Although 93% of organizations report using some form of AI, most are far from full adoption. Only 31 percent have implemented AI across core operations through proof of concept and pilots, with the rest still in the early stages. 32 percent have been partially deployed in some workflows, and 20 percent are still in testing or piloting.
Organizations continue to report that generative AI is not yet producing measurable business benefits, reflecting the current state of adoption. Most implementations are still in the pilot or partially deployed stage, and conditions are not yet in place to capture meaningful value. Only 2% of respondents said their organization is benefiting from investments in generative AI. Of those who reported a gain, more than half (57 percent) said it was modest (5 to 20 percent), while almost a third (31 percent) could not quantify it at all.
Behind these modest achievements lies a common challenge. Many organizations still face fundamental barriers that prevent them from scaling AI across the enterprise. Legacy systems, siled data, and unclear success metrics often prevent organizations from embedding AI throughout their organizations.
Low AI integration may also reflect a lack of a clear strategy for selecting appropriate use cases. Companies should not underestimate the effort required to select, refine, and mature their use cases to ensure they create both tangible business value and personal value for employees. When AI tools address real-world pain points and make daily tasks easier, employees are much more likely to adopt, adapt, and continue using them.
A further cause of poor ROI may be the tendency to layer AI on top of existing processes rather than redesigning workflows to take full advantage of the technology. Integrating AI into current workflows allows for incremental improvements, but the greatest value comes from processes where tasks, decisions, and systems are optimized for AI and redesigned to leverage the full power of AI.
