Artificial Intelligence: a Force Multiplier for Government

Every day, millions of Americans interact with digital services that are fast, seamless, and remarkably responsive. A package ordered today can be tracked in real time and delivered tomorrow. A banking app can instantly confirm a transaction or flag a suspicious charge. A rideshare appears within minutes.

But when people interact with government, their experience often feels very different. A simple request may mean navigating multiple websites, completing complex forms, or waiting days for a response.

With the relentless advance of technology, the public increasingly expects government to match the speed, accessibility, and responsiveness they experience elsewhere.

Despite these demands, governments also continue to be constrained by tight budgets, aging infrastructures, workforces stretched thin by retirements and turnover, and inability to add positions.

One promising strategy to respond to the increasing demands on government is to leverage artificial intelligence (AI). When implemented strategically and responsively, AI has the potential to help government operate more efficiently, expand service capacity, and improve the experiences of both employees and the public.

Therefore, the question for public sector leaders today is not whether to explore AI. The real question is how to leverage this technology responsibly and intentionally.

AI is already improving government service

Public-sector organizations are leveraging AI to deliver more responsive service. For example, AI-driven tools such as chatbots or virtual assistants answer frequently asked questions about property taxes, licensing, court dates, or public health services. These tools provide 24/7 responsiveness without requiring more staff.

Handling these routine inquiries automatically also allows employees to focus on more impactful work. In child support services, for example, AI tools send appointment reminders and respond to document requests, allowing caseworkers to focus on families needing intensive support.

AI’s analytical capabilities also enable government to deliver services proactively:

Predictive models forecast demand for emergency services, identify infrastructure maintenance needs, and flag public health risks before they escalate.
Public works departments use AI tools to analyze historical data on road conditions, weather patterns, and traffic volumes to prioritize repairs, thus reducing service disruptions and overtime.
Human services agencies use predictive analytics to identify clients at risk of homelessness, enabling early intervention instead of responding to crises.

AI must be adopted carefully and strategically

These applications illustrate how government can apply AI tools to become more effective, strategic and proactive. However, public-sector organizations should resist the impulse to hastily deploy AI enterprise-wide or copy what other organizations are doing.

When AI is adopted in a structured and intentional way, the result is a practical pathway to improving operational efficiency and service capacity without increasing headcount.

Successful AI implementation isn’t just about technology or algorithms. Instead, it’s an organizational change initiative that requires strategy and planning. Successful adoption typically follows a step-by-step approach that treats AI as a force multiplier that augments – but does not replace – human expertise and existing staff. Organizations applying this change strategy:

Established strong AI governance and clear policies
Assessed organizational readiness
Redesigned workflows before automating them
Conducted AI pilots and measured impacts before scaling enterprise-wide
Engaged the workforce early and often

Establish strong AI governance and clear policies

Structure and policies ensure this technology is used responsibly, ethically, and transparency. Governance is not bureaucracy – it is risk management.

Clear AI guardrails give employees confidence and assure elected officials that AI will be implemented responsibly. An oversight committee (e.g., including human resources, legal, IT, program leadership, and other stakeholder groups) can review proposed applications and monitor outcomes. HR, in particular, should be a key architect of AI strategy and policies because AI’s main impact will be on work and the workforce.

Some key governance / policy considerations:

AI guiding principles (e.g., fairness, transparency, accountability, people-centric design)
Legal, ethical and privacy considerations
Acceptable and prohibited uses
Cybersecurity guardrails
Cross-functional collaboration
Requirements for human oversight

Assess organizational readiness

A readiness assessment helps determine if the necessary conditions exist to implement AI successfully.

A key starting point is strategic alignment – whether AI initiatives support organizational priorities. This includes identifying the specific problems AI could solve and how these potential applications support mission and goals.

Data readiness is also critical. Because AI systems depend on reliable data, organizations should assess whether it has accurate, reliable and accessible data; and whether policies exist to manage data responsibly.

Organizations should also evaluate their technology and infrastructure, including computing capacity, systems integration, cybersecurity, and availability of cloud or internal platforms to support AI tools.

Redesign workflows

AI can improve work processes when organizations first rethink and redesign these processes. Simply automating inefficient workflows (sometimes known as “paving the cow path”) rarely produces meaningful improvements.

Instead, organizations should first map current workflows within and across units; as well as identify and fix bottlenecks, pain points, handoff delays, manual and time-consuming work, and processes that cause errors or rework.

Process redesign also identifies ways to automate paper-based or in-person interactions. Online intake forms, electronic signatures, and automated notifications can potentially reduce administrative burden and expand capacity and service without increasing staffing.

Pilot AI, measure results, and then scale strategically

Implementing AI should follow the same disciplined project management as any major change. Pilot projects are one of the most effective ways to introduce AI, especially in government. Pilots provide proof of concept, reduce risk, build trust, and create a structured pathway to wider adoption.

Instead of committing large amounts of money or changing enterprise systems immediately, a pilot – a controlled rollout – limits risk within a defined scope, timeline, function and/or department. Limiting risk is especially important in the public sector, where mistakes can become public and embarrassing. Slowly ramping AI up can help build confidence and support.

One local government, for example, categorized AI-suitable processes into low, medium and high risk. It then piloted AI on low-risk but high-impact functions to build confidence about adopting the technology more broadly.

Strong pilots include:

A specific AI application with high potential value but low risk of public harm
A strong champion(s)
A clearly defined scope
Expected measurable outcomes and success criteria
Baseline performance data
A defined testing period

Pilots should track AI performance improvements. Some common metrics:

Faster turnaround time
Lower processing costs
Fewer errors
Reduced backlog
Improved customer (internal and external) satisfaction
Staff and staff time reallocated to higher-value work

Successful pilots can then be scaled across departments. As one local government official put it, “Leaders must be willing to try and then pivot quickly when there are issues.” Pilot projects provide this agility before full-scale implementation.

Engage the workforce early

Adopting technology succeeds or fails based on people, especially in government.

According to the 80/20 rule of AI implementation, only 20 percent of successful AI implementations involve technology. The other 80 percent is about people and change management, including convincing employees to embrace and use this new technology.

Employees have questions about how AI may affect their organization, their work, and themselves. According to one global survey, 54 percent of frontline public sector workers fear that AI might replace their jobs. That’s why effective communication must answer the AI “why” by framing it as a capacity-building tool that can reduce repetitive tasks and drudgery, and enhance impact, but not eliminate positions.

In fact, many local governments are considering using AI precisely because they cannot add positions.

Transparent communication about policies, goals, plans, actions, milestones, ethical use, and safeguards helps maintain trust and encourages adoption. Communication should also be a two-way street. For example, by asking employees to identify ways AI can improve operations.

Training is equally important. AI Literacy is one of the hardest-to-find skills globally. Organizations around the world are building this literacy to help their employees apply AI technology with judgment and confidence. This includes building practical skills such as:

Interpreting AI data and outputs
Ensuring data quality
Identifying and managing exceptions from expected outcomes
Maintaining ethical standards

Hands-on workshops, sandbox environments, and departmental AI champions can demystify the technology. Employees who see AI actually reduce tedious work often become its strongest advocates.

A force multiplier for government

If implemented strategically and intentionally, AI can be force multiplier for government by offering a realistic strategy to meet heightened public expectations without increasing staff. The goal is not to replace employees but to empower them, transforming limited capacity into greater impact through structured and intentional adoption of AI tools.

By creating strong governance and clear policies, assessing readiness, targeting high-impact tasks, redesigning workflows, enabling the workforce, and measuring outcomes, public-sector organizations can improve operational efficiency and service delivery while relying on existing staff and resources.

Done well, adopting AI is a win-win – delivering better government performance and better outcomes for the people government serves.

If you are ready to begin your AI journey, CPS HR Consulting can help assess your organization’s readiness and identify practical next steps. We work alongside public sector leaders to ensure AI is implemented thoughtfully, responsibly, and with measurable impact. Reach out to start the conversation.

Bob Lavigna has more than 40 years of experience leading HR organizations and programs at all levels of government, in public higher education, and the nonprofit sector. He writes frequently for professional publications and has spoken at conferences across the U.S. and abroad.

Bob’s book, Engaging Government Employees: Motivate and Inspire Your People to Achieve Superior Performance (Harper Collins Publishing), is the only book to focus exclusively on measuring and improving engagement in the unique environment of the public sector.

He is an elected Fellow of the National Academy of Public Administration, was selected as a “Public Official of the Year” by Governing magazine, and is a past national president of the Public Sector HR Association. The first member of his family to graduate from college, Bob has a B.A. in Public Affairs from George Washington University and an M.S. in Human Resources Management from Cornell University.