The challenge of successfully adopting AI in organizations often lies not in the technology itself but in the underlying operating models that dictate how teams work together. phrase reports that As Elaine Barsoom’s insights reveal, the failure of a joint venture model that thrived in Europe but faltered in the US exemplifies a broader issue: the assumption that what works in one context will seamlessly translate to another. This misconception can lead to significant missteps, especially in the realm of AI, where the technology is often deployed without a corresponding redesign of workflows and organizational behavior. The stark reality is that nearly 60 percent of AI transformation efforts yield limited or no material value, underscoring a critical lesson: investment alone cannot bridge the gap between AI adoption and tangible returns.

Barsoom’s experiences at both American Express and Nike illustrate the importance of addressing organizational behavior as a prerequisite for effective technology integration. When GitHub Copilot was introduced at Nike, the initial rollout was textbook perfect, yet it failed to gain traction because the engineering teams were not engaged in rethinking their operational processes. The solution lay in fostering a culture of collaboration and support, where peer-to-peer sharing and change management became integral to the adoption process. The shift from merely deploying technology to embedding it into everyday practices transformed the tool from an experimental phase into a vital operational asset. The key takeaway is that success in AI adoption is measured not by usage statistics but by meaningful changes in behavior that drive value.

For localization managers and enterprise language buyers, this analysis has profound implications. As organizations increasingly rely on AI-driven tools for managing multilingual content, the risk of fragmentation looms large. Barsoom emphasizes that customers experience the brand in moments, not through the complexities of the underlying systems. This means that a coherent operational infrastructure is paramount. Brands that can effectively coordinate their content and communication across diverse markets will not only enhance their customer experience but also avoid the pitfalls of inconsistency that can erode trust. A global fashion retailer’s success in managing vast translation needs within a streamlined operating model serves as a prime example of how strategic alignment can yield significant operational advantages.

Ultimately, the lesson for language professionals is clear: the focus should not solely be on acquiring advanced AI tools but on cultivating an environment that supports their effective use. The organizations that thrive will be those that prioritize the development of cohesive operating models capable of adapting to the complexities of global markets. By doing so, they will not only harness the full potential of AI but also ensure that their technological investments translate into real, sustainable value.