Raleigh’s CIO Charts a ‘Crawl, Walk, Run’ Approach to Citywide AI Deployment
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Raleigh, North Carolina, is rapidly emerging as a model for how cities can leverage artificial intelligence (AI) to improve services, streamline operations, and enhance quality of life for residents. The city’s ambitious AI initiative, spearheaded by CIO Mark Wittenburg and his IT team, aims to address challenges ranging from urban growth and climate change to the surprisingly complex task of pothole repair.
Wittenburg, speaking at Gartner’s recent IT Symposium/Xpo event, emphasized the need for innovation to meet rising constituent expectations. “We have to be innovative,” he said, noting that residents now expect the same seamless technology experiences they receive from private companies.
Building on a Foundation of Innovation
Raleigh’s commitment to technological advancement isn’t new. Anchored by the Research Triangle Park – the largest research park in the U.S. and home to tech giants like Cisco, IBM, Dell, and Lenovo – the region has a deeply ingrained culture of innovation. This environment provides a rich talent pool and collaborative opportunities for the city’s IT department. Wittenburg highlighted the importance of leveraging these regional assets, stating that the AI initiative is focused on improving services for Raleigh’s 500,000 residents while drawing on the expertise of local universities – North Carolina State University, Shaw University, and Meredith College.
Partnerships with these institutions are proving fruitful, with Wittenburg noting that collaboration with students is “sparking some amazing ideas and how to solve some real-world challenges that we have.”
From Siloed Workflows to AI-Powered Efficiency
The drive for IT innovation predates the current wave of AI hype. Six years ago, Wittenburg’s team began tackling siloed applications and processes across city departments. “How do we take these siloed workflows, like hiring somebody, and then what are the pieces those workflows touch along the way?” he explained. The goal was to streamline operations by sharing data and workflows, laying the groundwork for future AI integration.
The emergence of generative AI (GenAI) provided a new catalyst for improvement. Wittenburg’s team began experimenting with GenAI internally, prioritizing a cautious approach. “There’s a couple of good examples of where that’s gone bad,” he cautioned, emphasizing the importance of internal testing before public rollout.
This internal focus yielded significant results. By implementing ServiceNow’s AI platform, Raleigh’s IT team has achieved a 95% auto-summarization and approval rate for help tickets, leading to a 66% reduction in ticket resolution times and a quicker clearing of service backlogs.
A ‘Crawl, Walk, Run’ Approach to Public Services
When applying AI to public-facing processes, Wittenburg adopted a phased “crawl, walk, run” methodology. This involved carefully evaluating the potential benefits, risks, and appropriate technologies for each application.
The first public-facing AI project focused on Raleigh’s water system. The city digitized records dating back to the 1700s and built a model using data analytics, AI, and GenAI to analyze the infrastructure and predict potential failures. This approach allowed for the creation of a closed model using Raleigh’s own data, minimizing risk and enabling city employees to validate and refine the AI’s predictions.
Next, the IT team integrated ServiceNow’s AI platform with the city’s public chatbot, adding “agentic pieces” – AI capable of autonomous decision-making. “It was amazing, because now it started to use the knowledge articles, but it also started to dig into those closed tickets to other workflows, and to start to put all that together. It’s just amazing watching it learn things that we didn’t know we were doing,” Wittenburg said.
Simplifying Government and Enhancing Safety
The ultimate goal is to leverage AI to simplify interactions with city government. A prime example is the effort to streamline pothole repair, a process currently complicated by jurisdictional boundaries – city, county, and state roads each have separate reporting procedures. “What if we could get all those AIs and those agents and all these services to hide the complexity of government from you all?” Wittenburg asked.
Another key initiative, “Vision Zero,” utilizes machine learning and partnerships with Nvidia and Esri to analyze traffic intersections and identify potential safety hazards. The team is now incorporating GenAI to solicit suggestions for improvements, such as adding turn signals or adjusting light timing.
Guidance for CIOs Embracing AI
Wittenburg’s advice to fellow CIOs embarking on their AI journey is straightforward: prioritize governance and “guard rails,” establish a solid data foundation, and “don’t let fear hold you back.” He stressed the importance of creating a consistent experience for constituents and reducing the complexity of interacting with local agencies. Ultimately, Raleigh’s experience demonstrates that a thoughtful, phased approach to AI deployment can deliver significant benefits to both residents and city operations.
