This year’s World Economic Forum (WEF) was undoubtedly momentous. Alongside the complex geopolitical backdrop, artificial intelligence (AI) emerged as a central theme both in formal and informal sessions. The attention shifted away from novelty to execution: scaling AI adoption, delivering measurable economic impact, and ensuring its benefits are shared across countries and sectors.

Underlying many of these discussions was a shared concern: if AI remains concentrated in a small number of advanced economies, firms, and platforms, it risks reinforcing global inequality rather than narrowing it. Without widespread and affordable adoption that benefits the real economy and democratizes breakthroughs in areas like health and education, the ‘social license’ to feed AI’s insatiable appetite for energy, water and infrastructure may quickly fade. 

This challenge of widespread adoption and affordability is closely linked to the shifting geopolitical landscape. The global economy is no longer organised around a single technological centre of gravity.  Trade frictions, export controls, industrial policy, and security considerations are reshaping supply chains for semiconductors, data-centre equipment, and critical minerals. Diverging approaches to standards, data governance, and technology regulation add a further layer of complexity. In this context, access to AI is shaped not only by innovation capacity, but also by access to compute, data sovereignty, reliable clean power, connectivity, financing, and partnerships.

For developing economies facing constrained fiscal space and competing development priorities, these considerations are immediate and consequential. The infrastructure investment needed to advance AI is already a magnitude more than the current SDG financing gap. This is why widespread AI adoption must be treated as a central development objective. In terms of energy – and very practically - AI adoption offers the opportunity for a ‘twin’ sustainable technology and energy transition. 

AI ‘diffusion’ also requires affordable access to models, deployment in local languages, and integration into small and medium-sized enterprises, and public services. It is the difference between AI as a demonstration technology and AI as a driver of productivity, inclusion, and resilience. 

The projected benefits are even greater. Globally, AI-driven efficiency gains in industry, logistics, agriculture, energy, and public services are projected to add USD$15 trillion to GDP by 2030. Regionally, ASEAN nations could see GDP contributions topping 3%, or ~USD$1 trillion, with Indonesia adding about $USD360bn to its economy. But these gains require deliberate policy choices, appropriate financing, and human capacity. In Indonesia, roughly USD$3 billion is needed in computing infrastructure by 2030.

Blended finance is critical to converting the promise of AI into reality. Through platform such as the G20 Bali Global Blended Finance Alliance, concessional capital, guarantees, and risk-sharing arrangements can mobilize and help crowd in private investment for the infrastructure underpinning sustainable and sovereign AI, while directing deployment toward sectors with strong public and economic returns. 

In this regard, this year’s “Blue Davos” theme offered a needed reality check of how AI will, and already is, impacting on our physical environment and the ‘value’ of nature. The growing recognition that oceans, coastal systems, and nature-based assets are central to sustainable economic growth, resilience, and food and energy security matters. In the context of AI, it matters because this technology is firmly embedded in physical systems: energy grids, water infrastructure, logistics networks, and natural capital. 

These linkages are particularly significant for emerging markets, where economic development, environmental exposure, and demographic pressures intersect most directly. As data centers expand, they will compete for the same power, land and water that communities and productive sectors rely on. Indonesia’s geography makes this challenge more complex, but also more strategic. 

We also face profound choices to protect and invest in human assets. A recent UNDP report, The Great Next Divergence, warns that new waves of digital and AI-driven growth could widen economic gaps if access, skills and institutional capacity remain uneven. The International Monetary Fund (IMF) estimates that AI could affect around 40% of jobs globally and up to 60% in advanced economies, with young people and entry-level workers particularly exposed. 

How these choices play out in practice is already visible in the Blue Economy sector. AI-driven monitoring is improving fisheries management and reducing illegal, unreported, and unregulated fishing, supporting livelihoods while sustaining fish stocks. In ports and shipping, AI can optimise vessel movements and terminal operations, reduce congestion and fuel use, and lower emissions — outcomes of particular importance for trade-dependent developing economies. 

In aquaculture, AI-based sensing and feeding systems can increase yields while reducing waste, water use, and disease risk. Coastal countries are also applying AI to map and monitor mangroves, coral reefs, and seagrass, strengthening the valuation and protection of natural assets that underpin food security, tourism, and climate resilience. And, more recently, our seas are offering solutions to the AI-resource conundrum, hosting ‘floating’ data centres that recycle sea water for cooling and use the ocean’s own wave power for energy.

This year’s UN Ocean Impact Summit in Bali will highlight these and place greater emphasis on AI solutions that are grounded in real economic and environmental contexts. For Indonesia, this shift is particularly timely. Digital transformation sits at the core of national development ambitions, from building a digitally skilled workforce of nine million by 2030, to expanding smart city initiatives and supporting sustained economic growth. AI is expected to play a key role in improving public services, raising productivity, and strengthening competitiveness across a vast and diverse archipelago.

The real message from Davos was an urgency to consider the choices we make now. An Indonesian proverb captures this moment well: ‘berakit-rakit ke hulu, berenang-renang ke tepian: The hard journey upstream determines how safely we reach the shore’. Decisions about how AI is financed, governed and deployed today will determine human development, the possibility for real freedom of all people to decide who to be, what to do, and how to live, as it was coined long ago by Amartya Sen and Mahbub ul Haq, in our shared planet. 

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Rriginally published on The Jakarta Post.