1. Introduction

With its potential to automate routine jobs, to optimise supply chains and to enhance interactions with customers, AI could fundamentally alter the structure of the world economy. So far, most of the focus on the potential impact of AI has been on large cities and global firms but smaller cities and rural economies can benefit too, especially as they try to address many of the key local economic challenges they face – such as labour shortages, constraints on the supply of land and labour, and lack of access to advanced technologies. AI could help to automate certain jobs, to optimise supply chains and enhance interactions with customers, and in the process help to boost productivity and allow many small and medium-sized enterprises (SMEs) to compete more effectively in the larger economy. In rural areas, this can be especially powerful in sectors such as agriculture. For example, AI has helped to transform farming through the introduction of precision farming systems that manage crops in a way that is more cost-effective because it uses more real-time, data-driven decisions. The increased use of AI in agriculture could help to boost productivity as well as make it more sustainable by reducing the overuse of fertilisers and water. Linked to this, AI could create new and different jobs in local communities, especially if new spin-off industries emerge that require new sets of skills, such as the need for data analysts, drone operators and AI systems managers. All of these developments should require a ‘workforce development’ approach in local communities, where local government and educational institutions play an important role in training local workers for the AI-fuelled economy. But what are the challenges in using AI in local economies, especially if local areas lack the digital infrastructure to do so? Given some of the challenges, local government could play a key role in powering the market for AI-fuelled growth by investing in both physical and digital infrastructure, public-private partnerships and business-support policies [1]. This paper considers the role of AI in local business innovation and in the transformation of the workforce. It also considers the important role that local government plays in supporting both.

2. AI in Local Business Innovation

For small and medium-sized enterprises (SMEs) and local businesses, AI technology is on the rise as more of the world becomes digitalised. Businesses in rural areas may find it more difficult to adopt new technologies, although there are a variety of reasons for that, including (but not limited to) lack of talent in small towns. But AI could also present opportunities for scalable, cost-effective solutions for small and local businesses, helping them become more refined and effective. To illustrate this, cloud-based solutions with machine learning and algorithms can help businesses – including small ones – better manage their operations, and get better at engaging with customers and expanding their market. Agriculture is a leading sector for AI innovation, and many farmers in rural areas are using AI-powered precision farming technologies that can help them monitor the health of crops, allocate resources and improve yields [2]. For instance, AI systems – with the help of sensor, drone and weather-data predictions – can help farmers make real-time, data-informed decisions about their farms that can make them more efficient, but also more sustainable, by saving water, pesticides and fertilisers. Similarly, in small-city businesses, retailers are also benefitting from using AI to better manage inventories and predict customer tastes, so they can better keep up in broader markets and reduce the costs of operational inefficiencies. AI is changing the way local and small businesses operate, making them more fluid, nimble and competitive [3].

2.1. Impact on Productivity

At the local level, they can provide a substantial boost to productivity. Because AI-powered systems tend to run much faster than humans, they can potentially enhance production and service delivery. This could be especially valuable for SMEs that might lack sufficient human resources to attend to daily business activities. For example, chatbots may be programmed to provide customer service on a 24-7 basis, thus freeing humans from having to respond to simple queries, and allocating more time to activities with higher strategic or creative value. In the case of manufacturing firms, AI-powered robots may run production lines, reduce downtime and decrease human errors [4].

Additionally, for local enterprises operating in rural areas, AI can aleviate labour market challenges including the lack of skilled workforce and compensate for perceived worker shortages, by allowing local enterprises to replace manual and repetitive tasks with machines and robots, which in turn allow such firms to produce more goods or services. This results in increasing output which consequently increases revenue. The productivity gains allow business to re-invest these gains into operations, which in turn facilitates additional growth, which then allow such firms to grow and operate in multiple markets. The automation gains led by AI are not only limited to traditional industry sectors, but innovation led by AI, robotics, hardware and software, and machine learning are now allowing businesses to expand into new growing industries, which will allow businesses to diversify their revenue stream and hedge their costs [5]. Table 1 below illustrates both productivity and revenue growth in various sectors to provide an insight on how productivity gains are actually happening in local firms.

Table 1: AI Integration Impact on Productivity

2.2. Enhancing Customer Engagement

One of the most important audiences for AI are small businesses – the local businesses that rely on their local customers for most of their revenue. AI systems can help anticipate what their customers need and deliver the unique services that they crave. One way that AI can help is simply to provide insight into what types of customers and products are most profitable. AI-driven CRM systems can collect and analyse your customers’ purchasing data, enabling local businesses to focus on the ones most profitable for them. Another way that AI can help small businesses is to use the data it collects about customers to better manage their relationships and sales leads. It can predict which customers are most likely to churn, and it can customise messaging in a way that makes it more likely to convert. High levels of personalisation are crucial for customer loyalty [6]. If the system can learn about your customers’ preferences and then offer them recommendations or deals that cater to those preferences, then it can make the difference between your business acquiring or retaining the customer. It’s doubly important for small local businesses who can’t survive without the patronage of their local customers.

2.3. Supply Chain Optimization

Importantly, this is being achieved through AI optimisation of supply chains. Supply chain management is a crucial component of business activity, and for those operating in geographically distant clusters, AI can play a vital role in maximising supply chain efficiency through prediction of demand, inventory management, optimisation of distribution routes, and other measures. This is especially important for the smooth operation of rural businesses, which often face high transportation costs due to remote locations and the constraints that infrastructure bottlenecks impose. With the help of AI, these costs can be reduced, delivery times can be improved and the overall operation of the business optimised to boost its competitiveness. In supply chains, where changes in demand or other factors can lead to severe consequences for those involved, AI solutions can help to mitigate such outcomes. An example of this comes from AI-based systems that make optimisation decisions based on real-time traffic data; this can happen faster and more efficiently than can most human workers [7]. If there’s a road traffic incident, the AI-based system can instantaneously re-route the delivery. Similarly, if there’s a change in consumer demand, the system can make decisions on rescheduling production times. Without this ability, rural-based businesses face the risk of losing their competitiveness in a globalised economy that operates at great speed. In addition to its contribution to the operation of business, the use of AI in supply chains has the potential to reduce waste, improve sustainability and enhance the environmental footprint of a business, which is an increasing concern for those in all sectoral industries [8].

3. AI’s Impact on Labor Markets

3.1. Job Creation and Workforce Transformation

While the uptake of AI may be leading to job-displacement and job-skill-displacement, it also offers an opportunity for job-creation in small cities and rural areas. When businesses embrace AI, there are increasing opportunities for workers in developing, managing and operating AI systems. For example, the uptake of AI in agriculture creates opportunities for new jobs: in analysing and making sense of data about crops; in piloting and operating drones and farm robots; and in running the precision farming technologies that we will use to grow our food. Many of these are roles and careers that require a different skill set than that of a ‘farmer’. This helps to motivate a change in the nature of the rural workforce – one that has already started to emerge. For example, state and county governments and community colleges in small cities and rural areas are developing training programmes and courses to help workers develop the skills needed for these new roles and careers in the AI economy. These focus on digital literacy, coding and data science, and help to build the core skills needed for jobs in the new digital economy. These new training programmes and courses are critical for the workforce in small cities and rural areas, and will help prepare workers to compete in a fast changing economic landscape. As we see in a below table, the uptake of AI can lead not only to job-displacement but it can be transformative for the nature of work and the type of jobs we ask our workers to do [9]. AIs could assist workers in shifting from jobs that only ask them to perform repetitive tasks to jobs where they are engaged in higher skills, involving creativity, innovation and strategy. For example, completing data records with minimal variations in input, but requiring some critical thinking, would be the type of jobs that could be assisted by AIs, allowing workers to engage in higher-skilled tasks with creativity and innovation. The data displayed in the below table provides an overview of the new jobs roles, skills, and workforce transformation methods emerging due to the uptake of AI. These were identified in the above studies and indicate significant job growth in these areas.

Table 2: AI Impact on Job Creation and Workforce Transformation

3.2. Reskilling and Upskilling Programs

Second, local economies must develop reskilling and upskilling opportunities that offset the inevitable job displacement that will come with new AI technologies. As new AI technologies disrupt industries faster than ever before, workers will need to learn new skills to remain competitive in the labour market. In small cities and rural areas, where residents might not have ready access to more advanced forms of education and training, local governments and businesses are working together to provide online courses and vocational training programmes. Some of these programmes focus on developing technical skills, such as programming and data analysis. Many more focus on the ‘soft skills’ that workers need to succeed in a tech-based workplace, like critical thinking, problem solving and collaboration. These investments in reskilling and upskilling shouldn’t be viewed as a pure defensive strategy to preserve existing jobs – rather, local policymakers should view these investments as equally about preparing workers for the jobs of the future [10]. The continued development of AI technologies will also spur further job creation. Over time, new and old industries will create high-quality jobs for workers with skills in areas such as AI system maintenance, algorithm development and data-driven decisionmaking. Local economies that make a pre-emptive investment in reskilling their workforce will be best positioned to compete in the global marketplace and to take advantage of the economic opportunities that AI promises to create.

3.3. The Role of Local Governments

The main way local government can foster AI technologies in the labour market is to facilitate the expansion of AI-embedded industries, through public-private partnership. Government can invest in AI research and provide funding for those companies wishing to bring AI into their core operations, as well as formulate and implement policies (eg, tax credit) to incentivise the expansion of AI-embedded industries. Local governments can play an even more important role in facilitating the implementation of AI technologies in rural areas. The poorer rural localities lack the resources to foster the adoption of AI technologies in the labour market. Government intervention can help them to close the gap in the resources through investment in AI-related infrastructure. Moreover, government can procure AI-related training from educational institutions and provide them in rural areas. These policies will not only strengthen the local labour market but also ensure the local business has access to the skilled labour they need for implementing AI technologies. The bar chart in Figure 1 below shows the percentage of local government initiatives in facilitating the adoption of AI technologies. The main areas in which government can help are investment in infrastructure, funding for AI technology, and partnership with educational institutions (shown in the recent policy studies).

Figure 1: Local Government Focus Areas for AI Adoption Support

3.4. Addressing the Digital Divide

A half-step down from underestimating rural workers is the issue of the digital divide – the gap between those who have access to digital technologies and those who do not. AI is an inherently digital technology that requires a robust digital infrastructure including both high-speed internet and access to data – neither of which are widely available in the countryside. The success of any private-sector response to AI depends on the government providing the basic infrastructure. Local governments must partner with private enterprise to ensure that the digital divide does not prevent AI from benefitting all sectors of the economy. Access to broadband and other digital infrastructure is the essential first step in ensuring that the rural economy can participate in the AI-driven economy. But it isn’t enough to simply provide access to more high-speed internet.

4. Conclusion

Unlocking the potential of AI to drive business innovation and workforce transformation, especially in rural areas and small cities, can add significant value to local economies. Robust, scalable AI technologies can help businesses increase productivity and engagement with customers, while improving supply chain efficiencies, thereby driving business growth and providing sustainable economic growth to local economies. Simultaneously, the new jobs resulting from AI can allow rural workers to move into higher-value jobs that require advanced technical skills. Creating a healthy ecosystem for AI to be adopted – including investment in digital infrastructure, reskilling, and government policies that promote innovation – is key. Local governments have a crucial role to play in addressing the digital divide, ensuring that businesses and workers can benefit from the arrival of these AI technologies. Ultimately, whether AI can help provide sustainable economic growth is a function of how local economies can adapt and make use of the transformative power of AI.