Leading consulting firms are at the forefront of AI adoption, not only helping clients develop AI strategies but also leveraging the technology internally to transform their own operations. AI executives from Deloitte, EY, KPMG, McKinsey, and PwC shared their insights on how they use artificial intelligence in daily work and their best practices for maximizing AI’s potential.
These consulting giants have developed proprietary AI tools including McKinsey’s Lilli, EY’s EYQ, and PwC’s ChatPwC, alongside using commercial models from OpenAI, Google, Microsoft, and Anthropic. The AI leaders revealed that their use cases span from research and analysis to content creation, email management, and strategic planning.
Dan Priest, US chief AI officer at PwC, described using AI as a “thought partner” rather than just a search engine, noting how it helps identify blind spots in thinking and policy development. He uses AI for everything from analyzing labor productivity trends to managing hundreds of daily emails and even creating recipes from leftover ingredients. His approach involves providing context, asking short questions, and iterating with increasingly specific follow-ups.
Jim Rowan, head of AI at Deloitte, emphasized using AI as a “thought companion and writing partner” for drafting internal communications, social posts, and speaking engagement materials. His advice: start using approved tools immediately and gain hands-on experience, even in personal life if enterprise tools aren’t available.
Rodney Zemmel, global leader for McKinsey Digital, highlighted AI’s strength in “level one” creativity and brainstorming, encouraging users to move beyond simple lookups and engage in dialogue with AI. He advocates for building agents that can execute simple tasks, allowing humans to focus on the most valuable 20% of their work.
Matt Barrington, Americas CTO at EY, stressed the importance of context management, maintaining separate AI workspaces for different focus areas and providing clear instructions about desired response styles. Todd Lohr from KPMG noted AI’s value in synthesizing information and enabling broader leadership perspectives.
The executives acknowledged challenges including changing established work habits, managing disparate data sources, keeping pace with rapid innovation, and understanding the difference between consumer and enterprise-grade AI tools. Client conversations have evolved from seeking “killer use cases” to asking how to fundamentally evolve business strategy around AI capabilities, with growing interest in AI agents that can integrate with workforces and enable entirely new capabilities beyond human capacity.
Key Quotes
AI, the big powerful foundation models, it’ll grab those labor facts and statistics, it’ll do analysis, it’ll show you trends, discontinuities, or cause analyses. It is much more robust. In terms of research and analysis, it emerges as a thought partner versus just a search engine.
Dan Priest, US chief AI officer at PwC, explains how AI has transformed his research process beyond simple information retrieval to sophisticated analysis and strategic thinking partnership, representing the evolution from AI as tool to AI as collaborator.
Too many people are still using it to look something up. The trick is to have a dialogue with it and to get comfortable building agents that can execute simple tasks. Let AI handle the 80% of tasks we’re mediocre at, so we can excel at the exciting 20%.
Rodney Zemmel, global leader for McKinsey Digital, emphasizes the importance of moving beyond basic AI usage to more sophisticated applications involving dialogue and agent-based automation, highlighting the strategic value of focusing human effort on high-impact activities.
The questions have sort of shifted. A year ago, they were asking, ‘What’s the killer use case?’ Now, the questions we’re getting are less about those technical use cases and they’re much more about ‘How do you evolve the business strategy to take advantage of AI capabilities?’
Dan Priest from PwC describes the fundamental shift in how clients approach AI, moving from tactical implementation questions to strategic business transformation, indicating AI’s evolution from departmental tool to enterprise-wide strategic imperative.
Your outputs are only as good as the data you input. I know from personal experience that it can take time to refine prompts to the point that you get the desired result. Learning to ’talk’ with the AI tools out there in the market and the different styles and approaches takes a little time.
Jim Rowan, head of AI at Deloitte, addresses the learning curve associated with effective AI usage and the critical importance of prompt engineering, while also warning about security risks between consumer and enterprise AI tools.
Our Take
The convergence of insights from these five consulting powerhouses reveals a critical inflection point in enterprise AI adoption. What’s particularly striking is the consistency in their approaches—emphasis on iterative prompting, context management, and viewing AI as a collaborative partner rather than a replacement tool. The shift from seeking “killer use cases” to strategic business transformation questions suggests we’re entering AI’s second wave, where competitive advantage comes not from having AI, but from fundamentally reimagining business processes around it. The executives’ candid discussion of challenges—particularly around changing ingrained work habits and data integration—provides valuable realism often missing from AI hype. Their focus on agentic AI and human-AI collaboration models aligns with broader industry movements toward more autonomous systems. As these firms shape AI strategies for thousands of global enterprises, their internal practices essentially become blueprints for corporate AI adoption, making their experiences particularly influential for the broader business ecosystem.
Why This Matters
This article provides crucial insights into how the world’s leading consulting firms—trusted advisors to Fortune 500 companies—are actually implementing AI in practice. The shift from theoretical AI discussions to practical, daily usage by senior executives signals AI’s maturation from experimental technology to essential business tool. The evolution of client questions from “what’s the killer use case?” to “how do we evolve our business strategy?” represents a fundamental transformation in how organizations view AI—moving from tactical efficiency gains to strategic competitive advantage.
The emphasis on AI agents and human-AI collaboration reflects broader industry trends toward agentic AI systems that can execute complex workflows. These consulting leaders’ experiences offer a roadmap for other organizations navigating AI adoption, particularly around prompt engineering, context management, and balancing innovation with security. Their acknowledgment of challenges—from changing work habits to data integration—provides realistic expectations for AI transformation. As these firms guide thousands of companies through AI adoption, their internal practices become de facto industry standards, making their approaches particularly influential for the broader business community.
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Source: https://www.businessinsider.com/ai-chiefs-top-consulting-firms-how-to-use-ai-prompts-2025-2