KPMG Survey Finds Organizations Must Transform Operations to Scale AI
A recent survey by KPMG highlights a striking insight: while enterprises are investing significant sums in artificial intelligence (AI), the success of these investments largely hinges on their integration into business operations. This finding emerges from KPMG’s Global AI Pulse: Q1 2026 survey, which engaged 2,110 C-suite leaders and their direct reports from 20 countries across eight sectors.
According to the report, an overwhelming 95% of organizations claim to have an AI strategy in place. However, only 39% reported actively scaling AI or driving its adoption across their enterprises. Alarmingly, just 8% of these organizations indicated they have experienced a tangible return on investment from their AI initiatives. This disparity raises critical questions about the effectiveness of current AI strategies and their alignment with business operations.
The projected spending on AI is substantial—companies anticipate an average investment of $186 million over the next year. Such figures underscore the urgency for organizations to ensure that their AI initiatives not only exist but are also effectively woven into the fabric of their operations. The report suggests that the differentiating factor between successful AI implementations and those that fall short is not merely a willingness to undertake experiments or the availability of technology and resources. Instead, it lies in the very structure of the organizations themselves.
The leaders in AI deployment are characterized by their governance structures, organizational design, and the skills of their workforce. The report points out that many organizations are simply not designed to support AI at scale, leading to a situation where broad experimentation occurs without translating these investments into measurable, enterprise-wide successes.
Distinguishing Leaders from Laggards
The report clarifies that the leaders—the 11% identified as "AI leaders"—demonstrate a remarkable ability to translate AI investments into meaningful business outcomes. These organizations maintain a clear linkage between their AI initiatives and resultant business results, employ consistent performance metrics across functions, and have real-time visibility into the impacts of their AI systems. Samantha Gloede, KPMG’s global head of risk services and trusted AI leader, notes that the measurement of AI’s value remains a significant challenge for most organizations. However, those navigating this successfully incorporate measurement practices within their AI operations.
Organizations that excel in scaling AI exhibit common traits. They construct agent ecosystems in a way that genuinely transforms business outcomes, thus moving beyond mere pilot programs. They also modernize their governance systems to manage risks effectively while preserving stakeholder trust. Crucially, they invest in their human resources, equipping teams with the skills necessary to adapt to an AI-integrated workplace.
Statistical data from the survey reinforce these observations. Approximately 82% of AI leaders report deriving meaningful business value from their investments in AI tools. In contrast, among those still engaged in pilot programs, only 62% assert they experience substantive value. Notably, AI leaders express 2.5 times greater confidence in their ability to manage associated risks than their less successful counterparts. This confidence extends to their adeptness in crafting multi-agent systems and effectively orchestrating AI across various workflows.
The Governance Challenge
Despite the clear benefits of integrating AI, governance continues to present significant challenges across enterprises. The survey reveals that while 52% of organizations utilize AI to automate workflows, a mere 9% have successfully orchestrated multiple agents across these workflows. Gloede highlights that fragmented systems and disparate data sources impede effective decision-making across business functions.
"For many organizations, coordinating multiple AI agents across various functions presents a major hurdle that is crucial to overcome," she states. As AI systems cross departmental lines, the delineation of decision-making authority becomes blurred. Therefore, establishing clear governance protocols from the outset is vital. Gloede emphasizes that effective governance should be a foundational element of any AI deployment strategy, not an afterthought.
KPMG’s findings indicate that organizations with robust governance frameworks often demonstrate higher levels of ambition regarding AI implementation. For instance, 81% of AI leaders possess the capabilities and governance structures necessary to manage AI risks at scale, compared to just 63% of organizations that do not rank as leaders. These leaders also invest significantly more in compliance initiatives, cybersecurity measures, and governance expertise at the board level.
For Chief Information Officers (CIOs), laying down comprehensive governance structures prior to deploying AI is essential for fostering trust throughout the organization. Gloede advocates for viewing governance not as a hindrance but as an enabling force—integrating accountability and risk management directly into workflows is key to establishing an AI-empowered enterprise.
Workforce Preparedness and Training Initiatives
Turning to the challenges of workforce readiness, the survey reveals that many organizations face hurdles not merely from technology or funding, but primarily due to employee preparedness. A scant 22% expressed complete confidence that their talent pipeline could meet the demands of an AI-enhanced workforce, while 25% acknowledged workforce readiness as a significant concern.
Gloede underscores the necessity for hands-on training and real-world application of AI skills. Companies leading in AI workforce readiness have introduced innovative training programs, allowing employees to immerse themselves in simulations that mirror actual workflows. These organizations often encourage experimentation through internal initiatives, even offering cash prizes for teams that successfully develop AI solutions yielding measurable improvements in operations or client relations.
By implementing such strategic training approaches, organizations can cultivate a workforce capable of adapting to the evolving demands of AI, ensuring that they stay competitive in a rapidly advancing technological landscape.