Embracing AI: a necessity for state governments

State governments must harness AI now to tackle pressing challenges, elevate service delivery and redefine citizen engagement.

Leveraging AI technologies is not an option

State governments today face numerous operational and service delivery challenges such as budget constraints, staff shortages, resistance to change, older technology and data protection concerns. While addressing these issues may seem overwhelming, high service expectations and the need for efficiency necessitate the consideration of innovative solutions to deliver value across the different departments.

The rapid evolution of technology has led to significant advancements in automation and AI, enabling complex processes to be automated – helping to expedite citizen services, reducing the impact on vacancies and seamlessly integrating with current IT infrastructure.

By integrating these technologies, state governments can not only address current challenges but also better position themselves to meet evolving and increasing needs of those they serve.

AI technology is evolving at a very fast pace

The AI evolution is happening in months, not years. Artificial intelligence has evolved from simple rule-based systems to sophisticated, adaptive technologies that are transforming public sector operations, with a brief history below:

• Early implementations focused on robotic process automation (RPA) and optical character recognition (OCR) to digitize paperwork and streamline repetitive tasks.
• As machine learning matured, agencies began leveraging predictive analytics and anomaly detection to improve decision-making.
• Tools for reporting and visualization enabled clearer insights from complex datasets, while process mining uncovered inefficiencies in workflows.

Today, generative AI (Gen AI) and agentic AI — capable of autonomous decision-making and task execution — are opening new frontiers in service delivery, constituent engagement and policy development.

“Copilots” in state agencies introduce GenAI directly into the productivity tools already used by government employees. For state and local agencies, this means faster document drafting, automated meeting summaries and intelligent data analysis — all within a secure, compliant environment. Copilots help reduce administrative burden, freeing up staff to focus on higher-value tasks like constituent services and strategic planning. Its integration with existing infrastructure ensures a smoother adoption curve and maximizes return on existing technology investments.

Right fit: matching AI to the right problems and patterns to add value

AI is most effective when applied to problems with clear patterns, repetitive tasks or large volumes of data, and it’s best paired with areas where it can augment human decision-making. However, it may not be suitable for highly nuanced, low volume or ethically sensitive decisions where human judgment is critical. Therefore, to justify investment, agencies should measure AI’s impact through tangible metrics like reduced processing time, cost savings, improved service delivery, as well as where new-found time is spent. Establishing a baseline and tracking improvements helps demonstrate ROI and guide future scaling.

Functional patterns pair well with AI (e.g., document summarization, virtual agents for communication and data pipelines with agile scenario modeling). For instance, AI excels in use cases such as document summarization, virtual agents for citizen services and intelligent routing of requests — tasks that benefit from speed, consistency and scalability. These patterns are repeatable and data-rich, making them ideal for automation.

However, equally important is the integration of high-quality, well-governed data; oftentimes the foundation of effective AI. Lacking data quality can produce biased or inaccurate results. Seamless integration across systems ensures AI tools have access to the right data at the right time.

The truth is, not every problem requires AI — sometimes a rule-based system or process redesign is more efficient and cost-effective. Staying grounded in business needs and outcomes helps avoid overengineering and ensures technology serves a clear purpose.

Challenges in deploying AI technologies – be prepared for challenges and roadblocks early on

AI implementation has been made to look easy, and software vendors might say that it is, but those who have done an initial deployment quickly experience the complexity and challenges that initial projects face. Common obstacles include identifying stakeholders (IT, business and end users), obtaining approvals for AI tools, selecting the right business domain and use case, integrating with existing tools, choosing appropriate AI tools with minimal customization, securing data, and training employees to maximize the capability while maintaining data security.

Taking the time to establish a strategic and structured approach can help anticipate these roadblocks and identifying the right stakeholders up front will help facilitate the project. Slow and deliberate up-front success milestones enable you to quickly scale with confidence when ready.

Start small but get the big things right

When rolling out a technology as powerful as AI, the key to a successful implementation is starting small and being deliberate. Starting small enables you to control how the solution is designed, how it works within your technology and environment, how your employees engage, how data and access are enabled, and helps prove out the value that can be achieved. This approach allows an organization to engage the proper stakeholders and reflect on the capabilities – what is impactful, how much time it takes to get the needed AI capabilities in place, how data is used and how end users engage. This then allows an organization to modify the approach to meet their needs prior to scaling and helps to drive alignment on what the outcome and potential risks will be.

Additionally, having a passionate technology advocate can make a huge difference when trying to drive a new technology like AI. Their enthusiasm and expertise can overcome resistance to change, inspire innovation and empower staff. This leadership is crucial for implementing AI solutions that deliver tangible value to the state.