Presented by SAP & Carahsoft
Episode 2 of Mission Forward, the video podcast series presented by SAP and Carahsoft, continues the exploration of how federal agencies are driving efficiency and innovation—this time focusing on the shift to AI-powered, standards-based modernization.
The federal government is entering a new phase of modernization—one defined not just by upgrading legacy systems, but by fundamentally rethinking how technology supports mission delivery. In this episode, SAP Executive Advisors Brian Laird and Tahera Zamanzada explore how agencies are moving from fragmented, services-led environments to architectures that enable speed, scalability, and collaboration.
At the center of this shift is artificial intelligence, not as a standalone capability, but as an embedded function that connects systems, data, and processes. When AI is built into the architecture itself, it becomes a driver of efficiency and insight—helping agencies move faster while reducing the burden of maintaining outdated, customized systems.
For decades, federal agencies built systems to solve individual problems. While effective in the moment, those solutions created a patchwork of disconnected systems across government. Finance, HR, procurement, and supply chain functions—many of which share similar underlying processes—were implemented separately, leading to duplication and inefficiency.
Laird points out that this fragmentation has resulted in significant technical debt and limited the government’s ability to operate as a unified enterprise. The opportunity now is to recognize the commonality across these functions and move toward shared services that can be replicated and scaled across agencies.
Standards-based architectures make this possible. By aligning around common data models and repeatable processes, agencies can begin to reuse what works—accelerating implementation and improving outcomes. This shift also enhances interoperability, allowing agencies to collaborate more effectively and leverage collective buying power.
While the vision for modernization is clear, the path forward is not without challenges. One of the most common pitfalls agencies face is attempting large-scale, all-at-once transformations. These “big bang” approaches often struggle under their own complexity, leading to delays, cost overruns, and limited adoption.
Instead, both Laird and Zamanzada advocate for an incremental approach. Agencies should begin with targeted pilot programs in low-risk, high-impact areas—testing new technologies, learning from early results, and scaling success over time.
This approach reflects a key mindset shift: modernization is not a one-time event, but an ongoing process. By starting small and iterating, agencies can build momentum, demonstrate value, and reduce the risk associated with large-scale change.
A major barrier to AI adoption in government is the perception that data must be fully cleansed and standardized before any meaningful progress can be made. Zamanzada challenges this assumption, emphasizing that agencies should prioritize progress over perfection.
AI can actually play a role in identifying data quality issues. By piloting AI in high-volume use cases, agencies can uncover gaps, reduce redundancy, and begin improving their data environments in parallel with implementation.
This approach not only accelerates adoption but also reveals inefficiencies that might otherwise remain hidden. In many cases, agencies discover multiple systems performing the same function—creating opportunities to streamline operations and reallocate resources.
The success of this transformation is not just about technology—it’s also about people. Today’s federal workforce is more digitally fluent than ever, with employees who expect access to modern tools and data-driven insights.
Laird highlights that this growing digital acumen presents a significant opportunity. Employees are not only capable of using advanced technologies—they are eager to do so. Agencies that embrace this shift can empower their workforce, improve productivity, and accelerate innovation.
At the same time, attracting the next generation of federal talent requires a different approach. As Zamanzada notes, younger professionals are motivated by mission outcomes, not by maintaining legacy IT systems. Providing access to cutting-edge tools and meaningful work is essential to bringing new talent into public service.
One of the most important enablers of standards-based modernization is interoperability—the ability for systems, data, and processes to work seamlessly across organizations.
By adopting common platforms and shared data backbones, agencies can take successful solutions from one environment and apply them to another. This not only improves efficiency but also accelerates learning across government.
The shift toward interoperability also supports a broader cultural change. As agencies begin to share solutions and best practices, they move away from the idea that their challenges are entirely unique. Instead, they recognize the value of collaboration and collective progress.
Despite the clear benefits of shared services and standards-based approaches, cultural resistance remains a significant hurdle. Agencies often view themselves as distinct, with unique missions that require customized solutions.
Overcoming this mindset requires intentional effort. Zamanzada emphasizes the importance of building communities and coalitions that encourage collaboration across agencies. By highlighting shared challenges and demonstrating successful outcomes, these groups can help shift perceptions and drive adoption.
Education and evangelization play a critical role in this process. As more agencies see the benefits of standardized approaches, momentum builds—making it easier for others to follow.
Ultimately, successful modernization starts with a clear understanding of the desired outcome. Laird stresses that agencies must define what success looks like—whether it’s improved readiness, better auditability, or enhanced service delivery—before implementing new technology.
From there, standards-based architectures and AI can serve as the foundation and accelerant for achieving those goals. Technology becomes a means to an end, enabling agencies to deliver measurable improvements in mission performance.
The transition from services-led to standards-based modernization represents more than a technical upgrade—it’s a shift in how government operates. By embracing shared services, prioritizing interoperability, and adopting an iterative approach to change, agencies can reduce complexity and unlock new levels of efficiency.
AI plays a central role in this future, helping agencies connect data, streamline processes, and empower their workforce. But just as important are the cultural and organizational changes that support this transformation.
Agencies that succeed will be those that move quickly, learn continuously, and focus relentlessly on mission outcomes—building a modern, resilient foundation for the future of government.