The U.S. government’s role in AI and data science is critical as CIOs prioritize evaluating AI technologies, yet only half see budget increases. Common pitfalls in data analytics include disconnected workflows, lack of collaboration between data scientists and developers, and inadequate change management.
Many projects fail due to insufficient learning from experiments and poor integration. To drive value, organizations must focus on effective change management, iterative improvements, and seamless integration of digital tools into end-user workflows. Addressing these issues can help optimize AI and data investments and ensure business value.
