As the federal government continues to grapple with the complexities of implementing artificial intelligence and data analytics, a key takeaway from the recent AI & Data Exchange 2026 conference is that the real challenge lies not in the technology itself, but in driving continuous process improvements across the entire organization.
One of the most insightful speakers at the conference was Casey Mulligan, a renowned economist and former chief economist at the Council of Economic Advisers. Mulligan emphasized that while AI and data analytics can be incredibly powerful tools for driving decision-making, they are only as effective as the processes they are applied to. In other words, if the underlying processes are inefficient, outdated, or poorly managed, even the most advanced AI systems will struggle to deliver meaningful results.
Mulligan’s message was underscored by a recent survey of federal agencies, which found that only 22% of respondents reported that their organizations have the necessary data and analytics capabilities to drive evidence-based decision-making. This suggests that many federal agencies are still struggling to get their data houses in order, and that the benefits of AI and data analytics are being held back by inefficient processes and outdated systems. As Mulligan noted, driving continuous process improvements is essential to unlocking the full potential of AI and data analytics in the federal government.
What This Means For You
The implications of Mulligan’s message are clear: if you’re working in the federal government, or in any organization that relies on data-driven decision-making, it’s time to take a hard look at your processes and identify areas for improvement. By investing in process improvements and building a strong foundation of data and analytics capabilities, you can unlock the full potential of AI and data analytics, and drive more effective decision-making throughout your organization.