Federal agencies are predicted to increasingly integrate artificial intelligence-driven defenses and unified cloud governance for more resilient, secure-by-design IT in 2026.
AI will be the fastest-growing IT spend category — impacting the entire stack, from infrastructure to software and services — as the driver of innovation, according to technology experts.
As a result, federal CIOs and chief AI officers are bullish on transforming generative AI pilots into full-scale production systems boosting operational efficiency and improving mission outcomes in 2026. The year should see projects building on 2025’s momentum and mark early maturation of the AI ecosystem.
“We’ll see robust regulatory frameworks emerge, alongside investments in data infrastructure, as AI evolves from consuming data to generating it,” says Nic Jefferson, vice president of government affairs at Dell. “This year, AI moves from promise to reality.”
GET READY: Here are the four biggest artificial intelligence trends heading into 2026.
AI Evolves Past Pilots
To this point, agencies have cautiously piloted AI, but expect them to fast-track the technology to improve the responsiveness of government services — driving a surge in public-private partnerships. These partnerships ensure rapid AI integration, Jefferson says.
AI policy and regulation will become critical in 2026.
“The rise of agentic AI — autonomous systems capable of complex decision-making — will challenge existing norms, forcing urgent conversations around transparency, accountability and human oversight,” Jefferson says.
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Technology Acquisition Accelerates
Agencies (and the Department of Defense, in particular) want to shorten the time to acquire technology, especially AI, and make it available to the workforce at commercial speed, says Max Claps, research director for worldwide national government platforms and technologies at IDC.
“By centralizing acquisitions through OneGov, and by applying approaches like Commercial Solutions Openings and continuous Authorization to Operate, the federal government wants to avoid traditional lengthy processes and engage nontraditional vendors to develop and deploy capabilities with increasing speed and agility, while improving security,” Claps says.
On the other hand, the phased rollout of the Cybersecurity Maturity Model Certification 2.0 could become a barrier to entry, Claps says.
A single, federal standard is essential because we cannot scale AI while navigating a 50-state patchwork of conflicting and costly regulations.”
Randy Dougherty
CIO, Trellix
A Simplified, United AI Policy Framework
The most significant federal IT trend for 2026 is the move toward a simplified, unified AI policy framework, says Randy Dougherty, CIO of Trellix.
“A single, federal standard is essential because we cannot scale AI while navigating a 50-state patchwork of conflicting and costly regulations,” Dougherty says.
The executive order on ensuring a national policy framework for AI that President Trump issued in December is an effort to pre-empt that patchwork, one which prioritizes rapid industry innovation over states’ privacy concerns and will lead to prolonged litigation.
The White House framework provides the legal and technical certainty needed for innovation by removing compliance obstacles caused by varying state laws, Dougherty says.
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Post-Quantum Cryptography Becomes the Baseline
The security paradigm is shifting away from software-based perimeter defenses toward physics-based, hardware-enforced isolation, says Ryan Simpson, chief technologist for federal partners at NVIDIA.
One major driver is the rise of data processing units, which offload security functions from the CPU and create an internal air gap between controls and application workloads.
“By isolating security policy enforcement at the hardware level, DPUs ensure that, even if a host system is compromised, the underlying security architecture remains intact,” Simpson says.
Post-quantum cryptography is also becoming a baseline requirement for agencies, rather than a future consideration.
“Agencies are accelerating transitions to quantum-resistant algorithms to address ‘harvest now, decrypt later’ threats, in which adversaries collect encrypted data today with the expectation of breaking it once quantum computing capabilities mature,” Simpson says.
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Aggressive Internal Upskilling
The talent gap is now a critical operational risk, with some contractors winning federal projects they cannot staff due to a severe shortage of specialized expertise, Dougherty says.
There is a particularly acute need for professionals who have both high-level AI skills and the necessary top-secret security clearances for federal work.
To bridge the workforce gap, agencies are shifting focus from external hiring to aggressive internal upskilling by training veteran analysts specifically in AI defense and cloud-native architecture.
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