According to the PwC 2026 AI Performance Study, roughly 74% of the economic value created by AI is realized by just 20% of companies. The study is based on responses from 1,217 senior executives (director level and above) across 25 industries and multiple regions worldwide.
Who the winners are and how they differ
PwC finds that leading companies do more than deploy a larger number of AI tools: they use the technology strategically to identify growth opportunities, rethink business models and redesign workflows. Specifically:
- Leading firms are two to three times more likely to use AI to drive growth and business model transformation.
- They are twice as likely to redesign processes rather than merely introduce tools.
- They increase the number of decisions made without human intervention about 2.8 times faster than their peers.
Joe Atkinson, Global Chief AI Officer at PwC, noted that the highest‑performing AI organizations use AI to transform their business models and expand beyond traditional industry boundaries. These companies were 2.6 times more likely to report that AI supports such transformation and two to three times more likely to identify and exploit growth opportunities arising from industry convergence.
Scaling and automation versus pilots
While leaders scale rapidly and automate broadly, the majority of companies remain in pilot phases for many AI initiatives. PwC’s analysis emphasizes that the main driver of AI‑led financial performance is capturing growth pathways from industry convergence, rather than solely improving efficiency.
Advanced use and autonomous operation
Top performers are also more likely to deploy advanced AI approaches:
- They are 1.8 times more likely to run multiple tasks within predefined guardrails.
- They are 1.9 times more likely to operate autonomous, self‑optimizing systems.
Additionally, these firms increase the number of human‑free decisions 2.8 times faster than competitors.
Building “scalable trust”
Behind automation is the deliberate construction of what PwC calls “scalable trust.” Leaders more frequently have responsible AI frameworks (1.7 times more common) and cross‑functional AI governing boards (1.5 times more common). As a result, employees at leading companies are twice as likely to accept AI‑generated outputs.
Risk: the gap may widen
PwC warns that unless approaches change, the gap between AI leaders and laggards will grow. PwC’s 2026 Global CEO Survey also flagged 2026 as a pivotal year for artificial intelligence: a small number of companies are already converting AI into tangible financial results, while many still struggle to move beyond pilots. The difference already appears in levels of trust and competitiveness and may accelerate for those that do not shift their strategy.
Methodology (for editors)
PwC’s study is based on 1,217 senior executive responses across 25 industries and multiple regions. AI‑attributable performance was measured by revenue and efficiency gains attributable to AI, adjusted to industry medians. PwC analyzed the impact of 60 practices related to AI management and investment, categorized into AI usage and AI foundations, which together form the PwC AI Fitness Index.
