Government

A new class of public sector C-suite leaders is reshaping how government executes on its vision for a citizen-centric, digital-first government. Roles such as chief AI, data, customer experience, innovation, and workforce officers—created through recent laws and executive directives—are now in place across many jurisdictions. Their rise signals a major shift. These government leaders are responsible for executing a digital-first, citizen-centric vision and are shifting accountability from back-office IT functions to the front-stage experiences residents rely on every day. With this leadership capacity in place, government is positioned to be better equipped to drive modernization, accelerate AI adoption, and strengthen service quality.

These new government C-suite leaders translate digital-first priorities into operational practice. Working across agencies, they guide the adoption of unified resident portals, AI-enabled virtual assistants, shared data platforms, and integrated service delivery models. By unifying technology, data, and design, these executives will help governments deliver services that are simpler, more interoperable, and more consistent across programs.

Across the country, these executives are already reshaping how government services are designed and delivered. The US Department of Homeland Security’s Office of Customer Experienceis demonstrating how CX leadership at the executive level can unify service design, policy, and technology to improve resident interactions at scale. According to the NASCIO–Georgetown Beeck Center State Chief Data Officer (CDO) Survey, state CDOs are evolving from technical advisors to enterprise leaders—establishing data governance and shared platforms that enable more consistent, interoperable digital services.

States and cities such as Arkansas, Nevada, Florida, Connecticut, New York City, and Denver are elevating chief workforce development officers to coordinate labor, education, and technology strategies. These leaders will strengthen the workforce-education ecosystem, enable talent mobility, and use AI to redesign jobs for more effective human-machine collaboration. 

The government C-suite will ground modernization in real mission needs—from aligning eligibility and case management systems within Health and Human Services (HHS), to redesigning licensing and permitting in transportation agencies, to using AI and linked data to connect residents with employment opportunities in real time. In 2026, the presence of these roles marks a turning point: government now has the leadership structure required to deliver on a truly digital-first, citizen-centric vision.

After decades of expensive legacy system replacement projects that aimed for a “big-bang” launch but often failed to deliver results, governments in 2026 will shift toward incremental, modular, and AI-assisted modernization that delivers value earlier. Instead of replacing entire platforms at once, agencies will modernize in smaller waves using agentic workflows, automated code conversion, and cloud architectures to reduce technical debt and create more flexible, adaptable systems.

Modernization in 2026 is set to be increasingly grounded in modular, AI-assisted approaches that reduce risk while increasing momentum. Agentic workflows, automated code conversion, and AI-enabled testing will help agencies refactor legacy code and modernize systems in manageable waves. These upgrades are not only technical—they strengthen the architecture needed to integrate data across programs, support shared service components, and deliver more intuitive digital experiences. As part of this move to modernize, states are preparing to use the April 2026 DOJ accessibility deadline to modify public-facing systems so that accessibility is built into new platforms from the start. Together, these capabilities can create the foundation for interoperability, secure data sharing, and responsible AI deployment.

Agencies are already demonstrating how incremental, AI-assisted modernization can improve both mission delivery and resident experience.

• At the federal level, US Citizenship and Immigration Services is replacing legacy components through smaller, AI-enabled modernization waves that preserve mission continuity while building a more adaptable, secure foundation for future innovation.
• HR1 requirements are catalyzing state Medicaid eligibility and workforce systems modernization, using modular components and automated code conversion to update decades-old platforms without risking service disruption.
• Modernization efforts are also reshaping licensing and permitting systems in transportation and public safety agencies, where incremental upgrades and cloud-native architectures are reducing backlogs and creating more intuitive digital experiences for residents.

Across all government sectors and missions, modernization delivered in waves can reduce technical debt, improve program performance, and create the architectural foundation needed for interoperability and AI at scale.  

These gains will also free capacity for frontline staff and improve the digital experiences residents rely on across programs. In 2026, this shift marks a turning point: modernizing in modular waves will strengthen the technical and operational resilience needed to deliver mission-critical services more consistently.

Modernized systems, stronger data governance, and cross-functional C-suite leadership will give governments the foundation to make interoperable services real. States and localities are using their modernized infrastructure to link data, applications, and workflows across agencies, supporting “no wrong door" service pathways that reduce administrative burden for residents and staff. Interoperability is the outcome of these efforts and becomes possible only when modernized systems, strong data governance, and empowered C-suite leaders come together to support seamless, “no wrong door” access to services. This shift—from siloed operations to integrated systems—enables governments to design services around people rather than processes.

Unified resident portals, supported by shared data hubs and federated data management, will connect services behind the scenes while keeping navigation simple for residents. Integrating information across health, housing, workforce, and public safety programs will help governments respond earlier, make decisions with fuller context, and reduce the friction caused by disconnected systems. Interoperability gives frontline workers better visibility into resident needs and creates more connected, accessible digital experiences.

Across the country, governments are demonstrating what it looks like to operate as one.

• In Oregon, Multnomah County modernized its data infrastructure to better address homelessness and housing insecurity, replacing manual, siloed systems with an integrated data mart that provides timelier insight into who is experiencing homelessness and which interventions are most effective.
• In Florida, the Division of Emergency Management unified data across state agencies and volunteer networks during disaster-relief efforts, creating a single source of truth for faster decision-making and quicker distribution of aid—reducing delays and trauma during crisis events.

These examples show how integrated data and shared systems can support more coordinated, community-centered service delivery.

Interoperability is becoming the next maturity milestone for modern government. As agencies adopt shared data governance frameworks, common identity and eligibility standards, and modular architectures, they can connect services across programs and jurisdictions without compromising security.

State–local IT coordination will also strengthen interoperability as more states deliver shared IT services and data platforms that support local governments—reflecting priorities highlighted in the 2025 NASCIO State CIO Survey.

These capabilities are creating the conditions for responsible AI adoption, supporting more accurate eligibility determinations, coordinated casework, and proactive outreach based on cleaner, more complete data.

In 2026, the opportunity is to bring modernization, data governance, and human-centered design together into a single roadmap for connected services. Governments that advance these priorities in tandem move closer to seamless, integrated experiences—delivering services that are coordinated, intuitive, and designed around the people they aim to serve.  

Cyber threats to government continue to rise in both volume and sophistication. State CIOs consistently rank cybersecurity as their top priority, and federal watchdogs report sustained attacks targeting critical infrastructure, from water systems to schools and hospitals. Cybersecurity is not only about preventing attacks, but also about protecting the continuity of the services residents rely on most.

To guard against cyberattacks and emerging AI-assisted threats, government is doubling down on perimeterless approaches that combine Zero Trust principles, data sovereignty, and modern architectures. Zero Trust is shaping how systems verify identity, restrict access, and segment networks. Meanwhile, data sovereignty helps clarify where sensitive information resides and who controls it across multi-cloud and multi-jurisdictional environments.

Additionally, we’re seeing all levels of government move toward whole-of-government models. Governments now treat cybersecurity as a shared responsibility across agencies and levels of government. As nation-state threats intensify and the traditional network perimeter continues to erode, these approaches will converge to help governments maintain legal control of sensitive data and protect connected systems.  

The federal government has already established policy frameworks to guide cybersecurity implementation. Agencies can align with models such as NIST’s Zero Trust Architecture (SP 800-207) and the CISA Zero Trust Maturity Model. The White House’s AI-ISAC will strengthen threat-intelligence sharing and help detect AI-enabled attacks. State and local governments will continue to rely on the US Congress to reauthorize CISA’s State and Local Cybersecurity Grant Program in 2026. States rely on these funds to implement the whole of government approach.

To mitigate emerging risks from AI-assisted and future quantum-enabled attacks, public and private sector organizations are collaborating to combine Zero Trust architectures with post-quantum cryptography. These approaches can help agencies protect mission-critical systems even as threats grow more sophisticated. In 2026, cybersecurity will become a continuous capability, embedded in modernization efforts and aligned to mission outcomes to sustain public confidence in a more digital, interconnected government.

Given the broad societal impact of governmental actions, many leaders have chosen wisely to first establish state-wide or government-wide AI policies before scaling. Those who have put these foundational elements in place are positioned to accelerate adoption of AI and embed it into operations at scale in the next year. They do so while keeping a human involved as the decision-maker to prevent bias or unjust outcomes that impact individual rights and erode public trust in government.

The US federal government along with a growing number of states is leading the way by establishing Chief AI Officers to guide implementation of comprehensive frameworks along with investments to train employees on how to use AI tools in their job. A growing number of Governors have also put partnerships in place with academia and private companies to create state-wide or government-wide pilots and employee training programs. Examples include the State of Pennsylvania’s partnership with OpenAI and New Jersey’s AI Assistant which provides a generative AI platform with a secure “sandbox” environment that employees can use to test AI applications before scaling across government operations.

At the federal level, agencies are advancing implementation under the White House AI Executive Order and OMB M-25-21 memorandum, while navigating an increasingly complex compliance environment driven by more than 94 AI-related government-wide requirements tracked by the GAO.

As more parts of government adopt AI-driven agentic workflows at scale, Chief AI Officers must ensure that systems are monitored and cross-functional teams are aligned to scale responsible AI across operations. 

Government leaders remain cautious about scaling generative AI in frontline services. According to NASCIO’s 2025 State CIO Survey, nearly three-quarters of CIOs cite concerns around model accuracy, data security, and workforce readiness. Federal officials echo similar risks, pointing to compliance requirements, limited technical resources, and budgets. Responsible AI will remain a central priority with risk mitigation strategies grounded in policies like NIST’s AI Risk Management Framework, guiding decisions about where and how models are deployed. 

AI adoption and readiness signals

Nearly 75% of CIOs report serious concerns about using GenAI in direct citizen services — citing accuracy, security, and workforce readiness.

According to The 2025 State CIO Survey:

• 82% of CIO organization employees now use GenAI tools in daily work (up from 53% last year).

• 90% of states are running pilot projects and 86% are conducting proofs of concept.

• 71% are training employees.

• Only 25% of states have dedicated funding.

As government realizes the promise of AI in 2026, success is unlikely to be defined by speed and cost-savings alone, but by how effectively leaders balance innovation with risks related to bias, safety, security, misinformation, and public trust.

Even with stronger AI policies taking shape, the challenge ahead is preparing the workforce. Public employees are eager to use new tools but many still need the right training and data skills to use them effectively and responsibly. Turning AI plans into real results means investing in people and developing teams who understand how to build, test, and manage AI systems as part of their everyday work.  

NASCIO’s 2025 State CIO Survey identified workforce skills as one of the top three barriers to modernization. To address this, agencies are launching targeted reskilling programs, integrating “Responsible-AI 101” into mandatory training, and partnering with universities to build public-sector AI academies—so every employee can apply AI responsibly, strengthen public trust, and accelerate mission results.   

Various federal government agencies have launched internal AI Workforce Resource Hubs focused on equipping employees with the knowledge on how to use AI responsibly and effectively. Similarly, at the state level, the National Association of State Workforce Agencies is creating an AI Resources Hub to help state workforce agencies train public employees.  

How federal agencies are preparing an AI-ready workforce

As part of the US government’s AI Action Plan, federal agencies are equipping employees for responsible AI use. The General Services Administration’s AI Training Series supports this effort, helping staff at every level learn how to accelerate AI innovation, build American AI infrastructure, and lead in international AI diplomacy and security. This effort provides a blueprint for states and local governments to follow.

An AI-literate workforce is essential for sustainable modernization, and in 2026, upskilling becomes integral to modernizing how government delivers public services.