Innovation Insights: AI, Data, and Security Driving Federal Transformation

Presented by Carahsoft

At the Google Public Sector Summit, industry leaders from across the technology landscape shared how innovation, data strategy, and security are converging to shape the next era of government modernization. Executives from MongoDB, TTEC Digital, LMI, Box, Qanapi, AvePoint, Wiz, US AI, and Red Hat offered perspectives on how artificial intelligence, cloud-native development, and cultural change are redefining how agencies serve citizens and warfighters alike.

A clear theme emerged across every conversation: innovation is no longer optional—it’s the foundation of resilience, speed, and trust in government. But innovation without security, and speed without governance, can introduce new risks. The leaders at the Summit emphasized that modernization requires a balance of agility, responsibility, and cultural readiness to sustain meaningful outcomes.

From legacy to agility

Andrew Iskander, Regional Vice President for Federal at MongoDB, described how agencies must shift their mindsets from monolithic, legacy architectures to agile, interoperable solutions. Traditional relational databases that powered government systems for decades are no longer suited for the demands of modern AI applications, he said. Instead, document-model databases and no-SQL architectures allow agencies to handle structured and unstructured data at scale, enabling the speed and flexibility AI requires.

Iskander noted that achieving this shift is as much cultural as it is technical. “It starts from the top,” he said. “Leaders need to drive a culture that’s open to failing fast and learning quickly.” Agencies that cling to one-vendor dependencies or outdated architectures, he added, risk being unable to recover from cloud outages or security incidents. Modern government, he argued, must be built around one interoperable code base that runs across multiple cloud service providers—ensuring both resilience and innovation.

Trust and transparency at the core of AI

For Christen Smith, President of Solutions at LMI, innovation must begin with trust. She cautioned that agencies racing to deploy AI must not lose sight of data integrity and accountability. “If you didn’t trust or understand your data before AI got a hold of it, you’re not going to trust or understand it any better as the basis of an AI-generated output,” she said.

Smith stressed that AI systems must be transparent and explainable so that decision-makers can trace how algorithms reach their conclusions. The goal, she said, isn’t product speed but mission speed—enabling government operators to make confident, informed decisions without hesitation. LMI, she explained, helps agencies establish secure, scalable AI environments that enable faster outcomes “without compromising either privacy or mission, because speed only matters when it’s trusted.”

Citizen experience as a mission priority

Teresa Sabol, Vice President of Federal at TTEC Digital, brought the conversation back to the citizen. She highlighted how AI and automation can dramatically improve the customer experience across government services—from self-service tools that handle routine requests to intelligent systems that empower human agents to solve complex problems.

Drawing on her experience as a former IRS contact center director, Sabol described how AI can reduce call wait times by automating lookups and data retrieval, freeing human agents to focus on empathy and problem-solving. “The more you put to self-service,” she said, “the more time agents have to handle the complicated issues with understanding and compassion.” For TTEC Digital, empathy isn’t just a design feature—it’s a capability that must be built into every AI interaction.

Data as the new weapon

Michelle Davis, Senior Director for DoD Solution Architecture at Red Hat, described data as “the most important weapon we have.” She said the demand for data will only grow, making it essential for agencies to adopt open standards, hybrid architectures, and federated AI models that allow data to be processed where it resides—at the edge, in the cloud, or on-premises—without compromising security.

Davis emphasized the need for cultural readiness to match the pace of technology. “It’s not a technology problem—it’s a culture problem,” she said. Training, experimentation, and environments that allow teams to “fail fast and learn fast” are critical to fully leveraging the power of AI and data.

Security redefined for speed

Security was a central focus across nearly every conversation. Chris Saunders, Worldwide Director of Public Sector Solution Engineering at Wiz, argued that government’s traditional approach to cybersecurity—built around compliance checklists and point-in-time assessments—no longer works. “Industry looks at risk differently,” he said. “They focus on what puts them most at risk right now.”

To truly modernize, Saunders said, agencies must democratize security—creating shared visibility into risk data across development, operations, and security teams. When everyone uses the same data to prioritize risk, agencies can scale security without slowing innovation.

Macey Smith, Co-Founder and Chief Growth Officer at US AI, echoed that theme. Her company embeds security directly into its intelligent computing platform so agencies can innovate faster without sacrificing compliance. Historically, she said, “security has slowed down modernization,” but integrating it into the foundation of technology allows agencies to reduce development cycles from years to months—or even weeks. “AI can now build applications in hours or days,” she said, predicting that traditional agile development will soon give way to AI-driven development models.

Building confidence in trusted data

For Trent Telford, CEO of Qanapi, the race to AI is meaningless without trust in the underlying data. “Garbage in, garbage out,” he warned, “but AI aggregates that at an exponential level.” To prevent “hallucinated” outputs and data manipulation, Telford’s team uses cryptographic chains of provenance to verify the origin, integrity, and permissions of every data source.

He advised agencies to start small—pilot projects that demonstrate verifiable data trust before scaling. “You can’t change all your historical systems overnight,” he said. “But if you take an API-first approach, you can connect old and new data sources securely and start proving the value.”

Governance as the anchor

Jason Gray, Managing Director for Global Federal Government at Box and former CIO at both the Department of Education and USAID, underscored that every modernization effort must be rooted in governance. “It starts with cross-functional teams—mission, privacy, and security leaders working together from the start,” he said.

Transparency and explainability in data management, he noted, are essential for maintaining citizen trust. Gray also emphasized culture as a driver of innovation: “It’s not about saying no; it’s about finding a safe, secure, scalable way to yes.” That mindset, he said, is what allows agencies to innovate while maintaining the confidence of leadership and the public.

Balancing innovation with resilience

Finally, Heather Harinstein, Director of Federal at AvePoint, cautioned that agencies’ rush to adopt AI has exposed new vulnerabilities. Her company’s research found that 75 percent of organizations experience security issues linked to AI adoption, often delaying rollouts by months. She encouraged agencies to focus on three pillars: security (ensuring only the right people access the right data), governance (automating compliance and content oversight), and resilience (preparing to recover quickly from internal or external threats).

“Attacks are going to happen,” she said. “Whether internal or external, agencies must be able to respond and recover.”

The path forward

Taken together, these perspectives reveal a federal technology community that’s deeply aware of both the promise and the peril of rapid innovation. AI and cloud modernization are transforming how government operates—but only when built on a foundation of secure data, strong governance, cultural readiness, and a shared commitment to public trust.

As Sabol put it, the ultimate goal is simple: to help government deliver services with greater empathy, efficiency, and confidence. That’s the true measure of innovation in the public sector—and the driving force behind every conversation at the Google Public Sector Summit.