How Can Smaller Cities Join the Growing AI Economy?

As artificial intelligence gains ground, countries are setting national strategies to promote the technology’s adoption. Local governments may not have those same resources, but they can make AI more accessible.

by / December 2018

Artificial intelligence (AI) is poised to make a significant impact on the global economy, adding $15.7 trillion to the GDP by 2030. In pursuit of these economic benefits, many countries have developed national strategies to promote the adoption of AI within their borders, such as China’s ambitious plan to become the global leader in AI. But what can state and local governments — especially those outside of the country’s main tech hubs — do to ensure they are not left behind in the AI economy?

The major challenges these regions face is ensuring that AI is accessible, available and affordable for local businesses, especially small and medium-sized businesses that may not have the resources of their larger counterparts. To address these challenges, state and local governments should develop a three-fold strategy.

First, help ensure AI is accessible to local firms. This requires educating the business community about the benefits of AI, such as through organizing regular networking events for those interested in the topic or sponsoring an “AI Awareness Month” to help businesses better understand AI. Those that do not understand the potential value of AI are unlikely to pursue it, so local businesses need to learn about use cases for AI in their specific industries. For example, many businesses can use AI to streamline processes, such as improving customer service interactions by automating responses to certain types of inquiries with chatbots.

Second, government should support the development of local training programs for AI skills. Not all cities will be able to recruit the top graduates from the best computer science programs in the country, so instead they should focus on developing their local talent. State and local governments can partner with local colleges and universities to develop AI certificate or apprenticeship programs targeted at local business needs. The goal should be to train high-potential workers who may already have some technical background and industry experience but lack the necessary data science skills to take on more advanced AI projects.

In particular, state and local governments should focus on training workers for the long tail of AI business adoption. These businesses do not need to be focused on developing the latest cutting-edge AI tools and methods, but instead should focus on effectively using existing AI technologies. For example, there are increasing numbers of cloud providers who are offering AI as a service that make it possible for programmers without deep knowledge of AI to integrate this technology into existing systems.

Third, consider jump-starting local AI adoption. Part of this strategy should involve making AI adoption less risky by having government be an early adopter. An important part of early adoption will involve not only using AI in custom implementations, but also becoming early adopters of commercial off-the-shelf AI products. For example, many companies are using AI to improve productivity by using virtual assistants to schedule meetings or using algorithms to better match job seekers with job openings and reduce unconscious bias in hiring. By proving the value of the technology, and sharing best practices and lessons learned, the public sector can pave the way for adoption by local small and medium-sized businesses.

In addition, not all businesses are going to be hiring full-time AI experts. To encourage businesses to pursue third-party AI services, states should consider creating an AI incentive tax credit to provide businesses a partial tax credit to incentivize them to become early adopters of AI while also supporting the growth of AI service providers.

While state and local governments cannot replace the need for a national strategy for AI, they can take important steps to ensure that the businesses in their jurisdictions are full beneficiaries of the transition to an AI economy. 

Daniel Castro Contributing Writer

Daniel Castro is the vice president of the Information Technology and Innovation Foundation (ITIF) and director of the Center for Data Innovation. Before joining ITIF, he worked at the Government Accountability Office where he audited IT security and management controls.