Companies are rushing into AI, but adoption is still lagging, a KPMG executive says
The Accelerated Integration of Artificial Intelligence
Companies are rushing into AI but adoption – Artificial intelligence is rapidly transforming the corporate landscape, with businesses adopting the technology at an unprecedented pace. However, despite this swift integration, many companies are still grappling with the challenge of demonstrating measurable outcomes from their AI initiatives. Mathieu Wallich-Petit, Head of Clients & Markets at KPMG France, shared his insights on this trend during a conversation with Euronews Next at VivaTech in Paris. He emphasized that while enthusiasm for AI is growing, the actual implementation remains inconsistent, highlighting a critical gap between ambition and execution.
“Our clients do embed a real strategy in AI, but in reality, on the ground, there is still a big lag,” Wallich-Petit said. He explained that KPMG’s role is to assist organizations in overcoming this disparity, as the technology evolves faster than many companies can adapt.
Strategic Implementation and Measurable Outcomes
According to a report released by KPMG in March, 95% of its clients have developed a comprehensive AI strategy, indicating widespread recognition of its potential. Yet, only 8% of these companies can accurately quantify a return on investment, underscoring the difficulty in translating strategic vision into tangible results. Wallich-Petit noted that while 64% of firms have observed some level of success, the majority are still in the early stages of realizing AI’s full impact.
“What is amazing is that the pace of acceleration of the technology is really exponential,” he remarked. “And we see the adoption within each company to be pretty much linear.”
This exponential growth in AI development contrasts sharply with the linear progress seen in corporate adoption, according to the executive. The disparity suggests that organizations are often slower to adapt, even as the technology becomes more sophisticated. Wallich-Petit stressed that this gap is not just about speed, but about ensuring that AI is integrated effectively into core operations rather than treated as a standalone project.
Evolution in AI Applications Across Industries
Wallich-Petit pointed to the insurance sector as an example of how AI is evolving beyond its initial use cases. While earlier implementations were primarily focused on automating claims processing, the industry is now leveraging AI for broader functions, such as client scoring, pricing models, and customer service workflows. This shift reflects a more holistic approach to AI deployment, where the technology is no longer seen as a niche tool but as a fundamental component of business operations.
“Before it was very much about automation of claims, and now it’s very much end-to-end, from scoring new clients, pricing and to customer service,” he explained.
Despite these advancements, the majority of KPMG’s clients are still in the process of scaling AI applications. The report reveals that only around 10% of companies have achieved full-scale AI integration, indicating that the journey from pilot projects to widespread adoption is both complex and time-consuming. This highlights the need for sustained investment and strategic planning to ensure long-term success.
Investing in AI: A Strategic Priority
As AI continues to gain traction, businesses are allocating more resources to its development. Wallich-Petit observed that corporate boards are increasingly viewing AI as a competitive advantage, not only to streamline operations but also to attract top talent in the tech-driven market. This shift in mindset has led to a rise in AI budgets, with companies prioritizing innovation and scalability.
“KPMG says companies are continuing to increase AI budgets because boards see the technology as a competitive advantage and a way to attract talent,” he stated.
However, this financial commitment is accompanied by heightened scrutiny. Businesses are now demanding clearer evidence of AI’s value, particularly in terms of rapid and substantial returns. Wallich-Petit acknowledged that this focus on outcomes is crucial, but he also warned that without proper planning, the investments could fall short of expectations.
The Human Element in AI Success
Wallich-Petit underscored that the success of AI strategies hinges not just on technological capabilities, but on the people who implement and manage them. “My view is that it’s really about people, it’s not a question of technology,” he said. This perspective emphasizes the importance of upskilling employees and fostering a culture of continuous learning to maximize AI’s potential.
“Upskilling people, training people, is probably the most important strategic angle to make an AI strategy a success,” he added.
For companies still transitioning from pilot phases to full-scale deployment, the priority lies in embedding AI into daily workflows. Wallich-Petit described this as the “magic recipe” for sustained growth, requiring a shift from experimental use to operational integration. He argued that this transition involves three key pillars: robust governance frameworks, improved data management systems, and ongoing employee training programs.
AI Sovereignty and Geopolitical Implications
As AI adoption accelerates, the concept of AI sovereignty has emerged as a pressing concern for businesses. Wallich-Petit highlighted that companies are becoming more cautious about over-reliance on a few dominant model providers, particularly in light of geopolitical tensions affecting access to advanced AI tools. “The main theme is not to rely on only one model, but to have a diversity of models,” he said.
“That question has become more concrete as access to some advanced AI models becomes caught up in geopolitics,” he noted.
This issue is exemplified by recent developments involving KPMG’s partnership with Anthropic, a U.S.-based AI company. In May, the two organizations announced a global alliance to integrate Anthropic’s Claude AI assistant into KPMG’s client delivery platform, expanding access for its workforce. However, this collaboration was soon tested when the U.S. government ordered Anthropic to suspend access to its Fable 5 and Mythos 5 models for foreign users, raising questions about the balance between innovation and geopolitical risk.
Pathways to Sustainable AI Adoption
Wallich-Petit believes that the future of AI adoption depends on a combination of strategic foresight and operational agility. He warned that businesses must avoid treating AI as a fad, instead viewing it as a long-term investment that requires careful management. “We always say it’s having people in the loop. I think it’s more than that. We need to have people driving with AI,” he remarked.
For companies aiming to harness AI’s power, Wallich-Petit suggested a multi-pronged approach. This includes fostering collaboration between technology developers and business leaders, ensuring data quality and accessibility, and aligning AI initiatives with broader organizational goals. He also called for greater transparency in AI governance, emphasizing that clear communication and accountability are essential for building trust and driving adoption.
In summary, while the enthusiasm for AI is evident across industries, its real-world impact remains uneven. The KPMG report and Wallich-Petit’s insights reveal that the journey from strategy to execution is fraught with challenges, from measuring ROI to navigating geopolitical complexities. As the technology continues to evolve, the focus must remain on bridging the gap between innovation and practical implementation, ensuring that AI becomes a cornerstone of sustainable business growth.
