Government leaders know that AI has the potential to accelerate software development and modernize aging systems and their cryptography. But despite identifying promising use cases and achieving some early wins, many agencies remain cautious. The problem is that most organizations lack the policies and enterprise control capabilities needed to address requirements around compliance, performance and security. So while AI’s potential is promising, the risk can feel daunting.
Closing that gap requires a more integrated approach to modernization. Rather than using AI for isolated coding tasks, agencies can leverage agentic orchestration to create workflows that span the entire software development lifecycle (SDLC). Risk management should not be treated as a final checkpoint. Instead, agencies should build governance and human oversight into every stage of the process with software development policies and agency practices instantiated in the AI platform used by development teams.
“Agencies want to transform how they build and maintain applications, but they can’t afford to trade velocity for risk,” said Russ Hopler, IBM Solution Architect at Four Inc. “The challenge is to account for compliance, performance and security in a way that gets them a healthy balance.”
In this video interview, Hopler explains how agencies can use agentic AI to automate SDLC best practices with enterprise visibility and governance built in. Topics include:
- Moving beyond code generation to AI-powered software development lifecycle management.
- Balancing innovation with security, governance, AI cost controls, and federal compliance requirements.
- Modernizing legacy applications and code cryptography faster without compromising performance or reliability.