Artificial intelligence (AI) is everywhere, sparking both optimism about its potential and anxiety about its risks. As someone who has spent decades working with economic models and public policy, I understand both reactions. In fact, if AI makes you feel somewhere between excited and uneasy, you’re exactly where you need to be. This is one of the main points of “Bringing AI to Main Street ” to help local leaders, policy makers, and community advocates cut through the hype and the fear, and focus on what really matters: the impact AI can have on our communities, how we can learn as we go, and what it takes to be truly ready.

Three words: impact, learning, and readiness, capture the essential approach for any community seeking to bring AI to Main Street. These pillars guide practical, equitable, and sustainable adoption, ensuring that local leaders focus on what matters most as they navigate the opportunities and challenges of AI.

Impact

AI offers real benefits, but the path to adoption is not always smooth. Communities should expect technical, cultural, and educational challenges along the way. At the macroeconomic level, AI’s potential is staggering. We have enough data and macroeconomic models to run econometric forecasts on what AI will do for the economy as a whole. Some models predict that productivity growth could increase by 1.5 percentage points per year for the foreseeable future. It means we all go on more vacations and work less within a generation. This is how impressive this could be.

But when it comes to local economies, the data is not yet there. That is why the report relies on real-world examples of AI adoption across geographies and sectors, from Chicago to Honolulu, and from recycling to insurance, NGOs to academia. The takeaway? Adoption of AI has not been painless. People do not really know how to manage computers, let alone AI. Yet, despite these challenges, the impact can be positive, very positive. Processing times, cost savings, customer satisfaction and countless other aspects of business can improve. Whoever and whatever AI touches has the potential to become more efficient.

Learning

If AI is so good, how should local authorities foster and accelerate its adoption? The report proposes an iterative framework, using short, testable cycles focusing on the end user. Technology companies may be able to design and execute super-expensive, long-term projects. But for small-scale, user-oriented applications, the speed at which AI itself is evolving could make them obsolete within a month. Instead, go short and testable. Continue learning from what you are doing.

This approach is only possible through robust partnerships. As a local leader, you learn from others as much as you learn from yourself. Advocates, service suppliers, academics, technicians, and users should all be part of the conversation.

Readiness

Even with strong partnerships and a learning mindset, communities need foundational structures for AI. These include things like broadband infrastructure, workforce digital literacy, and sound data governance. Legal and ethical challenges abound, especially around data use and privacy. To help leaders assess their preparedness, the report offers a checklist—26 questions across six categories: infrastructure, workforce, sustainability, governance, and more. Local leaders can use the results to plan mobilization and develop priorities. And even if you do not see an AI future in your community, you would be well advised to run through the 26 questions—they amount to a self-evaluation of your development path.

Conclusion

The bottom line is that AI will make you - will make all of us! - more efficient. No question about it. If you are going for it, do not go for large projects - go for short and testable. Do not go it alone, and start by taking stock of your community’s assets. You can embrace AI’s potential, but do so thoughtfully. Focus on impact, foster continuous learning, and rigorously assess readiness. Use the checklist, build partnerships, and keep projects nimble. Bringing AI to Main Street is not just about technology, it is about building resilient, adaptive communities ready for the future.

Download Bringing AI to Main Street: Maximizing Artificial Intelligence’s Positive Impact on Municipal Economies. This report was developed with the generous support of Google.

Marcelo Giugale is a Fellow of the National Academy of Public Administration, an Adjunct Professor at Georgetown University, and a former Director of the World Bank. His books, academic articles, and media engagements have ranged widely—from economic development to fiscal policy, and from public debt management to sustainable finance. He holds a PhD and a MSc in Economics from The London School of Economics, and a Suma-Cum-Laude BA in Economics from Universidad Católica Argentina.