AI Foundations
AI USE
1/9
Breadth and depth
This factor captures how much AI is used across your organisation’s value chain and how deeply AI is deployed into workflows within each function. The AI leaders’ score for breadth and depth is roughly twice as high as the rest. Watch Joe Atkinson, PwC’s Global Chief AI Officer, explain more about breadth and depth of AI use, what leaders do differently, and what you can do to join them.
1:53
This factor is a measure of a company’s most advanced AI applications. Think of this variable as a spectrum—from using AI simply to summarise long texts all the way through to building autonomous, self-optimising agents. The AI leaders are twice as likely to use AI that operates autonomously. Watch Scott Likens, PwC’s Global Chief AI Engineer, PwC US, explain more about sophisticated AI applications and the value they can create.
Sophistication
2/9
2:10
This factor assesses the extent to which AI enables cross-sector competition or collaboration. That could be sensing emerging value pools between sectors, responding to shifts in customer needs, or collaborating across sectors to unlock new value from ecosystem partnerships. AI leaders are more likely to use AI to derive growth from industry convergence, the strongest AI fitness factor influencing AI-driven performance. Watch Nicki Wakefield, PwC’s Global Clients and Industries Leader, explain what AI leaders are doing differently and what all organisations can do with AI to capture value in motion.
Capturing value from industry convergence
3/9
2:20
This factor captures how innovation-friendly—yet rigorous—a company is. Does your business have dedicated innovation infrastructure, like sandbox environments? Embedded ownership of innovation within business units? And a cadence of portfolio reviews to test, prioritise, scale, and stop AI initiatives? AI leaders are more likely to provide dedicated innovation infrastructure and conduct frequent reviews of innovation portfolios to scale up AI initiatives. Watch Agnes Koops, PwC’s Global Chief Commercial Officer, explain how the AI leaders treat innovation and how you can replicate it.
Innovation
4/9
1:57
The security, access controls, regulatory compliance processes, ethical frameworks, and oversight bodies needed to manage risk from AI design to deployment. AI leaders are 1.6 times as likely to have a Responsible AI framework that guides AI strategy—including use case selection, design, deployment, and ongoing monitoring. Watch Kazi Islam, PwC’s Global Assurance Strategy and Growth Leader, discuss the importance of AI risk management and how to build trust in AI.
Governance and risk
5/9
2:17
This factor is the degree to which a business has modern, scalable platforms and trusted, varied data sources accessible to everyone. Also critical: reusable AI components and replicable, redesigned workflows in priority applications. Compared to the chasing pack, AI leaders are more than twice as likely to have eliminated outdated and costly IT applications, systems, and infrastructure. Watch Dan Priest, Chief AI Officer, PwC US, explain the criticality of getting your data architecture and tech foundations ready to point AI at growth.
Data and technology
6/9
2:12
The strength of connection between corporate strategy and AI deployment. Does the organisation have a prioritised AI road map? Is every use case linked to a clear business objective? Is business impact tracked? And is someone accountable for every critical AI outcome? Watch Daria Vlasova, AI Strategy & Go-to-Market lead, PwC UK, explain how the AI leaders root their AI planning in their strategic growth priorities.
Strategy
7/9
This factor measures the funding and resourcing for AI. Are investment levels sufficient? Can resources be reallocated as priorities shift while still supporting longer-horizon innovation? Leading companies are more likely to invest sufficiently, reallocate funds with agility, and invest for long-term results. Watch Teresa Owusu-Adjei, PwC’s Clients and Markets Leader, Global Tax and Legal Services, explain how the AI leaders manage their AI investments.
Investment
8/9
2:19
This factor is a measure of whether leaders and employees have the skills, incentives, collaboration models, and levels of trust needed to build AI and use it effectively in day-to-day decisions. AI leaders are 1.7 times as likely as other firms to say their employees participate in ongoing, role-based AI-learning sessions. And those employees are twice as likely to trust the insights generated by AI. Watch Pete Brown, PwC’s Global Workforce Leader, explain how AI can help unite human potential with tech power.
Workforce
9/9
2:14
