AI Regulation: An Adoption Accelerator
The emergence and growing adoption of generative AI, alongside the implementation of the EU AI Act, have coincided remarkably, catalyzing an AI renaissance within enterprises. While companies had already begun applying AI in various sectors, the impact of these two forces has necessitated a paradigm shift in organizational thinking and operations.
Suddenly, the focus shifted to AI, with a surge in demand for new tools coming from all corners of organizations. Developers began utilizing co-pilots to enhance coding efficiency, sales teams employed AI to draft customer outreach emails, and marketing teams harnessed generative AI tools for localized campaigns and message translations.
Competitive Pressure and Governance Needs
Executives and boards of directors felt compelled to act to harness the potential competitive advantages AI presents. A recent study highlighted that 89% of global CEOs view AI technology as crucial for maintaining profitability, with 77% planning to increase AI budgets in 2025. However, 87% of these leaders also recognized an urgent need for AI governance frameworks, citing concerns over data privacy and cybersecurity.
Many executives expressed worries about the potential risks to both revenue and reputation. Additionally, CFOs voiced concerns regarding the financial implications of AI investments, with 33% fearing a lack of capital for investments. Notably, around half of the CFOs surveyed indicated that if an AI investment does not yield measurable ROI within a year, justifying further investment would be challenging.
The Perfect Storm for AI Strategy
These dynamics—interest, adoption, competitive pressures, and cost concerns—created a perfect storm within enterprises. For many organizations, this storm culminated in the formulation of a new AI strategy, triggering a wave of organizational and cultural transformation. Implementing AI at scale demands enhanced efficiency and coordination, but such change often encounters resistance.
Impact of the EU AI Act
The real catalyst for this transformation has been the EU AI Act, which came into force in August 2024, introducing requirements that will be applied progressively. A chief data officer from a major global pharmaceutical company characterized this shift: traditionally, each business unit operated independently, driving its own data and AI initiatives. However, the EU AI Act’s mandates for transparency and accountability in AI usage have redefined this landscape.
As per the CDO, “the EU AI Act will be the driver of a complete view of AI across the enterprise.” Consequently, all AI models used for decision-making will now be cataloged at the enterprise level, enhancing visibility across organizations. Compliance with the law necessitates a shift in how AI initiatives are managed, fostering collaboration rather than stifling innovation.
Regulation as a Catalyst for Collaboration
Regulation has emerged as an effective mechanism for data and IT teams to federate distributed data activities. In the pharmaceutical sector, the central data team imposed AI governance requirements to mitigate compliance risks, effectively providing an “insurance policy” for business units. This newfound need for cataloging and assessing AI risks has increased visibility and collaboration, inspiring teams to explore synergies and enhance project efficiency.
As an example, in manufacturing, a defect-prediction model could benefit from pooled data across different product teams. The central data team facilitates these connections, accelerating projects and fostering efficiencies. Rather than hindering AI adoption, regulation is proving to be a catalyst for collaboration and a driver for reducing inefficiencies.
The EU AI Act as an Ally
Many data leaders echo this sentiment. Another data leader from a large European medical equipment manufacturer remarked, “The EU AI Act has been the best ally for data teams. Without it, we’d have more difficulties getting topics on the table.” One significant area of focus is data and AI literacy. With the EU AI Act mandating that all staff receive training, the implementation of data literacy programs is now more feasible.
As of February 2, 2025, the AI literacy requirement states that providers and deployers of AI systems must ensure a sufficient level of AI literacy for their personnel, considering their technical knowledge and the context in which AI systems will be used.
Conclusion
The overarching message is clear: “the EU AI Act will make us all reflect more about how we use the new tools.” This reflection is not only beneficial but essential as organizations navigate the complexities of AI integration.
