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Paper short abstract

This paper compares competing AI pathways in developing contexts, contrasting digital authoritarianism with developmental governance. It examines how political institutions shape AI use for control, capacity-building, and development outcomes.

Paper long abstract

This paper examines how artificial intelligence (AI) is reshaping governance trajectories in developing and transitional economies through two competing pathways: digital authoritarianism and developmental governance. While AI is frequently promoted as a neutral tool for efficiency, service delivery, and innovation, its deployment is deeply embedded in political and institutional contexts that shape development outcomes.

The first pathway, digital authoritarianism, emphasises AI-enabled surveillance, predictive policing, population monitoring, and behavioural control. In this model, AI strengthens executive power, reduces political accountability, and normalises data-driven social control, often under the banner of security, efficiency, or crisis management. Rather than enhancing state capacity in a developmental sense, such uses of AI risk undermining institutional trust, civil liberties, and inclusive growth.

The second pathway, developmental governance, frames AI as a public infrastructure supporting administrative capacity, transparency, and equitable service provision. When embedded in robust regulatory frameworks, independent oversight mechanisms, and participatory governance structures, AI can enhance policy effectiveness and contribute to long-term development goals. This pathway aligns more closely with the principles of accountable institutions and inclusive decision-making emphasised in SDG 16.

Drawing on comparative examples from emerging economies and hybrid political systems, the paper adopts a political economy approach to analyse how power relations, market structures, and institutional design determine which pathway prevails. It argues that AI does not inherently produce authoritarian or developmental outcomes; rather, outcomes depend on governance choices, regulatory capacity, and the balance between public interest and private technological power.