Presented by Granicus
New York State is building an artificial intelligence strategy designed to move beyond isolated experiments and make AI a practical, responsible part of government operations. In a conversation with State Gov Today’s George Jackson in New York City, New York Chief AI Officer Eleonore Fournier-Tombs discussed how the state is equipping its workforce to use AI, establishing safeguards for new applications and creating an innovation ecosystem that can serve more than 50 state agencies.
When Eleonore Fournier-Tombs became New York State’s chief AI officer, she took on a role that was still being defined.
Chief AI officer positions are relatively new across state government. While the broad expectations may be clear—help agencies adopt artificial intelligence responsibly—the precise mandate, operating model and relationship with individual agencies often must be built from the ground up.
Approximately nine months into the position, Fournier-Tombs said New York has organized its work around three pillars: innovation, governance and education.
Together, those pillars provide a framework for introducing AI across state government while balancing the pressure to deliver results with the need to protect residents, state employees and public data.
“Governance is a significant part of what we do, but it’s only one of the three pillars of our team,” Fournier-Tombs said.
Fournier-Tombs is based in New York City, where the office is developing a growing presence. The location places the team closer to universities, researchers, technology companies and major international gatherings, including the United Nations General Assembly.
“New York City is really a hub for AI and technical talent in the state,” she said.
That access is especially valuable as the office expands its team and looks for people who can help the state address the technical, organizational and policy dimensions of AI. At the same time, Fournier-Tombs emphasized that experienced public servants in Albany have been essential to helping her understand how state government operates.
Many members of her team have spent more than 20 years in state service. Their institutional knowledge has helped Fournier-Tombs, who came into the job without a background in New York State government, navigate its agencies, processes and responsibilities.
The innovation team is responsible for deploying general-purpose AI tools that can be used throughout state government. It also works on the infrastructure, procurement guidance and shared capabilities that agencies need to adopt AI effectively.
New York has already introduced an AI Pro tool based on Google’s Gemini large language model. The tool is available across state government and represents the type of shared technology that can be deployed centrally.
When an agency has a more specialized need—such as an application designed specifically for the Department of Labor or Department of Health—the Chief AI Office provides development support, technical guidance and access to the necessary infrastructure.
New York’s distributed IT structure is important to that process. A deputy commissioner of technology is assigned to each agency, giving the Chief AI Office a direct partner for identifying operational needs and evaluating potential solutions.
The office’s second pillar, governance, translates New York’s acceptable-use principles into a working process for agencies.
The state’s policy requires AI applications to be transparent, include appropriate human oversight, account for bias, fairness and equity, protect data and respect intellectual property. The challenge, Fournier-Tombs said, was determining how agencies could consistently put those principles into practice.
New York responded by developing an AI risk-assessment process based on the National Institute of Standards and Technology’s AI Risk Management Framework.
An agency considering an AI tool first completes a preliminary assessment that categorizes the proposed use as low, medium or high risk. The agency is then guided through questions addressing transparency, accountability, data protection and human oversight.
The process asks agencies to identify who is responsible for the tool, how its results will be evaluated and how the state will ensure that a person remains involved in consequential decisions.
The state worked with InnovateUS, a nonprofit organization that provides learning programs for public-sector professionals, to develop a two-hour asynchronous course covering basic AI literacy and ethics.
Employees who receive access to a state-authorized generative AI tool must complete the training. That includes employees using AI Pro, Microsoft Copilot or other platforms that New York may introduce.
The course explains what the technology is, what responsibilities employees have when using it and where they can seek assistance. It is intended to provide a common baseline rather than turn every employee into an AI specialist.
From there, training becomes more closely aligned with an employee’s role.
New York is developing more specialized instruction for leaders responsible for deploying AI in highly scrutinized environments. It is also training experienced developers to use AI for software development, application modernization and cybersecurity.
Fournier-Tombs cautioned against treating AI-assisted development as casual “vibe coding.” In state government, where applications may support critical services or contain sensitive information, AI-generated code requires technical knowledge, testing and careful oversight.
“We’re doing really careful deployment of these tools,” she said. “We’re really thinking through how we’re using AI for code modernization or for code scanning.”
The state does not expect AI education to have a defined endpoint. As the technology evolves and agencies identify more specific applications, New York expects to provide increasingly specialized training.
With foundational governance and training programs taking shape, New York is looking at how successful AI applications can move more quickly from experimentation into production.
Fournier-Tombs said this requires more than completing projects one at a time. It requires cultural change, shared infrastructure and an environment in which agencies can pursue their own ideas safely.
The state is developing an innovation strategy that includes internal AI infrastructure capable of running open-source models. The Chief AI Office would serve as the central hub, while individual agencies could establish their own innovation labs when they have the interest and capacity.
Those labs would give agencies controlled sandbox environments in which to test ideas. They would also provide access to the infrastructure, data layers and models needed to turn promising experiments into operational tools.
The goal is to enable agencies to drive projects based on their missions rather than depend on the Chief AI Office to develop every application.
“We’re thinking about AI innovation as an ecosystem of teams,” Fournier-Tombs said.
Under that model, the central office would focus more of its attention on foundational capabilities that can be reused across government.
Political leaders and the public increasingly expect AI investments to produce measurable results. At the same time, many people remain apprehensive about the technology, particularly its reliability and potential impact on employment.
Fournier-Tombs described the environment around AI as one of simultaneous impatience and fear. Government leaders want to see progress, but they also want assurance that new tools are safe, appropriately governed and worth the investment.
That dynamic makes communication essential.
The Chief AI Office works with the governor’s chamber and exchanges lessons with technology leaders in other states. New York is also beginning to measure the impact of individual deployments.
Some of the clearest opportunities have emerged in software development, legacy-code modernization and cybersecurity. The state also sees potential in customer service, including tools that can provide an initial level of support when residents submit questions, requests or claims.
One high-profile example is New York’s regulatory reset initiative, which uses AI to help review thousands of existing regulations.
Over time, governments accumulate rules that may be outdated, duplicative or no longer relevant. Reviewing that volume of material manually would require an enormous amount of time.
AI can process the information rapidly, identify patterns and surface regulations that may warrant closer examination. Human analysts can then review those suggestions and determine whether a rule should be revised or removed.
The technology does not make the final policy decision. Instead, it acts as a force multiplier that allows employees to focus their expertise and judgment where they are most valuable.
For Fournier-Tombs, who previously worked as a data scientist and researcher, that ability to analyze large volumes of information is one of AI’s most important strengths.
“It allows us to process masses and masses of information in a way that you couldn’t do just by hand,” she said.
The impact of AI on employment is also central to New York’s approach.
The state’s Future of Work initiative is examining how AI could affect New Yorkers and what policymakers can do to support workers through the transition. Fournier-Tombs said concerns about job displacement arise in nearly every public conversation she has about AI.
For state employees, the administration’s mandate is clear: AI is not being introduced to replace their jobs.
Instead, the state wants to reduce administrative burdens, streamline paperwork and give employees tools that improve the quality and efficiency of their work. The Chief AI Office is engaging unions, agencies and employees throughout that process.
“Our ultimate mandate is really upskilling everybody so that the workers themselves feel confident and empowered to use AI,” Fournier-Tombs said.
Employees also have an important role in identifying where AI could be useful. Because they understand the processes, bottlenecks and needs within their agencies, their input can help the state direct its investments toward practical problems.
New York is also making a major investment in AI research through Empire AI, a consortium centered at the University at Buffalo.
Empire AI provides computing resources and infrastructure that researchers can use to pursue projects intended to benefit New York residents and advance public-interest research.
The Chief AI Office does not direct that academic work, but Fournier-Tombs sees state government as a potential beneficiary—and, in some cases, a future client—of the research.
As researchers produce new tools, governance practices and findings, the state can evaluate whether those advances can be applied to improve services.
New York’s technology strategy is evolving alongside the AI market.
A year ago, Fournier-Tombs said, the strongest option often was to partner with large technology companies that had already invested heavily in developing, maintaining and updating advanced AI platforms.
Those commercial tools will continue to play an important role. New York is pursuing enterprise agreements that can make leading AI models available to agencies throughout the state.
At the same time, advances in open-source and open-weight models are giving the state more options for developing internal capacity. New York is investing in infrastructure that could allow it to operate some models within the state’s own environment.
That approach may provide greater control over costs, security, workforce training and environmental considerations.
Fournier-Tombs expects the result to be a hybrid model. Some applications will rely on proprietary commercial platforms, while others will use open-source technologies operated within state infrastructure.
The choice will depend on the agency’s mission, the sensitivity of its information and the specific problem it is trying to solve.
For New York, the objective is not simply to adopt more AI. It is to build the governance, workforce and infrastructure required to use the technology deliberately—and to ensure that innovation ultimately produces better outcomes for the people government serves.
This interview is part of The Future Public Servant, a State Gov Today initiative presented by Granicus in partnership with Carahsoft. The program explores how artificial intelligence, emerging technology and new approaches to leadership are changing public service—and how governments can prepare their workforces for what comes next. Additional interviews and resources are available at TheFuturePublicServant.com.