**Almost All Mid-Sized Companies Use Generative AI, Bu Many Still Struggle to Scale.**
A new study conducted by Kaufman Rossin, a top 50 CPA and Advisory firm, has revealed an astonishing 94% of mid-market companies in the US are already utilizing generative AI, but less than 20% have successfully scaled its adoption to deliver tangible business results. Released on May 19th, 2026, the findings expose a significant gap between initial AI implementation and long-term effectiveness.
The research highlights a four-stage framework for companies to overcome the obstacles hindering their ability to scale AI adoption. The framework focuses on developing AI literacy, identifying key performance indicators, streamlining data management, and fostering a culture of collaboration between IT, operations, and data science teams.
**A Framework to Overcome Obstacles.**
The four-stage framework, which Kaufman Rossin calls the ‘AI Maturity Model’, emphasizes the importance of **assessing AI literacy** among employees, a crucial step in unlocking the full potential of AI-powered technologies. Many mid-market companies often overlook this aspect, which can lead to a lack of understanding and effective implementation of AI solutions.
Another key aspect of the AI Maturity Model is the identification of **key performance indicators (KPIs)** that accurately measure the success of AI adoption. Companies need to establish metrics that align with their business goals and ensure AI-driven initiatives deliver tangible returns on investment. By doing so, executives can make informed decisions about AI resource allocation and optimize its deployment.
**What This Means.**
For mid-market companies seeking to effectively scale AI adoption, it’s essential to recognize that simply introducing AI-powered technologies isn’t enough. Developing a comprehensive understanding of AI and its application within the organization, along with a structured approach to measuring success, will significantly enhance the likelihood of realizing long-term results from AI-driven initiatives. Companies should focus on fostering a culture of collaboration, continuous learning, and iterative improvement to bridge the gap between early AI adoption and sustained business success.
