AI and Equal Opportunity: The Digital Divide and Turkey

Being able to access a tool and getting meaningful value from it are not the same thing; the new inequality can grow in exactly that gap.

Is AI for Everyone? The Digital Divide and a New Inequality of Opportunity

Does a free tool mean equal opportunity?

Imagine offering two people the same AI app. One has fast internet, an up-to-date device, strong English and people around them who have taught them how to ask good questions. The other worries about data costs, uses an old phone and doesn’t know how to check whether the answers they get are correct. Both may be able to access the app. But the opportunity they get from it is not equal.

That’s why, in AI debates, the line “it’s now open to everyone” is not enough. Effective use requires infrastructure, time, skills, local-language support, trust and the capacity for critical evaluation. New technology can reduce old inequalities; it can also make them less visible.

The digital divide is no longer just about connectivity

The World Bank’s Digital Progress and Trends Report 2025 frames AI readiness around four elements: connectivity, compute, context and competency. Internet access is the starting point. The cost of computing infrastructure, reliable data in local languages and users’ skills also determine the capacity to benefit from the technology.

This framework is as useful for organisations as it is for individuals. It may be easy for a small business to open an account with an AI tool; integrating it into a secure workflow, a sales experience or high-quality customer communication requires a different kind of organisational capacity. Buying a tool is not a transformation strategy.

What do Turkey's 2026 figures show?

According to the Turkish Statistical Institute’s (TÜİK) Artificial Intelligence Statistics bulletin of 2 October 2026, the share of people aged 16–74 who report using generative AI rose from 19.2% in 2025 to 37.6% in 2026. Usage varies sharply by education level: in 2026 it was 62.7% among university graduates and 8.5% among those with primary education. The same bulletin reports that 14.0% of enterprises with at least 10 employees use at least one AI technology.

These figures matter, but we need to read correctly what they measure. The indicator for individuals is a self-reported usage rate, not a direct measure of skill or economic gain. The enterprise figure represents businesses with at least 10 employees, not all micro-businesses. In short, rising usage may be a positive signal, but on its own it doesn’t prove that the benefits are shared equally across society.

Education and language: The invisible gateways

There is a skills gap between opening an AI app and defining the right problem. If users don’t know when the output may be wrong, where they shouldn’t share personal data and how to verify the result, simply having the tool may not be enough. AI literacy isn’t just writing good prompts; it is understanding a system’s limits, risks and appropriate use.

Language and cultural context can also be decisive. If a system poorly represents a local industry’s terminology, regional needs or everyday cultural cues, it may not deliver the same quality of experience. Accessible design, suitable interfaces for people with disabilities and training that fits different learning needs are also part of equal opportunity.

Where is the real opportunity for small businesses?

AI can make it easier for small businesses to produce visuals, communicate with customers, prepare proposals and access information. This is an important democratising potential: some creative services that only large budgets could once afford may become accessible. But cheaper tools don’t automatically provide the skills to write a good brief, define brand positioning, control quality and choose effective distribution channels.

Take two businesses using the same video production platform. One has a clear target audience, product promise and measurement approach; the other simply copies a popular visual style. Even with similar access to production technology, their communication results may differ. Equal opportunity is not just being able to press the button; it is understanding which strategic goal that button serves.

What responsibilities does equal opportunity require?

Governments, educational institutions, platforms and companies can play different roles. Reliable connectivity, basic digital skills, teacher and employee training, local-language support and accessible product design all complement each other. Low-cost options can help, but they don’t solve every inequality on their own. Training programmes shouldn’t be limited to tool demos; they should also cover critical evaluation and data security.

For organisations, inclusion shouldn’t become an abstract CSR slogan. Who was the product designed for? Who can’t use the interface? Which users can’t get their problem solved? Which metrics show participation, and which show real benefit? Asking these questions regularly can turn inclusive innovation into a measurable area of work.

Conclusion: Technology can belong to everyone; capability doesn't level out on its own

AI is creating new possibilities for many people and businesses. But those possibilities won’t be shared equally by themselves. The areas of infrastructure and competency highlighted by the four Cs need to be considered together with social conditions and organisational strategy. Otherwise, those who already use technology well will move faster while others fall behind.

What matters for NeoMinds Media’s approach to accessibility is not to describe AI only in terms of production speed and low cost. A more meaningful goal is for small businesses, too, to gain access to quality storytelling and strategic communication capability. A fair technological future will be built to the extent that we narrow the gap between having access to a tool and truly having a voice.