RESEARCH REPORT
Reinventing enterprise models in the age of generative AI
5-MINUTE READ
March 17, 2025
In brief
- Generative AI (gen AI) is more than a new technology—it represents a fundamentally different way of working.
- 97% of executives believe gen AI will transform their company and industry. 93% say their gen AI investments are outperforming other strategic areas.
- Organizations must reimagine not only how tasks are performed, but how new capabilities can be scaled to reinvent work across the enterprise.
By the numbers
Across industries and regions, executives are moving from piloting targeted gen AI use cases to implementing these technologies at scale. Yet amidst the push for ROI, too little attention is paid to how gen AI will reshape the very structure of the enterprise.
Our latest research highlights:
97%
of executives believe gen AI will fundamentally transform their companies and industries.
93%
of executives say their gen AI investments are outperforming investments in other strategic areas.
65%
of executives say they lack the expertise to lead gen AI transformations, underscoring an urgent need to develop new skills.
But the challenge isn’t just about upskilling. It’s about redesigning how people and machines work together—holistically and at speed.
Progress (and pitfalls) so far
Despite strong momentum around gen AI pilots:
- 82% of workers believe they already understand gen AI technology and 94% are confident they can develop the skills needed—yet 63% of employers still cite skill gaps as a major hurdle.
- Leadership trust gaps are emerging, as many executives underestimate how prepared (and eager) employees are to adopt gen AI.
- Misaligned organizational structures loom larger than many realize. Simply layering gen AI on existing workflows will not unlock its full potential.
Where more work is needed
Forward-thinking leaders see that operating models, structures and skills must radically adapt to capture gen AI’s full value. Traditional transformation approaches no longer suffice; a new playbook is required.
A four-lens framework for enterprise model reinvention
Adding AI agents to the workforce will unlock new levels of intelligence, ignite innovation and improve decision-making. To see the full potential, workers must embrace AI agents as “intelligent colleagues” with novel capabilities that are different from their own.
The nature of work, tasks and skills are continuously evolving, placing a premium on co-learning between people and intelligent agents as they begin to innovate together. This evolving job architecture means organizations will need to plan their workforce based on predicted workforce planning vs. relying on traditional, predefined career paths.
Gen AI can quickly disseminate information and insights, breaking down traditional organizational structures and hierarchies. Gen AI will also make it easier for people to work in new disciplines, as they will have access to well-synthesized, easily digestible information.
As people collaborate with gen AI agents, the structures they work within will naturally flatten and become more flexible. We will see more self-organizing teams, requiring new approaches to governance, metrics and funding to incentivize human+machine productivity.
To succeed in the next decade, organizations need to reinvent every part of their enterprise with technology, data and AI—and access, unlock and create great talent.
Julie Sweet / Chair and CEO of Accenture
Why now is the time to act
How to accelerate your enterprise model reinvention
Next 3 months
- Conduct a rapid “gen AI readiness” diagnostic to identify top-value processes for reimagination.
- Engage your workforce in transparent dialogues about gen AI’s impact on roles, responsibilities and career paths.
Next 12 months
- Launch cross-functional pilots with clear metrics for human + machine workflows.
- Redesign learning & development to embed AI “learning companions” into daily work.
- Pilot flexible organizational structures to foster fluid, project-based teaming.
By year two
- Scale a platform-based model (e.g., through global capability centers) to standardize and continuously improve AI-enabled services.
- Overhaul performance metrics to measure and reward human + AI outcomes (not just headcount or hierarchy).
- Continuously refine trust and governance frameworks to ensure responsible AI use enterprise-wide.
Explore our report for actionable insights on harnessing four key lenses—amplified intelligence, dynamic skills, fluid boundaries and adaptable structures—to reshape work at scale.
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