KPMG, one of the Big Four consultancies, has fully integrated artificial intelligence across all its operations and is now guiding global businesses through their own AI transformation journeys. David Rowlands, KPMG’s global head of AI, revealed in an interview with Business Insider that every employee across the firm’s three divisions—accounting, tax, and advisory—now has access to AI tools, with all staff able to use a form of GPT and approximately 20% of the global workforce equipped with Copilot licenses.
Rowlands emphasized that AI enables employees to complete existing tasks more quickly, but noted that most companies are still navigating the adoption path. Client concerns have evolved significantly over time: initially focused on ethics, hallucinations, and trust issues; shifting in recent months to realizing business cases and enabling workforce adoption; and now centering on data management, differentiation, and protection.
One of the biggest barriers companies face is focusing on single-use cases for AI systems rather than embedding AI into their operating models. Rowlands stressed that systems must have reusability and that point solutions haven’t proven particularly effective as business cases. He advocates for organizations to think beyond isolated use cases and integrate AI comprehensively into their operations.
KPMG is heavily investing in AI infrastructure. In 2023, the firm announced a $2 billion investment in artificial intelligence and cloud services through a Microsoft partnership over five years, expecting to generate more than $12 billion in revenue during that period. In November, KPMG announced an additional $100 million investment in Google Cloud, projected to drive $1 billion in growth.
Regarding return on investment—a hot topic among CEOs as billions pour into AI infrastructure—Rowlands acknowledged that mid-2024 surveys showed “ambivalent” results, but the firm is now seeing anecdotal evidence of ROI. He cited that copilot systems save approximately 40 minutes per week per user, with benefits manifesting through improvements in growth, quality, and agility. Rowlands predicts that within a year, COOs and CFOs will be positive about their AI returns.
Looking ahead, Rowlands expects multi-agent models—groups of specialized AI agents coordinating to solve collective goals—to rapidly become reality within 12 months, potentially addressing major challenges like decarbonization. KPMG conducted “24 hours of AI” training in January 2024 to prepare its workforce, emphasizing that everyone should know how to use AI effectively and innovatively with clients.
Key Quotes
Whatever they were doing already, they can now do quicker.
David Rowlands, KPMG’s global head of AI, explained how AI tools are enhancing employee productivity across all divisions of the firm, emphasizing the immediate practical benefits of AI implementation.
What you have to think about is having AI embedded in your operating model. At KPMG, we’re keen to get people beyond use cases because a point piece of technology, a point use case, hasn’t been a particularly effective business case.
Rowlands identified one of the biggest barriers companies face—focusing on single-use cases rather than comprehensive AI integration. This insight challenges the common approach of deploying AI for isolated tasks and advocates for systemic transformation.
Organizations will be increasingly differentiated by the data that they own.
Rowlands highlighted the critical importance of data strategy in AI implementation, suggesting that competitive advantage will come from how companies manage, own, and leverage their proprietary data as AI becomes ubiquitous.
We don’t really think about replacing jobs. It’s more about enhancing individuals and roles. And those who are using AI well are being more successful than those who aren’t.
Addressing concerns about AI’s impact on employment, Rowlands positioned AI as an enhancement tool rather than a replacement technology, emphasizing that success comes from effective AI utilization rather than workforce reduction.
Our Take
KPMG’s AI strategy reveals a critical shift from experimental AI projects to enterprise-wide transformation, providing valuable lessons for organizations struggling with implementation. The firm’s emphasis on moving beyond isolated use cases addresses a fundamental problem plaguing many AI initiatives—the failure to achieve scale and meaningful ROI. Rowlands’ candid acknowledgment that mid-2024 surveys showed “ambivalent” results on returns, followed by emerging positive signals, offers a realistic timeline for AI value realization that counters both excessive hype and premature pessimism. The prediction about multi-agent models becoming mainstream within 12 months is particularly significant, suggesting we’re approaching a new phase of AI capability that could finally deliver on promises to solve complex, systemic problems. KPMG’s massive investments—$2 billion with Microsoft and $100 million with Google Cloud—demonstrate conviction that AI will fundamentally reshape professional services, making this a bellwether for the broader enterprise AI market.
Why This Matters
This story provides crucial insights into how major professional services firms are implementing AI at scale, offering a blueprint for other organizations navigating their own AI transformations. KPMG’s comprehensive approach—moving beyond isolated use cases to embedding AI throughout operations—represents a maturation of enterprise AI strategy that addresses the industry’s ongoing debate about ROI and practical implementation.
The evolution of client concerns from ethics to business cases to data strategy reflects the broader market’s journey from AI skepticism to practical deployment challenges. With billions invested in AI infrastructure and questions about returns intensifying, KPMG’s experience provides real-world evidence that benefits are materializing, even if gradually. The firm’s prediction about multi-agent models becoming mainstream within 12 months signals an important inflection point for AI capabilities.
For businesses and workers, this story underscores that AI adoption is no longer optional but essential for competitive differentiation, particularly through proprietary data. The emphasis on workforce training and job enhancement rather than replacement offers a more nuanced perspective on AI’s labor market impact, suggesting a “rotation” rather than elimination of roles in professional services.
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