Kazakhstan’s Digital Economy: How AI Readiness Shapes Regional Development

The research raises a question that reaches beyond Kazakhstan: what helps a place turn access to technology into something economically useful?

Getting a business online can make payments easier and bring customers closer, but turning that connection into lasting economic value takes more than reliable internet. Workers need useful skills, companies need the confidence to change familiar routines, and regions need resources that help new ideas become everyday practice. Research from Kazakhstan explores how these ingredients shape the relationship between digital progress and local economic performance.

The study, "Digitalization and Regional Economic Development in Kazakhstan: The Moderating Role of AI Readiness," published in Economies, examines digital development across the country's regions. The finding connects stronger economic performance with both digitalization and the capabilities that prepare businesses and institutions for artificial intelligence. The relationship between digitalization and economic performance becomes stronger in regions with better research capacity, specialist skills, innovation, and organizational preparedness.

For a country seeking to diversify an economy with a substantial raw materials sector, that finding carries practical weight. Digital services can open opportunities for businesses and communities, but regions enter this transition with different levels of investment, infrastructure, and expertise. The research raises a question that reaches beyond Kazakhstan: what helps a place turn access to technology into something economically useful?

What the Researchers Measured Across Kazakhstan

The researchers assembled data covering 20 regional units from 2015 to 2024, creating 200 observations that each represented one region in one year. Historical figures were reconstructed to account for administrative boundary changes, including the creation of Abai, Jetisu, and Ulytau regions in 2022. Economic development was measured through inflation-adjusted gross regional product per person, which captures regional economic output rather than household income.

A Digitalization Index combined internet access, broadband connectivity, digital services, e-commerce, cashless payments, and business use of information technology. A separate AI Readiness Index gave equal weight to innovation, research and development, advanced technological skills, and organizations' capacity to adopt sophisticated technologies. Both indices used a 0–100 scale, keeping basic digital access separate from the capabilities needed for more advanced applications.

Using official statistical and administrative sources, the team applied a method called System GMM to account for previous economic performance, regional differences, and the possibility that prosperity itself encourages digital investment. The analysis included investment, education, urbanization, employment, and industrial structure, with 160 observations usable in the main model because it required earlier years' data. A second method, FGLS, used 180 observations to check whether the main patterns appeared under a different approach.

Why AI Readiness Changes the Digital Economy Story

Higher digitalization scores were associated with stronger regional economic performance, and the AI readiness measure showed a positive relationship of its own. The most distinctive finding concerned their combination: the link between digitalization and economic output strengthened as AI readiness increased. This supported the researchers' argument that connectivity and advanced technological capabilities work together in shaping regional development.

A connected company may have the tools to collect information, but employees with suitable expertise and managers prepared to change processes are needed to make that information useful. The paper discusses possible applications such as production monitoring, equipment maintenance forecasting, logistics planning, and more sophisticated digital services. These examples explain how the relationship could work; the study did not measure the economic returns from individual AI projects.

Investment and education were positively associated with regional economic performance, alongside industrial activity, with weaker evidence for employment and urbanization. Previous economic performance remained closely connected to current results, suggesting that established regional advantages tend to persist. Checks using different model settings and different weights for the AI readiness components preserved the main positive relationships.

The Regional Divide Behind National Digital Progress

Digitalization scores ranged from 38.50 to 92.60 across the observations, revealing differences that a national average could hide. AI readiness varied from 24.10 to 88.40, reflecting uneven access to research resources, specialized workers, innovative businesses, and organizational capabilities. These gaps matter because regions with strong foundations may be better positioned to turn digital investment into productive activity.

The paper identifies a risk that investment, technology companies, and skilled workers could become concentrated in the strongest economic centers. Communities with fewer resources could gain internet access without gaining the expertise or business support needed to capture comparable benefits. This is a policy concern drawn from the findings, rather than proof that AI has already widened Kazakhstan's regional inequalities.

For regions at an earlier stage of digital development, the researchers recommend reliable broadband, digital literacy, and support for businesses adopting everyday digital tools. More technologically developed regions may benefit from stronger data infrastructure, computing resources, specialist training, and support for innovative companies. National and regional authorities can use these differences to shape investment around local needs, giving communities outside leading cities opportunities to build their capabilities.

What the Findings Can and Cannot Tell Us

AI readiness in this study describes conditions that could support AI adoption, rather than how many businesses actually use it. Innovation, research spending, engineering expertise, and organizational preparedness can support many technologies, making the index an exploratory measure rather than a uniquely AI-specific score. The findings show relationships in the observed data and do not establish that introducing AI causes regional economic growth.

The relatively small sample of 20 regions over ten years limits the precision of the estimates and the strength of the model checks. Combining several activities into a single index can hide differences between the economic relevance of broadband, online commerce, payments, and other components, and some benefits may take longer to emerge. The authors state that their processed dataset is unavailable for sharing, which limits independent replication of the analysis.

Future research could track actual business adoption of AI, AI investment, specialist employment, and longer periods of economic change. Examining individual digital activities and possible minimum levels of skills or infrastructure could clarify where investment becomes most useful. For policymakers and businesses, the practical message is to pair technology spending with the people, research, and organizational changes that help communities put it to work.