AI reshapes professional services around trust and business outcomes

Professional services firms are rethinking how they deliver value as artificial intelligence takes on more routine tasks. This shift is changing project structuring, knowledge management, and success measurement. Rather than merely speeding up existing processes, companies are redesigning workflows around AI-driven execution while preserving essential client expectations, according to Matt Cook, a PwC U.K. partner and consulting software sector lead, and Prasad Narasimhan Sulur, Certinia Inc.'s chief business officer.

"Where we're seeing AI leaders win is they're not simply deploying better tools," Cook explained. "They're actually redesigning how that value is created." In other words, it's about creating value more efficiently, not just faster. Cook and Sulur discussed this transformation during an interview on theCUBE Research's Scott Hebner show.

They highlighted how AI is reshaping professional services economics, the necessity of governance to scale adoption, and the growing value of human expertise as AI assumes more responsibilities. Despite AI's potential, only 12% of surveyed CEOs reported both revenue growth and cost reductions from AI, while 56% saw no significant financial benefits.

This suggests the need for AI to be embedded into core operations rather than used as a standalone productivity tool. "The firms that win will be the ones that can turn AI into repeatable, measurable outcomes, not the ones with the most tools," Cook said. For professional services firms, AI's impact may not always translate into faster project delivery.

AI-assisted coding, for example, can speed up development cycles but may not eliminate delays in testing, integration, or release. Similarly, AI can expedite research and analysis in consulting engagements but requires a complete workflow redesign, not just automation of individual steps. Successful transformation hinges on strong leadership and employee capabilities.

Executives must set clear direction, while employees need proficiency to apply AI effectively and identify improvement opportunities. "The combination of the top-down mandate and what I call the bottom-up proficiency that your organization has is what's going to move the ball forward," Sulur emphasized. As firms adopt more consequential AI applications, reliability and accountability become crucial.

AI-generated recommendations may seem accurate but may contain errors requiring extensive human verification, potentially negating the expected productivity gains. To maintain trust, professional services firms must develop systems for providing appropriate business context, enforcing permissions, and validating outputs against expected results.

This involves not just improving model accuracy but also creating an overall architecture that supports workflow orchestration and enterprise data management. Orchestration systems help AI understand project stages, required tasks, and previous work, while data management systems ensure organizational knowledge is accessible in the right context.

Unstructured information, such as meeting transcripts and communications, can be a valuable resource if managed correctly. However, firms must decide which information is relevant to each task while preventing unauthorized access to sensitive data. Cook stressed that AI can aid in gathering evidence and developing scenarios but cannot carry professional accountability.

"AI can accelerate evidence gathering and scenario development, but it doesn't carry professional accountability," he stated. "That remains human." The growing importance of human judgment is also reshaping workforce expectations. PwC research indicates that AI-exposed junior positions increasingly require skills traditionally associated with senior roles, such as leadership and decision-making.

Looking ahead, professional services firms may invest more human resources in addressing complex client challenges as AI handles repetitive tasks. Companies that focus on building trusted systems, institutional knowledge, and redesigned delivery models could gain a competitive edge over firms solely focused on individual productivity improvements.

"When AI can produce more analysis than a human can read, the differentiator's not more content, it's better judgment," Cook concluded. This could lead to a fundamentally different professional services model where technological execution expands capacity while human expertise determines business outcomes' quality and value.