For city governments around the world, the primary question about technology is no longer if they should be thinking about using generative AI, but how to start using it.
It is a remarkable shift, which I and others in Microsoft for government have gauged over the past year as we’ve worked to help city governments solve their most important challenges through technology.
At the SXSW 2024 conference, the Esri Infrastructure Management & GIS Conference, and in my recent meetings with city leaders from Canada, Finland, and the Netherlands, generative AI has been at the center of most conversations. This excitement is notable because cities are traditionally cautious about technology adoption for important reasons such as risk, privacy, security, and governance, and many are still working through their cloud migration journeys.
The potential benefits of generative AI to improve operations and service delivery are too compelling for many cities to ignore. To cite just one example, the City of Kelowna in Canada launched an early AI initiative and is using cognitive search and conversational AI to deliver a 24-hour helpline for its 150,000 residents. Project leaders report that generative AI also enables them to automate and streamline internal processes around data entry and analysis, refactor legacy databases and code, and create new apps in minutes.
This type of innovation has prompted other cities to explore AI innovation, beginning with creating an effective and actionable plan.
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Success factors for AI adoption in city governments
Every city is unique, with its own ambitions for the use of generative AI and its own set of requirements and technology considerations. In our work with cities, we have identified a set of success factors that are common across cities investing time and money in generative AI and are enjoying early success.
1. Empower the workforce with effective upskilling
Realizing the value of AI starts with the workforce. According to research conducted as part of Microsoft’s Public Sector Insights on Skilling, the lack of skilled workers is often the number one barrier to AI implementation among organizations worldwide.
The imperative to upskill the workforce is particularly important for cities, whose early use cases usually focus on employee productivity and the internal processes they manage. Well-trained and confident workers also help ensure the success of public-facing initiatives. Executive support is key. Workers are empowered when leadership gives them the direction and license to responsibly use AI tools within the context of their day-to-day work.
To answer the skilling challenge, cities should invest in learning programs, building public-private upskilling partnerships, and giving people adequate time to gain skills and confidence. An ongoing learning experience platform, such as the one developed by Bank of Canada, can promote a culture of learning. Microsoft offers effective resources and strategies, including the Public Sector Center for Digital Skills, which provides specialized insights, guidance, and content, and Microsoft Learn, which offers customized training options.
2. Build an AI-ready data strategy
AI is only as good as the data that is made available to it. In city systems, data is often siloed or locked in spreadsheets or other static locations. A modern data strategy is one that integrates such diverse data sources, ensures data quality, establishes rules and processes for data access and management, and keeps data and systems secure.
An excellent example of how a complete data strategy can deliver ongoing AI benefits is the Smart Qatar (TASMU) Program built by the State of Qatar. Essentially a service platform built on a common data model across multiple domains, TASMU will empower a broad array of AI applications that are expected to help contribute 2% to the nation’s gross domestic product (GDP).
This sort of comprehensive data strategy is an important long-term goal, but cities should not wait to begin innovation on AI. Many cities are taking an incremental approach, leveraging the quality data they have in hand, with their existing cloud foundations and data governance standards to experiment with new AI use cases. A careful step-by-step approach will guide your data strategy.
3. Establish frameworks for governance, compliance, and sovereignty
Some city governments have been reluctant to use AI due to concerns about security, privacy, and compliance requirements. To address these concerns, cities should establish transparent frameworks for AI governance and assurance. The goal is to identify risks and goals associated with both externally facing and internally focused use cases and codify courses of action to ensure success.
Ensuring the residency of data within strict geographic borders is a key requirement for many cities. This calls for a solution that can ensure the required level of control of sensitive data while still providing a hyperscale cloud environment for a huge number of applications.
Microsoft offers guidance for cities to establish AI governance and enhance trust and privacy in AI innovation. For cities with strict data residency concerns, we also offer Microsoft Cloud for Sovereignty, which offers tailored cloud services to help build cloud-based workloads in compliance with specific security, policy, and regulatory requirements.
Take the first steps in building an AI-empowered city
For city leaders who want to advance their AI journeys, our experts and industry advisors can work with you to identify potential use cases for early innovation based on your specific goals, requirements, and environmental conditions.
To learn more about how Microsoft can empower cities and government organizations with technology to help solve society’s biggest challenges, visit the Microsoft for government website, read our Microsoft for Government e-book, or get in touch with your Microsoft representative or technology partner.
