Analysis Region: 31 cities and counties in Gyeonggi-do
Key Regions: Southern Gyeonggi High-tech Industrial Zone, Northern Gyeonggi, Eastern Rural Zone, AI Innovation Cluster Hubs
Agenda: Regional disparities in AI access, industry, education, and administrative capabilities
Golden Time Type: Opportunity + Structural Risk
Reference Date: August 28, 2026
Version: Regional AX Golden Time Intelligence v3.1
While it is statistically possible to view Gyeonggi Province as a single AI economic zone, it is insufficient in reality. AI and software companies and research personnel are concentrated around Pangyo and Seongnam, while the southern region, including Suwon, Yongin, Hwaseong, and Pyeongtaek, is densely populated with semiconductor and high-tech manufacturing industries. On the other hand, the northern and parts of the eastern regions differ from the very prerequisites for applying AI to actual industry and daily life, such as industrial infrastructure, research institutions, manpower, transportation, healthcare, and education.
This gap is not merely an impression. In a survey of 4,700 Gyeonggi residents released by the Gyeonggi Research Institute on August 27, 2026 , 46.0% of respondents answered that the gap between regions within Gyeonggi Province would widen due to the spread of AI . Furthermore, 77.5% were unaware of the very existence of public facilities or programs for AI experience and learning in their local areas. Directly pointing out the differences in digital infrastructure and industrial structure among Gyeonggi's six major regions, the research team analyzed that it is necessary to differentially apply digital infrastructure expansion and vocational retraining to the northern Gyeongwon and Northeast regions, while providing more advanced AI services to the southern Southeast, Gyeongbu, and West Coast regions. ( Gyeonggi News Portal )
Gyeonggi Province is also aware of the issue. It has established six AI innovation clusters connecting Pangyo, Seongnam General Industrial Complex, Bucheon, Siheung, Hanam, and Uijeongbu by 2026, and is pursuing a plan to educate approximately 150,000 people through AI and Digital Learning Centers. The policy direction is confirmed to expand the AI concentration centered in Pangyo to other regions and guarantee residents' access to AI. ( Gyeonggi News Portal )
However, there is still a lack of publicly available integrated statistics that allow for the comparison of the number of AI companies, AI professionals, corporate AX adoption rates, AI education participation rates, public AI service usage rates, AI-related investment amounts, and data utilization across 31 cities and counties using the same standards. This is not merely a lack of statistics, but a policy-related data gap. To narrow this gap, we must first be able to measure which cities and counties are lagging behind in which fields.
Therefore, Gyeonggi-do's AI Golden Time does not involve distributing the same AI projects to all cities and counties. The core idea is to measure AI Readiness differently across 31 cities and counties based on their industry, population, education, aging, and corporate structure, and to design regional industrial AX differently while ensuring equal minimum access rights .
Gyeonggi Province is close to the scale of a nation in terms of population alone. Based on existing official data, the population of Gyeonggi Province as of June 2024 was approximately 14.1 million, accounting for 26.7% of the national total. Of this, the South accounted for about 10.42 million and the North for about 3.63 million, representing 74.2% and 25.8%, respectively. ( Northern Gyeonggi Administrative Integration Committee )
However, treating a population of 14 million as a single average obscures the internal structure of Gyeonggi Province. While Seongnam, Suwon, Yongin, Hwaseong, and Pyeongtaek have an industrial structure combined with large corporations, R&D, semiconductors, ICT, and manufacturing, some cities and counties in the north and northeast have relatively low densities of manufacturing and high-tech industrial bases and research institutions, and have been affected by military, environmental, and metropolitan area regulations.
Although this data is historical and should be used only as a Historical Official Baseline , analysis showed that as of 2019, the GRDP of Northern Gyeonggi was approximately 78 trillion won, accounting for only about 17% of the province's total; furthermore, at that time, 89.2% of the 12,806 research institutes in Gyeonggi Province were located in Southern Gyeonggi . The proportion of manufacturing businesses in the north was also at the 13.74% level. While these figures cannot be considered identical to current numbers, they are significant as a structural baseline indicating that a gap in innovation infrastructure between the north and south has accumulated over a long period. ( Gyeonggi News Portal )
The AI gap arises on top of these existing disparities in industry, research, income, and education. It is difficult to create an AI industry independently in regions where there are no existing AI companies. Conversely, in regions where manufacturing firms, universities, hospitals, research institutes, and startups are already concentrated, the pace of transition is likely to accelerate as AI is absorbed into existing industries.
Therefore, the AI gap in Gyeonggi- do should be analyzed as the difference in existing regional capabilities × AI accessibility × utilization ability, rather than the possession of AI technology .
A key shift in Gyeonggi Province's AI policy is the expansion from a single hub in Pangyo to a multi-hub network. By 2026, Gyeonggi Province has established bases in Bucheon, Siheung, Hanam, and Uijeongbu with Pangyo as the central hub, creating a structure to operate a total of six AI innovation clusters, including the Physical AI Lab in the Seongnam General Industrial Complex. ( Gyeonggi News Portal )
Spatially, this is a significant change. In particular, the inclusion of Uijeongbu in the AI Innovation Cluster signifies an intention to expand AI policies centered on advanced industries in the southern region to the north. However, one must distinguish between the fact that the number of hubs has increased and the judgment that the AI gap has narrowed.
Even if AI cluster buildings or testbeds exist, spatial diffusion is limited if companies in the region do not actually adopt AI, if skilled personnel do not settle in, or if the utilization of AI by local residents and small business owners is low.
The Seongnam Physical AI Lab is a prime example. The nation's first physical AI demonstration facility opened in late 2025, and initiatives such as attracting six companies and providing manufacturing process demonstration equipment are underway. Gyeonggi Province has set targets for the next three years, aiming for 100 billion won in revenue for resident companies, 150 new jobs, and 50 technology developments. However, these figures are project goals and not current achievements. ( Gyeonggi News Portal )
Therefore, when comparing AI policies of 31 cities and counties, one must distinguish between center establishment → number of trainees → supported companies → actual AX adoption → changes in productivity, income, and services.
AI has the potential to widen regional disparities more rapidly than the internet or smartphones. This is because, while the internet was characterized by the ability to access the same information after connecting, the productivity improvement effects of AI can vary depending on the user's data, job function, industry, and education level.
In particular, the existing industrial structure of a region becomes more important as we shift from generative AI to physical AI. Regions with many manufacturing companies and factories can increase productivity by combining robots, sensors, and data with AI, whereas regions with weak industrial bases may have a smaller market to apply the same technology to.
The Gyeonggi Research Institute's 2026 study on Physical AI in Manufacturing also highly evaluates the potential of Gyeonggi's manufacturing sector while identifying the "AX gap" between large corporations and SMEs as a key risk. The analysis suggests that initial costs, ROI uncertainty, and a shortage of skilled personnel are hindering the AI transition of small and medium-sized manufacturing companies. ( Gyeonggi Research Institute )
If this logic is extended to space, differences in AX speed may occur between areas densely populated with large corporations and high-tech industries and areas centered on small and medium-sized enterprises and lifestyle industries, and between areas densely populated with research institutions and areas with weak research infrastructure.
Therefore, the regional gap in the AI era is not about whether one possesses AI, but about the ability to transform AI into productivity and life services .
Gyeonggi Province announced its nine AI strategies and 52 major projects for 2025, presenting a direction to connect the Pangyo-centered AI Techno Valley with the core industries of 31 cities and counties. The initiatives also included challenges to solve local social problems using AI and collaborations with global AI companies. ( Gyeonggi News Portal )
In 2026, spatial diffusion policies became more concrete. An operating system for six clusters connecting Pangyo, Bucheon, Siheung, Hanam, Uijeongbu, and Seongnam was established, and a network promoting joint projects, technology development, internships, and open innovation between hubs was launched. ( Gyeonggi-do News Portal )
In terms of daily life, the AI and Digital Learning Centers have been expanded. Gyeonggi Province plans to provide education by 2026 to approximately 150,000 people —including not only digitally vulnerable groups but also youth, middle-aged adults, and small business owners—covering everything from generative AI and data understanding to digital ethics, all accessible via smartphones and kiosks. Approximately 250 operational personnel have also been recruited. ( Gyeonggi News Portal )
The policy direction is expanding to include industrial AI, lifestyle AI, and education AI. However, since educational opportunities, participation rates, and corporate AX support performance for each of the 31 cities and counties are not disclosed as identical statistics, it is still difficult to determine whether the overall scale of the province's projects has actually led to a reduction in regional disparities.
The regional disparity in AI is not a problem unique to Gyeonggi Province. Recent policy research viewing AI as a general-purpose technology is increasingly emphasizing that factors such as data governance, public sector utilization capabilities, corporate absorption capacity, and labor market transition support create differences in competitiveness, rather than the possession of the technology itself.
The Gyeonggi Research Institute also assessed in its 2026 AI policy study that Gyeonggi Province's core bottleneck lies in inconsistencies among rules, data governance, organizational capabilities, finance, and transition support systems, rather than the models or technologies themselves . In particular, it proposed the need for a public AI infrastructure accessible to all 31 cities and counties, as well as data sharing at the level of the manufacturing supply chain. ( Gyeonggi Research Institute )
In this respect, Gyeonggi Province faces conditions that are both advantageous and more challenging than those of other metropolitan local governments. While leading-edge AI demonstrations are possible due to the large absolute scale of its industries, enterprises, universities, and talent, it is difficult to apply a single policy to the entire region because the size and industrial structures of its 31 cities and counties vary significantly.
Ultimately, Gyeonggi Province's competitor is not a single specific metropolitan government, but the internal gap itself . Even if the most advanced city enters the global AI competition, if the transition in the remaining regions is delayed, the overall AX productivity of Gyeonggi Province will be limited.
According to existing official data, the southern region accounted for approximately 74% of Gyeonggi Province's population, while the share of Northern Gyeonggi's GRDP was historically around 17%. Although direct productivity comparisons are not possible due to differing base years, it is possible to confirm a long-term structure in which the spatial concentration of economic and innovation resources is greater than that of population distribution . ( Northern Gyeonggi Administrative Integration Committee )
Connecting AI infrastructure here changes the nature of the gap. Among the six AI innovation clusters, Seongnam, Pangyo, Siheung, and Hanam are connected to industrial zones in the south or adjacent to Seoul, while Uijeongbu is the representative hub of the north. Although the expansion of clusters to the north is positive, AI industrial hubs remain selectively distributed when compared to all 31 cities and counties. ( Gyeonggi-do News Portal )
It is also necessary to incorporate data on residents' perceptions. In a 2026 survey by the Gyeonggi Research Institute, 46.0% expressed concern that AI could widen regional disparities, while 77.5% were unaware of the existence of AI experience and learning facilities or programs in their residential areas. This demonstrates that implemented policies do not align with tangible accessibility. ( Gyeonggi News Portal )
Connecting the industrial gap, AI accessibility, and civic perception reveals a structure.
The AI gap is not a new gap, but rather a problem that has the potential to accelerate the gap as AI is added on top of existing disparities in industry, education, and infrastructure.
The first is the AI industry cluster gap . While areas like Pangyo and Seongnam have a high concentration of AI companies, startups, and skilled professionals, not all cities and counties have the same conditions.
The second is the corporate AX GAP . While large corporations and high-tech manufacturing firms can rapidly adopt AI through their own investments, small and medium-sized enterprises (SMEs) and micro-enterprises may experience slower adoption due to a lack of cost, data, and personnel. This gap is explicitly confirmed in the Gyeonggi Research Institute's research on manufacturing AI. ( Gyeonggi Research Institute )
The third issue is the AI access gap for provincial residents . Expanding the education program to a scale of 150,000 people is a different matter from ensuring the same level of accessibility in the actual 31 cities and counties. In particular, physical and cognitive accessibility may be low for the elderly, rural areas, and transportation-vulnerable regions, even if educational facilities exist.
The fourth is the AI capability gap in public administration . If the organizational scale, budget, specialized personnel, and data management capabilities of the 31 cities and counties differ, the level of utilization varies even when the same AI service is introduced.
The fifth is the measurement gap . Based solely on currently available data, it is difficult to compare the 31 cities and counties using the same AI Readiness Index. This is also the gap that needs to be resolved first.
The foundation determining the regional gap in AI is not merely a communication network. Even with a high-speed internet connection, it is difficult to transition to AX if corporate data is not organized or there is a lack of skilled personnel to utilize it.
In industrial areas, manufacturing data, AI demonstration equipment, GPUs and computing, skilled personnel, and collaboration between universities and companies are crucial. In residential areas, accessibility for residents to actually use AI education, welfare, transportation, and medical services is key.
In public administration, data standardization across 31 cities and counties is crucial. The Gyeonggi Institute’s AI research on pedestrian safety also suggested that standardizing and linking crime prevention CCTV, traffic CCTV, and sensor data according to common standards across the 31 cities and counties is necessary to shift from reactive response to preventive administration. ( Gyeonggi Institute )
Therefore, the AI gap between regions is difficult to measure solely by computer penetration rates. At a minimum, Access, Skill, Data, Business Adoption, Public Service, and Outcome must be viewed separately.
The ultimate outcome of fostering the AI industry is not the number of AI companies. We must go down to whether defect rates at local manufacturing firms have decreased, whether sales and operational efficiency for small business owners have increased, and whether access to medical care and support for the elderly has improved.
Gyeonggi Province's AI & Digital Learning Center is an important policy in this regard. It has expanded the target audience to include not only the digitally vulnerable but also youth, middle-aged adults, and small business owners, and broadened the scope of education from practical life skills to generative AI. ( Gyeonggi Provincial Government )
However, the effectiveness of AI education is difficult to measure solely by the number of graduates. Outcomes such as actual work application, employment or job transitions, improved sales for small business owners, and increased use of public services are necessary after the training.
In a 2026 survey by the Gyeonggi Research Institute, 76.1% of respondents stated that AI is helpful in daily life, while 70.6% simultaneously expressed concerns about job losses. This indicates that residents are accepting AI not merely as a convenience technology, but as an economic transformation. ( Gyeonggi News Portal )
Accordingly, the evaluation unit of Gyeonggi-do's AI policy must also shift from the number of people educated to how the lives and jobs of local residents have actually changed .
The spatial AI disparity in Gyeonggi Province cannot be explained solely by the dichotomy of the South and the North. Seongnam and Yongin are centers of high-tech industries and R&D, while Hwaseong, Pyeongtaek, and Siheung have strong manufacturing bases, and areas such as Goyang, Namyangju, and Bucheon are characterized by large-scale living zones. Furthermore, Yeoncheon, Gapyeong, Yangpyeong, and Yeoju possess distinct population densities and industrial structures.
Nevertheless, the structure of the North-South gap remains significant. The fact that Gyeonggi Province is investing 526.5 billion won in the Northern Gyeonggi Grand Transformation Project by 2025 and separately pursuing the relocation of public institutions, industrial bases, transportation, and living infrastructure demonstrates that existing structural disparities are a target of policy. ( Gyeonggi News Portal )
This is the same reason why the Gyeonggi Research Institute proposed in 2026 the need to design differentiated strategies for a basic AI society by dividing the 31 cities and counties into six major regions. The analysis indicated that the northern Gyeongwon and Northeast regions have a greater demand for digital infrastructure building and vocational transition education , while the southern Southeast, Gyeongbu, and West Coast regions have a greater demand for advanced services, such as financial security and crime response, built upon their existing infrastructure. ( Gyeonggi News Portal )
Therefore, for Gyeonggi-do's AI policy, rather than providing one to each of the 31 cities and counties, it is more appropriate to guarantee basic access equally and differentiate industrial and lifestyle AX according to regional structures .
The AI gap is likely to solidify faster than the infrastructure gap. Companies that adopt AI early accumulate data and work experience as learning assets. In contrast, companies that fail to adopt it lag behind in both data accumulation and organizational learning. Over time, the gap in experience may widen more than the gap in the technology itself.
Gyeonggi Province’s full-scale launch of six AI innovation clusters in 2026 and the expansion of AI and digital learning centers to a scale of 150,000 people demonstrate that this transition has already entered the policy implementation phase. ( Gyeonggi News Portal )
More importantly, AI is set to begin being fully integrated into the industrial policies and administrative services of 31 cities and counties. If data standards and support systems are poorly designed during the initial two to three years, a structure could be created where leading regions accelerate while vulnerable regions fail to keep up despite policy support.
Therefore, the period from 2026 to 2028 is a Golden Time to decide whether Gyeonggi Province will make AI a cause of new regional disparities or use it as a tool to reduce existing regional disparities .
12-1. Golden Time Application Case in Basic Local Governments ① — Seongnam City
Seongnam is a prime example demonstrating the diffusion responsibility of a leading region in addressing the AI gap in Gyeonggi Province . Software, platform, and AI companies are concentrated around Pangyo Techno Valley, and Gyeonggi Province's first Physical AI Lab has been established in the Seongnam General Industrial Complex. Within the framework of six AI innovation clusters, the two functions of Pangyo and the Seongnam General Industrial Complex are simultaneously interconnected. ( Gyeonggi News Portal )
Seongnam's Golden Time is not merely about attracting more AI companies. It is more important to see how effectively Pangyo's software and AI capabilities are disseminated to Seongnam's manufacturing companies and other industrial sectors in Gyeonggi Province. In particular, the Physical AI Lab is designed to enable SMEs to demonstrate industrial robotic arms, AMRs, and process data, providing a structure that verifies technology diffusion between AI firms and manufacturing companies. ( Gyeonggi News Portal )
For Seongnam to become a successful model, the Runtime Chain—comprising AI company clustering, manufacturing company demonstration, commercial contracts, productivity improvement, and expansion to other cities and counties—must be verified by actual evidence. It contributes to alleviating the AI gap in Gyeonggi Province not by the leading region staying ahead alone, but by accelerating the transition speed of surrounding areas.
12-2. Golden Time Application Cases in Basic Local Governments ② — Uijeongbu City
Uijeongbu is a significant example in the opposite direction to Seongnam. Although it is a core living area in northern Gyeonggi, the concentration of traditional high-tech industries and R&D is weaker than in the southern region. The very fact that this area has been included as one of Gyeonggi Province's six AI Innovation Clusters by 2026 carries policy significance, serving as a test of the potential for the AI industry to expand northward . ( Gyeonggi News Portal )
Uijeongbu's "Golden Time" does not lie in replicating AI industrial complexes like Pangyo. It is more realistic to create a "Northern-style" AI application model by connecting the industrial, medical, welfare, education, and administrative demands of the northern region with AI. The Gyeonggi Research Institute also analyzed that the need for expanding digital infrastructure and vocational transition education is relatively greater in the northern region than in the south. ( Gyeonggi News Portal )
Therefore, to determine whether the Uijeongbu AI Cluster actually becomes a diffusion hub for the north, we must track not only the number of resident companies but also the adoption of AI by northern companies, the job retraining of local personnel, public AI services, and diffusion to nearby Yangju, Pocheon, Dongducheon, and Yeoncheon. If Uijeongbu succeeds, Gyeonggi Province's AI policy could shift from a Pangyo-centric model to a multi-centered AI ecosystem .
The first loss is the entrenchment of the industrial productivity gap . If the differences in cost, quality, delivery time, and development speed widen between companies that adopted AI early and those that did not, there is a possibility that regional industrial disparities will also expand.
The second factor is the talent gap. When AI-related jobs and education are concentrated in specific regions, young people and skilled professionals also migrate to those areas. As corporate clustering and talent clustering reinforce each other, it becomes increasingly difficult for latecomer regions to catch up on their own.
The third issue is the disparity in public services. Local governments with abundant financial resources, data, and expertise can rapidly introduce AI services in transportation, welfare, safety, and healthcare, while cities and counties lacking these capabilities may experience delays. This could lead to a situation where the level of AI public services available to Gyeonggi-do residents varies depending on their place of residence.
The fourth is the illusion of the average effect of policy . Even if the total number of AI companies and investment in Gyeonggi Province increases, if they are concentrated in specific cities and counties, the provincial average may improve, but regional disparities could actually widen.
Gyeonggi Province also possesses favorable conditions for mitigating regional disparities in AI. This is because it simultaneously has Pangyo, a powerful AI hub; South Korea's largest manufacturing base; universities, hospitals, and research institutes; and the diverse industrial and living environments of 31 cities and counties.
In particular, there is no need to create the same AI industry in every region. Roles can be set differently, such as AI and software in Seongnam, manufacturing AX in Hwaseong and Siheung, public services and job transition in Uijeongbu and the northern region, and AI for agriculture, medical care, and care in rural areas.
If this differential structure works properly, Gyeonggi Province can create a multi-core AX model that connects the different strengths of the region with AI, rather than eliminating the AI gap.
It is impossible and unnecessary for all 31 cities and counties to become Pangyo. What is important is that no matter where one lives, they are not structurally excluded from economic, educational, and administrative opportunities due to AI.
Gyeonggi Province first needs an AI Readiness Map for its 31 cities and counties . It is not a list of AI projects, but a structure that continuously measures each region's access, industry, workforce, public services, and performance using the same standards.
Changes to observe | Things to do with AX | Policy decision | Verification indicators |
| Focus on AI companies | Mapping of businesses and investments by city and county | Specialized support for vulnerable areas | Changes in AI companies and investments |
| Corporate AX level | AI Maturity Assessment by Industry | Customized implementation support | AX Adoption Rate and Productivity |
| AI workforce | Demand analysis by job function and region | Education and retraining placement | Employment, transition, and settlement rates |
| Accessibility for residents | Analysis of education and facility usage data | Expansion of mobile and dispatched training | Participation rate and re-use rate |
| AI Public Services | Comparison of services in 31 cities and counties | Joint AI-based provision | Utilization rate and processing time |
| Northern-South gap | Readiness Comparison by Region | Regional differential policy | Gap change rate |
| Transition to SMEs | Cost, Data, and Personnel Bottleneck Analysis | Joint Testbed | Sales, Cost of Goods, and Defect Rate |
| Elderly and rural areas | Medical, transportation, and welfare demand forecasting | Lifestyle AI priority | Access time · Service usage |
| Regional data | Data quality and standard analysis | Standardization of 31 cities and counties | Number of linked datasets |
The key is not to provide support for the AI gap in 31 cities and counties after a problem arises, but to constantly monitor the speed of change and intervene preemptively .
Opportunity + Structural Risk
Gyeonggi Province is one of the regions in South Korea with the highest capabilities for AI transformation. Pangyo AI companies, advanced manufacturing, universities and research institutions, large-scale markets, and administrative data represent powerful opportunities.
However, precisely because of that strength, there is also a significant risk that the gap will widen. If leading regions absorb AI more quickly, companies, talent, capital, and data will concentrate back in those regions.
The fact that 46.0% of Gyeonggi residents expressed concern in a 2026 survey by the Gyeonggi Research Institute regarding the possibility of widening regional disparities due to AI demonstrates that this issue has already begun to manifest as a social awareness rather than a potential risk at the policy level. ( Gyeonggi News Portal )
Gyeonggi-do's Golden Time is determined to be the point in time when it must simultaneously push AI-leading regions further ahead and lift lagging regions .
In future runtime analysis, it is necessary to continuously track the following evidence at the smallest level.
- Number of AI-related companies by 31 cities and counties
- AI company establishment, relocation, and closure rates
- AI-related investment raised
- AI and software employment figures
- Net Inflow and Net Outflow of AI Professionals
- AI·AX Adoption Rate in Manufacturing Companies
- AI adoption rate in SMEs
- Changes in productivity of companies adopting AI
- AI-related average wages
- Access to AI educational facilities
- Number of trainees at AI and Digital Learning Centers by city/county
- Education participation rate relative to the population
- AI education participation rates by age
- Work utilization rate after training
- AI utilization rate among small business owners
- Accessibility to AI education for schools and youth
- Number of public AI services by city/county
- Actual usage rate of public AI services
- AI adoption rate in administrative tasks
- City/County Data Standardization and Linkage Levels
- Northern and Southern AI company density gap
- Corporate Performance of 6 AI Innovation Clusters
- Technology diffusion to regions outside the AI cluster
- Regional demand for AI job transitions
- Changes in income, productivity, and public service gaps due to AI use
In particular, the lack of a public AI statistical system that compares the 31 cities and counties using the same criteria needs to be managed as a core data gap.
Runtime Chain
Region-based → AI access → Education/talent → Utilization by businesses/administration → Productivity/services → Changes in income/living standards → Widening or narrowing of disparities between cities/counties
The most important recent evidence for this analysis is the report "The Rise and Significance of an AI-Based Society: Residents' Perceptions and Policy Challenges," released by the Gyeonggi Research Institute on August 27, 2026. In a survey of 4,700 Gyeonggi residents, awareness of an AI-based society was only 5.4%, but 66.8% agreed on its necessity after an explanation. Responses indicated that AI is helpful in daily life: 76.1% expressed concern about job losses, 70.6% about deepening social inequality, and 46.0% about widening regional disparities. ( Gyeonggi News Portal )
In particular, it is significant that 77.5% of respondents answered that they were unaware of whether public facilities or programs for AI experience and learning exist in their area . This demonstrates that providing AI policies is a different matter from ensuring residents have access to them. ( Gyeonggi News Portal )
Accordingly, the Gyeonggi Research Institute proposed a dual structure tailored to the industrial and digital infrastructure of the six major regions, rather than treating the 31 cities and counties uniformly. This approach combines region-specific policies—such as providing AI competency training, protection against voice phishing and deepfakes, emergency medical services, and welfare as basic services across all regions, with digital infrastructure and career transitions in the north and more advanced services in the south—with the latter. ( Gyeonggi News Portal )
Gyeonggi Province's policies are also shifting in this direction. The six AI innovation clusters represent a transition from a sole concentration in Pangyo to a multi-core structure, while the plan for 150,000 AI and digital learning centers is an attempt to expand access to AI beyond industrial policy. However, the establishment of clusters and educational goals focus on input and output , and must be distinguished from outcome evidence that the actual gap among the 31 cities and counties has narrowed . ( Gyeonggi News Portal )
Structural insights remaining from this analysis
The essence of the AI gap in Gyeonggi Province is not the difference in the number of AI facilities. It lies in the possibility that AI will operate in a way that amplifies existing regional disparities .
In regions where research institutions, large corporations, universities, high-tech manufacturing, and high-income talent are already concentrated, AI further enhances the productivity of existing assets. Companies accumulate more data, talent flocks to better firms, and local governments secure more private sector technologies and opportunities for demonstration. This virtuous cycle can widen the initial regional gap over time.
Conversely, in regions lacking industrial infrastructure and talent, it is difficult to achieve the same effect with just a few AI training sessions or the establishment of a single center. Therefore, the very assumption that identical inputs will produce identical results in AI policy is dangerous.
For this reason, Gyeonggi-do needs two policies simultaneously. One is to guarantee Minimum AI Access in education, medical care, welfare, and administration for all residents , and the other is to create different Regional AX Models tailored to the industrial and living issues of each city and county .
Seongnam's AI can be connected with manufacturing, software, and physical AI, while Uijeongbu's AI can become a hub for the transition of northern enterprises and public services. In rural areas, connecting with agriculture, healthcare, and care services can generate higher outcomes. Acknowledging these differences is the only way to reduce the AI gap across Gyeonggi Province as a whole.
And to achieve this, what is needed first is not a single new AI project, but a data system that measures the AI Readiness of 31 cities and counties annually using the same standards . A gap that cannot be measured is, in terms of policy, practically the same as not existing at all.
Golden Time Thesis — Gyeonggi-do's AI competitiveness is not determined solely by how far ahead Pangyo is. Whether 'One Gyeonggi-do' can be formed depends on how quickly AX is disseminated within the next two to three years, while measuring the different AI starting lines of the 31 cities and counties and ensuring minimum access rights for all, and tailoring it to the industrial and living structures of each region.
Version | Reference Date/Revision Date | Major changes |
| v1.0 | 2026.08.28 | Compiled the first-ever analysis of disparities in AI access, industry, education, and administration across 31 cities and counties in Gyeonggi-do. Determined "Golden Time" based on AI Readiness differences between the Southern High-tech Industrial Zone and the Northern and Eastern regions, residents' AI accessibility, six AI Innovation Clusters, and application cases in Seongnam and Uijeongbu. |
