitive overload or difficulty managing new complexity | 55% |
| Anxiety about job displacement | 49% |
| Burnout or signs of emotional exhaustion | 31% |
| Reduced sense of dignity or respect in their work | 26% |
| Loss of agency or autonomy in decision-making | 23% |

Source: Accenture talent reinvention CXO survey, 2025 (N = 1,320)

"We focus on personalized, predictive career conversations backed by AI systems. The (talent) platform we use integrates employee aspirations, performance data, and organizational needs into a single view. Employees can access self-service tools that suggest career moves and connect them with targeted learning resources."

— Data Science & Analytics Leader, Fortune 100 Technology Company

Talent Reinventors address this gap by focusing on individuals and using AI to make professional development deeply personal. By combining workforce data on performance, emerging skills and employee preferences, they can tailor development in ways that were never possible before. Employees receive clearer guidance on where they can grow, what skills will open new opportunities and how learning connects to the work they do.

Talent Reinventors also personalize their communication with employees to make it relevant and timely. They listen to employees and build real-time feedback loops—the cornerstone of all improvement—so people are informed and know that they are heard and that their views matter.

By providing clearer line-of-sight to career opportunities and personalized guidance and development support, they strengthen confidence and reinforce a sense of belonging for their people. And by providing tailored reminders and personalized suggestions for development, they give their employees the nudges they need to grow their skills in a way that's meaningful to them and the organization. When people can see their path and believe the organization is invested in their future, they are far more likely to grow with the business.

**Case in point:** When Accenture set out to reinvent work in the age of AI, it focused on people and processes, then tools, across an enterprise of over 780,000 people in 120 countries. Embedding the talent strategy in the business strategy has given leaders the clarity to use AI effectively—through experiences and new ways of working that keep humans in the lead.

Setting the stage for everything to come, Accenture started their talent reinvention journey by implementing a single, global digital core which integrated data across historically fragmented systems. Next up was becoming a skills-driven organization. The company built an AI-powered skills engine designed to ensure the right skills are in the right place at the right time. The platform empowers people to shape their own skills profiles, explore areas of interest and drive their careers forward. Leaders are armed with real-time, AI-driven insights to predict future skill needs and reskill at scale to grow the business and their teams.

This people-first approach is underpinned by Accenture's $1B annual investment in learning, a robust AI and agentic learning roadmap for all their people, and an AI and Data workforce now nearing 80,000.[^23][^24]

Building on this strong foundation, Accenture is focused on accelerating AI across the business as they reinvent the work and their workforce. Accenture's Talent Navigator—an AI-powered workforce intelligence platform—gives leaders visibility into work by breaking jobs into tasks, linking each to skills, cost and value—enabling the company to rethink roles and the work for a human+ world.

These things, along with a culture of listening, continuous feedback, progress over perfection and growing leaders who drive change at every level, all contribute to Accenture's consistently high ranking among the world's best places to work.

### What Talent Reinventors are getting right

**Personalized employee experience** 65% use AI to improve employee experience and engagement and are 1.3x more likely to make development journeys more accessible and tailored.

**Building confidence in future-readiness** 57% are confident in their workforce's AI capabilities and 41% believe their organizations are fully equipped to upskill for an AI-driven future.

**Recognizing and rewarding employee growth** 71% publicly recognize employee contributions on a regular basis, creating positive experiences that drive growth and encourage ownership.

## The barriers to reinventing talent

Few C-suite leaders remain unconvinced about the promise of AI to improve their business. Most are already using it in some form across all talent functions or plan to deploy it within the next two years (Figure 7).

Yet for most organizations, significant barriers stand in the way to achieving the full potential of AI. Teams have trouble scaling AI efficiently. Roles and skills are mapped to legacy processes. Business priorities target short-term goals versus longer-term restructuring. Cultures reflect deep-seated preferences for doing what has worked in the past.

While adoption is quickly accelerating, so are the barriers to value creation.

### Figure 7: AI adoption is expanding across all talent functions

| Talent function | Type | Currently using | Planning to implement |
| --- | --- | --- | --- |
| Talent Acquisition | AI/gen AI | 48% | 47% |
| Talent Acquisition | Agentic AI | 67% | 22% |
| Learning & Development | AI/gen AI | 28% | 68% |
| Learning & Development | Agentic AI | 50% | 41% |
| Internal Mobility | AI/gen AI | 61% | 33% |
| Internal Mobility | Agentic AI | 62% | 18% |
| Performance Management | AI/gen AI | 37% | 60% |
| Performance Management | Agentic AI | 51% | 36% |
| Employee Experience | AI/gen AI | 44% | 53% |
| Employee Experience | Agentic AI | 58% | 32% |

Note: Percentages do not total 100% as the chart excludes the "no plans to implement" category. Source: Accenture talent reinvention CXO survey, 2025 (N = 1,320)

### Figure 8: Fragmented systems and limited skills visibility are slowing progress

| Barrier | Percentage |
| --- | --- |
| Fragmented systems & outdated roles | 54% |
| Limited visibility into current and future skills needs | 47% |
| Conflicting priorities & short-term goals | 39% |
| Lack of leadership sponsorship/accountability | 36% |
| Cultural inertia | 34% |
| Low risk tolerance | 31% |
| Weak mobility, learning pathways or feedback loops | 30% |
| No or limited HR digital strategy | 10% |

Source: Accenture talent reinvention CXO survey, 2025 (N = 1,320)

In our research, we heard from managers and team members who are eager to embed AI into their daily workflows but are struggling to overcome common foundational barriers (Figure 8). For their organizations, adoption does not translate into sustained value.

Most organizations (54%) struggle with fragmented systems and legacy role structures, which can prevent AI from being embedded end-to-end across workflows, limiting performance of humans as well as AI tools. Visibility into workforce skills—both current and future—is also limited for nearly half (47%), making it difficult to deploy technology in a way that fills gaps and complements human capabilities. Conflicting priorities and short-term performance pressures further constrain progress for 39%, while 36% cite inconsistent sponsorship at the top of the organization. For these organizations, new technologies often shine in isolated pilots but seldom convert into sustained, enterprise-wide initiatives.

Roughly one-third of managers and team members say that cultural inertia and low risk tolerance factor into their ability to experiment—the very mechanism through which AI and people improve over time. Operational weaknesses in role mobility, learning pathways and feedback loops further compromise their ability to advance as quickly as the technologies they're using.

Talent Reinventors get past these and other barriers by tackling them head-on. For any organization intent on drawing full value from AI, the following actions are a good place to start.

## Actions to take now

### Reinvent talent strategy with an AI-powered approach

The old model of siloed systems and functions simply can't keep pace with the speed of change in the AI era. Talent Reinventors begin not by improving isolated parts of the system but by rethinking talent strategy as an integrated enterprise capability that shapes how work evolves, how people grow and how value is created. Several actions make this possible.

**Create clarity in priorities across HR, IT and the business:** Bring HR, IT and business decision-makers together so talent and technology roadmaps evolve in tandem from day one. Joint ownership, clear decision rights, governance and shared metrics create a holistic view of work, skills, behaviors and the workflows that enable the workforce.

**Redesign work around skills and potential, not rigid roles:** This balances human-AI collaboration at the task, team and enterprise level so all learn and evolve together.

**Develop workforce intelligence:** Linking workforce, learning, performance and productivity data—enabled by a mature, secure digital core with AI-ready data—brings learning and performance insights together to speed decision-making and improve talent mobility.

**Put people first:** Design workforce systems with empathy, judgment and inclusion—grounded in clear data-use guidelines, bias monitoring and employee feedback—so technology not only drives efficiency but builds trust, transparency and human agency at scale.

"Our deliverables are now higher quality, more structured, and clearer ... AI has indirectly raised the overall performance level."

— IT Manager, Biotechnology Company

### Create a culture of continuous learning

In a world where change is constant and unpredictable, organizations need to build the learning culture that allows them to adapt—creating an environment where people are continuously learning so they are ready to pivot quickly as opportunities arise.

Talent Reinventors reshape the employee experience into a human-AI growth journey—one that's personalized, always-on and deeply connected to how work gets done. Here are key actions to take at the individual, team and enterprise level.

**Design a workplace built on curiosity, creativity and trust:** Create tailored AI-led pathways for learning, career development and recognition. Make every interaction a learning moment that enables people and AI to learn, contribute, innovate and stretch into new opportunities.

**Embed learning into the flow of work:** Redesign roles and workflows so AI-enabled guidance, coaching and peer-to-peer co-learning happen in the flow of execution—making learning more relevant and turning rapid change into sustained performance.

**Embed continuous human-AI partnership:** Redesign work so AI supports people in the moment and learns continuously from feedback, accelerating skill development and productivity. Clearly define human-owned decisions, responsible use norms and escalation paths when judgment must override automation.

### Lead in new and dynamic ways

Talent Reinventors recognize that deploying AI is only the starting point; culture and leadership are the true differentiators of sustained performance. When organizations combine the right leaders, modern capabilities, effective team dynamics and an engaged culture, they significantly increase their ability to make an impact.

**Embody human-AI leadership:** Model digital, data and AI fluency and embed these capabilities into how leaders decide and create value. Leaders use AI to augment judgment, accelerate learning and design conditions for discovery—acting as architects of change, not just sponsors of technology.

**Accelerate change at the team level:** Empower team leaders to be the engine of reinvention. They create clarity and curiosity in an AI-enabled environment while fostering psychological safety, continuous learning and accountability. By personally engaging with AI and digital tools, leaders model new behaviors, reinforce a shared narrative and empower teams to move faster with confidence.

**Redesign team dynamics for confidence and collaboration:** Reconfigure teams to collaborate more effectively and act decisively. Clarify decision boundaries between human judgment and AI recommendations and formalize override protocols to reinforce accountability and trust. AI is used to improve decision quality, identify collaboration patterns and support leaders in expanding roles and responsibilities as work evolves and traditional silos break down.

**Reinforce culture for continuous reinvention:** Rewire culture through mindsets, incentives and talent practices that reward curiosity, experimentation and adaptability. A human-AI talent strategy integrates human and machine learning, supports internal mobility and uses ongoing feedback to grow the right skills where and when they are needed.

## Conclusion: The talent advantage

Most talent strategies were designed for a different era. They addressed workforce needs at a time when markets were predictable, roles were clearly defined and customer expectations evolved slowly.

Businesses were built around rigid chains of command, where each worker had a well-defined job and departments rarely overlapped. Training programs were set up to teach people a set of skills for a specific role, not give them the ability to transform their skills into building blocks on which they can build a career.

Today is different. The human+ AI workforce is not theory—it's here and it's not going away. People continue to be every organization's greatest asset. What has changed is the way that humans and technology learn, grow and evolve together.

Organizations that find the right balance between humans and AI—that keep humans in the lead—will attract and retain the best talent and continue to make significant leaps forward in resilience, innovation and profit. Nearly one in five organizations today can attest that talent reinvention takes effort, but the gains are impossible to ignore.

An elite group of organizations—Talent Reinventors—have created workplaces where humans and AI learn, grow and thrive together.

By putting people at the center of their digital reinvention—by keeping humans in the lead—they are vastly outperforming their peers and driving measurable value with AI.

## About the research

In this study, we set out to learn how leading organizations are building a human+ AI talent strategy—an integrated system in which people and AI continually amplify one another to drive growth, resilience and innovation. To understand what separates these leaders from the rest, we designed a mixed-method, multi-country research program that identifies the practices that distinguish "Talent Reinventors" and quantifies the value they generate both for employees and the enterprise.

We began by developing a framework that maps how organizations attract and match talent, move and develop people, align and support their growth and empower them through culture and leadership. Using this framework, we conducted two global surveys: one of 1,320 C-suite executives and another of 4,560 employees across large organizations, fielded between August and September 2025. Executives shared their priorities on talent and AI strategy, leadership agendas, technology investments and workforce practices.

Employees reported on their experiences of learning, mobility, skills development, culture and psychological safety. Together, the surveys span 20 industries and 12 countries across North America, Europe, the Middle East and Asia Pacific.

To illuminate the story behind the data, we conducted more than 55 in-depth interviews with C-suite executives and team leaders whose organizations are actively experimenting with or scaling AI in the workforce. These conversations helped us trace real transformation journeys, surface the tensions and opportunities of human-AI work, and identify emerging practices in internal mobility, co-learning, responsible AI and leadership behaviors. We supplemented these insights with a virtual focus group of 75 workers who shared firsthand perspectives on AI adoption, shifting skill demands, and day-to-day collaboration with intelligent tools.

We then triangulated these qualitative insights with external labor market and leadership data. We analyzed more than two million job postings from 468 organizations in our sample to understand how demand for skills—particularly AI, data, creativity and adaptability—is shifting. In parallel, we reviewed more than 3,000 earnings call transcripts from over 700 organizations to examine how senior leaders publicly discuss AI, talent, learning and culture, and how these narratives vary by maturity.

On the quantitative side, we used factor analysis to distill 22 survey items across the six characteristics into two underlying forces: Strategic Talent Alignment & Workforce Intelligence and Future-Ready Skills & Adaptability. Using scores on these factors, we applied k-means clustering to identify four distinct maturity profiles—Foundational, Developing, Progressing and the top-performing group we call Talent Reinventors, representing roughly 18% of the sample. Driver analysis then pinpointed the practices that most strongly differentiate Talent Reinventors, including embedding learning in the flow of work, using AI-enabled mobility platforms and treating workforce intelligence as a core enterprise capability.

Finally, we linked these maturity segments to business performance. By applying fixed-effects panel models to external financial data and projecting future performance trajectories, we quantified how marginal yearly advantages, when sustained, compound into sizable long-term financial gains—alongside significantly stronger culture, employee experience, adaptability and innovation capacity.

Taken together, this integrated evidence base—surveys, interviews, focus groups, labor market analytics and executive communication analysis—offers a robust, multi-angle view of how organizations are architecting today, where progress is stalling, and what it will take to close the gap between AI investment and realized value.

## Acknowledgements

The authors thank the following individuals for their contributions to this report:

**Research & Editorial:** Chitrangana Bhati, Nicole D'Agostino, Ranjan Ramdas, Abira Sathiyanathan, Dorota Kapkowska, Subhadeep Banerjee, Regina F. Maruca, Abhishek Gupta, Joanna Szpadkiewicz

**Marketing + Communications:** Natalie Zschech, Michael Dary, Jim Falloon, Shirley Brady, Jed Bonniwell, Adam Zrodlowski

The authors extend special thanks to subject matter experts Tim P. Good, Gaston Carrion, Francis Hintermann and Svenja Falk for their insights and contributions to this research.

## Endnotes

[^1]: John Kotter and James Heskett, Corporate Culture and Performance (Boston: Harvard Business School Press, 1992); Charles A. O'Reilly and Jennifer A. Chatman, "Parsing Organizational Culture: How the Norm of Adaptability Influences Performance," University of California Working Paper; Amy Edmondson, "Psychological Safety and Learning Behavior in Work Teams," Administrative Science Quarterly 44, no. 2 (1999); Erik Brynjolfsson and Andrew McAfee, The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies (New York: W. W. Norton & Company, 2014).

[^2]: Accenture, Pulse of Change Employee Survey, January 2026. All respondents. N=3350.

[^4]: Volkswagen Group, Boosting innovation, reshaping mobility: Volkswagen Group invests in AI, September 2025.

[^5]: Volkswagen Group, More efficient, smarter, more resilient: Volkswagen Group collaborates with AWS to help transform production for the age of AI, August 2025.

[^6]: Volkswagen Group, Artificial Intelligence in the Automotive Industry, September 2025.

[^7]: Volkswagen Group, Volkswagen Group establishes artificial intelligence company, January 2024.

[^8]: Microsoft, Accelerating our cultural transformation at Microsoft with Viva and AI, January 2026.

[^9]: Caterpillar, Caterpillar celebrates first 100 years with a commitment to the future workforce, April 2025.

[^10]: Caterpillar, Caterpillar introduces Cat AI Assistant, January 2026.

[^11]: Caterpillar, Caterpillar unveils AI-powered future and invests in the workforce building it, January 2026.

[^12]: Accenture, Pulse of Change CXO Survey, December 2025. All respondents. N=3650.

[^14]: Accenture, Learning Reinvented: Accelerating human-AI collaboration, September 2025.

[^16]: Merck & Co., 5 ways we're transforming artificial intelligence into impact, January 2026.

[^17]: Merck & Co., Merck Expands Innovative Internal Generative AI Solutions Helping to Deliver Medicines to Patients Faster, June 2025.

[^18]: IntuitionLabs, GPTeal: Merck's Generative AI Strategy for Pharma R&D, October 2025.

[^19]: Accenture, Pulse of Change CXO Survey, December 2025. All respondents. N=3650.

[^20]: Accenture Research analysis of earnings call transcripts from 700+ companies included in the CXO survey sample. January 2024–November 2025.

[^21]: BASF Group, Our Strategy.

[^22]: BASF Group, 2024 Annual Report, March 2025.

[^23]: Accenture, 2025 Annual Report, October 2025.

[^24]: Accenture, 2025 360° Value Report, December 2025.

## About Accenture

Accenture is a leading solutions and services company that helps the world's leading enterprises reinvent by building their digital core and unleashing the power of AI to create value at speed across the enterprise, bringing together the talent of our approximately 784,000 people, our proprietary assets and platforms, and deep ecosystem relationships. Our strategy is to be the reinvention partner of choice for our clients and to be the most client-focused, AI-enabled, great place to work in the world. Through our Reinvention Services we bring together our capabilities across strategy, consulting, technology, operations, Song and Industry X with our deep industry expertise to create and deliver solutions and services for our clients. Our purpose is to deliver on the promise of technology and human ingenuity, and we measure our success by the 360° value we create for all our stakeholders.

Visit us at accenture.com.

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## About Accenture Research

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## Sources

- Accenture-Talent-Reinventors-Report.pdf — primary authoritative source (PDF content)

- Talent Reinventors.md — secondary extraction aid (existing source markdown used only to recover structure and detail)