When it comes to modernization and new technology, government agencies usually don’t have an innovation problem. They have an adoption problem. Legacy tools and databases create seams that jeopardize the flow of real-time, mission-critical data. Potentially dozens of point-by-point solutions lead to disconnected systems and costly integration challenges. And for all its benefits, AI highlights the need to modernize what’s outdated.
There’s a misconception that reform means shutting down an old system, ripping and replacing it. What it actually means is shifting your mindset to think in terms of platforms — unified data foundations, that is — rather than individual solutions. Such platforms are a collection of capabilities that sit alongside your existing systems, handle many different workloads and help ensure that your data is AI-ready. You can retire legacy technology over time, ultimately benefiting some of your highest-value employees.
“It frees up your scarcest and most talented engineers from being full-time plumbers to doing mission-critical work, focusing on business logic [and] building features,” said Devin Dickerson, Principal Technologist with MongoDB. “Giving people the opportunity to contribute to the mission instead of maintenance is probably … the best retention strategy.”
In this video interview, Dickerson discusses how a unified data-platform strategy can help overcome obstacles to agency modernization. Topics include:
- The dangers of fragmented, ungoverned data
- How point-by-point solutions develop and destabilize systems
- Why modernizing your data layer is critical to AI-readiness