The phrase “science, technology and innovation” can sound abstract, like the language of panels, white papers and international forums. But underneath the acronym is something much more human: the desire to make life work better.
At the core is a transition: the understanding that today’s choices shape tomorrow’s world, especially now, as technology and AI are changing how we live, work and build the future.
A clinic that can keep vaccines cold because it has reliable solar power. A farmer who uses weather data to decide when to plant. A student in a rural town using digital tools to learn skills that were once out of reach. A young founder building a company around clean water, logistics, agriculture or health care. A city using better data to prepare for floods instead of only responding after disaster strikes.
The scale of that transition is already visible. Mobile technologies and services generate about $6.5 trillion in economic value, roughly 5.8 percent of global GDP. Solar power has become dramatically cheaper, with utility-scale solar photovoltaics averaging $0.043 per kilowatt-hour in 2024. Data center electricity consumption, meanwhile, is projected to more than double to about 945 terawatt-hours by 2030. The same technological age that expands possibility is also reshaping energy demand, infrastructure planning and the economics of development.
The real promise of science, technology and innovation is not novelty for its own sake. Not gadgets. Not a futuristic sales pitch. The promise is capability: the ability of people, communities and countries to solve problems faster, cheaper and more fairly than before.
Science, technology and innovation are not magic. They are infrastructure.
They are part of the machinery that determines whether global goals become practical progress.
| Layer | What it Enables | Where the Gap Appears | Development Implication |
|---|---|---|---|
| Connectivity | Entry into digital systems | Billions remain offline | Access is still foundational |
| Infrastructure | Reliable use at scale | Weak grids, broadband and cloud access | Digital tools remain fragile |
| Skills | Local adaptation and repair | Thin technical pipelines | Imported tools create dependency |
| Institutions | Procurement, oversight and trust | Slow or weak governance capacity | Innovation fails to scale safely |
| Agency | Ability to shape technology | Systems designed elsewhere | Countries consume rather than build |
| Sources: World Bank, ITU, UNDP | |||
The Current Status
At the core of economic development are science, technology and innovation. Their impact can be dramatic, shaping how societies respond to poverty, health, education, energy, climate resilience and the broader pursuit of human prosperity. With a forward-looking approach, they can become practical tools for advancing the Sustainable Development Goals and measuring progress toward 2030.
UN Sustainable Development Goals
| SDG | Goal | Internet Economics |
|---|---|---|
| SDG 9 | Industry, Innovation and Infrastructure | Connectivity and compute are transformational economic infrastructure. Connectivity has a profound impact on quality of life and humanitarian issues. |
| SDG 8 | Decent Work and Economic Growth | The Internet is disrupting economies as the labor force shifts to align with modern needs. Skill bases are moving toward specialists who can operate machines and digital systems. |
| SDG 10 | Reduced Inequalities | Digital exclusion creates economic exclusion. Internet access, skills, and AI capacity reduce participation gaps. |
| SDG 17 | Partnerships for the Goals | For most countries, technology transfer is the largest partnership need. Many do not yet have the technology or education base to match first-mover nations. |
| SDG 13 | Climate Action | Digital systems support climate data, planning, and resilience. Terrestrial economies must account for energy, hardware, and e-waste costs. |
Sources: United Nations Sustainable Development Goals; Institute of Internet Economics analysis.
SDGGoalInternet EconomicsSDG 9Industry, Innovation and InfrastructureConnectivity and compute are transformational economic infrastructure. Connectivity has a profound impact on quality of life and humanitarian issues.SDG 8Decent Work and Economic GrowthThe Internet is disrupting economies as the labor force shifts to align with modern needs. Skill bases are moving toward specialists who can operate machines and digital systems.SDG 10Reduced InequalitiesDigital exclusion creates economic exclusion. Internet access, skills, and AI capacity reduce participation gaps.SDG 17Partnerships for the GoalsFor most countries, technology transfer is the largest partnership need. Many do not yet have the technology or education base to match first-mover nations.SDG 13Climate ActionDigital systems support climate data, planning, and resilience. Terrestrial economies must account for energy, hardware, and e-waste costs.
Sources: United Nations Sustainable Development Goals; Institute of Internet Economics analysis.
The world is not short on technological possibility. Artificial intelligence can help institutions make sense of complex information. Solar power can expand access to reliable electricity. Digital platforms can connect people to services, markets and education. Better data can help governments, businesses and communities prepare for risks before they become crises.
The reach of digital technology is enormous, but still incomplete. Around 2.6 billion people remained offline in 2024, and internet use ranged from more than 90 percent in high-income countries to just 27 percent in low-income countries. The divide is not only about connection. It is about who can use digital systems to learn, trade, govern, create and compete.
There is a great deal to be hopeful about. But optimism should not be confused with inevitability. The existence of a technology does not mean it will be widely shared, fairly governed or locally useful. A country may have access to advanced tools but lack the systems needed to use them well. A community may gain new infrastructure but lack the capacity to maintain it. A young entrepreneur may have a strong idea but no path to scale.
The central development challenge of the moment is clear: the world has more powerful tools than ever, but unequal ability to use them. The new divide is not simply between countries that have technology and countries that do not. It is between those that can turn technology into productive capacity and those left consuming systems built elsewhere.
Nowhere is that capability gap more visible than in artificial intelligence.
| AI layer | Typical controller | Policy concern | Capability Requirement |
|---|---|---|---|
| Models | Private AI firms | Concentrated technical power | Evaluation and accountability |
| Compute | Cloud and chip ecosystems | Unequal access to scale | Infrastructure bargaining power |
| Data | Platforms and institutions | Privacy, bias and extraction | Data governance capacity |
| Applications | Software vendors | Public-sector dependency | Procurement literacy |
| Infrastructure | Data center operators | Energy and water demand | Grid and resource planning |
| Sources: UNDP, UNCTAD, IEA, OECD | |||
AI as Infrastructure
Artificial intelligence is the most visible symbol of this transition. It is already changing how people work, learn, communicate, build companies and make decisions. Used well, AI can help institutions become faster, smarter and more responsive. It can support research, improve public services, expand access to information and help people solve problems that were once too complex or expensive to address.
At the recent UN STI conference, AI was one of the major concerns. The fear was not simply that AI would move quickly, but that it would create a sharper technological divide between those with access to advanced tools and those without it. The central concern was technology sharing and transfer: whether less-developed countries would be able to participate in the AI economy, or whether they would be left behind on the wrong side of a widening capability gap.
The divide is already visible. AI reached roughly 1.2 billion users in three years, with nearly 70 percent of those users in developing countries. But usage remains deeply uneven: in some high-income economies, roughly two in three people use AI tools, while many low-income countries remain near 5 percent. AI is spreading quickly, but capability is not spreading at the same speed.
It is also important to understand that while AI is a national policy concern, it is not usually created through national technology systems. Much of today’s AI is developed by private companies and implemented through their software, platforms and infrastructure. Whether that is because governments lack technical capacity, financing or institutional flexibility, the result is the same: corporations build the tools, and public institutions must decide how to access, govern and apply them.
AI investment is also becoming geographically concentrated. Around 75 percent of foreign direct investment into developing economies now flows to just ten countries, leaving many developing countries and nearly all least developed countries struggling to attract capital. In AI, that concentration matters because capital, compute, talent and infrastructure shape who gets to build the systems and who merely uses them.
AI is not weightless. It does not exist in some frictionless digital space. Behind every digital tool is a physical system that must be powered, cooled, secured and governed. Data centers need energy and water. Advanced chips depend on complex supply chains. Public agencies need technical expertise to understand the systems they adopt.
Data center electricity consumption is projected to more than double to about 945 terawatt-hours by 2030, just under 3 percent of global electricity consumption. From 2024 to 2030, data center power demand is projected to grow around 15 percent per year, more than four times faster than electricity demand in other sectors. AI has turned digital infrastructure into an energy-policy issue.
The better question is not whether AI should be part of sustainable development. It already is. The question is whether it will be treated as public infrastructure or simply as private power. A serious AI agenda would focus on access, transparency, local capacity and responsible governance. It would ask who benefits, who is accountable and whether the technology strengthens the people and institutions using it.
AI should not be treated as a shortcut around development. It should be built into development carefully, with the same attention given to roads, energy grids, schools and public health systems. It also reveals a larger truth about the digital economy: even the most advanced technologies have physical costs.
Environmental Cost of a Digital World
The clean, digital future has a material footprint, and that footprint is becoming a shared concern across countries.
For many developing economies, science and technology offer a chance to leapfrog older systems. A country does not always need to follow the same infrastructure path that wealthy economies built over decades. It can move directly into cleaner energy, digital finance, modern public services, remote learning and data-driven agriculture. One of the strongest links between STI and the Sustainable Development Goals is the possibility of moving faster toward access, resilience and opportunity.
Solar power shows how quickly the economics of development can change. Utility-scale solar reached a global weighted average cost of about $0.043 per kilowatt-hour in 2024, making it 41 percent cheaper than the lowest-cost fossil fuel alternative. Clean energy is no longer only an environmental preference. In many places, it is becoming the cheaper economic platform.
But leapfrogging also creates a new dilemma. Many countries look to developed economies as models for growth and modernization, yet those same models now come with visible environmental costs. The digital economy depends on physical infrastructure and natural resources. Clean-energy transitions rely on complex supply chains, storage, maintenance, recycling and long-term planning. The development question becomes more complicated: how can countries adopt the benefits of advanced technology without inheriting the same environmental problems?
Electronic waste has become too large to treat as an afterthought. A record 62 million tonnes of e-waste was generated globally in 2022, and only 22.3 percent was formally collected and recycled in an environmentally sound manner. The total is on track to reach 82 million tonnes by 2030. Digital inclusion creates opportunity, but every device eventually enters a material economy of repair, reuse, disposal or harm.
These concerns are no longer local. E-waste moves across borders. Supply chains connect distant economies. Data centers place pressure on regional energy and water systems. Climate risks do not respect national boundaries. In an interconnected economy, one country’s innovation strategy can become another country’s environmental burden.
The goal is not to ask developing countries to slow down. The goal is to help them leapfrog differently: not into the wasteful systems of the past, but into cleaner, more circular and more resilient models of growth. A technology is not truly advanced if it solves one problem by quietly creating another. It should be judged not only by what it can do today, but by how it affects the systems that future generations will inherit.
| Stage | Weak Transfer | Capability-building Transfer | Economic Result |
|---|---|---|---|
| Acquisition | Buying finished tools | Understanding system design | Better procurement |
| Operation | Vendor dependence | Local maintenance capacity | Lower fragility |
| Adaptation | Imported defaults | Local modification | Higher relevance |
| Learning | Consumption only | Skill and knowledge spillovers | Productivity gains |
| Production | Permanent import reliance | Domestic value-chain participation | Local capability |
| Sources: IMF, UNECA, OECD | |||
Technology Transfer
Beyond the barriers and limitations within any one country, innovation and technological readiness are often shaped by larger systems. Without strong education pipelines, countries struggle to produce the talent needed for tomorrow’s industries. Weak business environments can stifle growth, while poor market dynamics may discourage companies from entering or investing. In that context, external technologies and technology transfer can become essential to leapfrogging older development paths and keeping pace with global standards.
Technology transfer is often discussed as if it means moving tools from one country to another. But real technology transfer is deeper than access. It is the ability to use, adapt, maintain and improve technology locally.
A country that imports advanced systems but cannot repair them, regulate them or build around them remains dependent. A government that buys digital tools but cannot understand their risks remains vulnerable. A university that produces research but has no pathway to industry leaves value on the table.
The goal should not be permanent dependence on imported solutions. The goal should be local capability. Technology adoption can produce productivity gains when it becomes learning rather than consumption. The deeper economic value is not the arrival of a tool, but the ability to absorb it, modify it and build around it. Adoption works best when it helps countries become more capable over time, not simply better customers for products designed elsewhere.
Historical technology transfer in Korea shows the economic logic. Larger productivity gaps with foreign firms correlated with faster productivity growth after adoption, and non-adopting firms increased patent citations to foreign sellers, suggesting wider knowledge spillovers. The lesson is not that every country should copy one model. The lesson is that transfer works when imported knowledge becomes domestic capability.
For the SDGs, this distinction matters. The goals are not achieved by importing solutions alone. They require countries to build systems that can solve problems continuously. Health, education, energy, climate resilience and public services all depend on institutions that can learn, adapt and improve.
Technology transfer is not charity. It is economic strategy. It determines whether countries merely consume the future or help build it.
Youth Integration and Focus
Capability, however, is not built by technology alone. It is built by people who know how to use it, adapt it and imagine what comes next. As technology and mobile phones permeate the world, they expand what people can access, learn and build. This is especially true for young people, who often absorb new tools quickly and weave them into daily life.
Enabling that spread, and amplifying it in productive ways, can have a profound impact on the future. The same individuals using today’s technologies will become the next generation of workers, founders, voters, leaders and institution-builders. Their values, habits and social expectations will shape the years ahead.
Mobile connectivity has become a global economic platform, not just a communications tool. Mobile technologies and services generated around $6.5 trillion in economic value added in 2024, equal to about 5.8 percent of global GDP. For young people, the phone is often the first layer of the digital economy: school, work, finance, media, identity, opportunity.
Youth engagement is often described in sentimental terms, as if young people represent only hope for the future. But in the context of science, technology and innovation, young people are not just future beneficiaries. They are already part of the system.
They are early adopters of new tools. They are building companies, creating digital communities, experimenting with AI, organizing around climate risks and identifying problems that older institutions often move too slowly to see. In many countries, young people understand technological change not as an abstract policy topic, but as the environment in which they study, work and imagine their futures.
That makes youth engagement an economic issue, not just a social one. A country that fails to create pathways for young people to build, test and scale ideas is wasting talent. It is also weakening its own ability to adapt. New businesses often translate public goals into usable products and services. They turn climate ambition into energy models, health goals into delivery systems, education goals into learning tools and local problems into market opportunities.
But youth and entrepreneurship cannot be treated as decoration. Too often, they are invited into conversations without being given real access to decisions, resources or markets. A young founder may be praised for creativity but still blocked by procurement systems, weak financing, limited networks or regulations designed for older business models. A student may be encouraged to innovate but never given the technical education or institutional support needed to do so.
If STI is infrastructure, then youth and entrepreneurship are part of the workforce building it. They need skills, trust, capital, mentorship, public-sector openness and pathways into regional and global markets. More importantly, they need institutions that take their ideas seriously before those ideas become obvious.
The SDGs depend on this kind of participation. Sustainable development is not only delivered by governments or international organizations. It is also built through the everyday problem-solving of people close to the challenges.
| Governance domain | Without guardrails | With guardrails | Why it matters |
|---|---|---|---|
| AI systems | Opaque decisions | Auditable systems | Public trust |
| Public procurement | Vendor lock-in | Technical evaluation | Institutional control |
| Data protection | Citizen extraction | Clear rights and limits | Legitimacy |
| Environmental rules | Hidden externalities | Disclosure and standards | Sustainable scaling |
| International cooperation | Fragmented development | Shared norms and transfer | Capability diffusion |
| Sources: OECD, UNCTAD, UN DESA, World Bank | |||
Governance
A central concern among countries is governance: the guardrails, frameworks and guidance needed to shape technological development and reduce unintended consequences. This is especially critical in the current era of AI advancement, hyper-connected internet proliferation and ecological concerns related to data centers and transitioning economies. As technology advances quickly, countries need both internal regulation and global cooperation. The challenge is to create rules that protect people and institutions without cutting off the innovation needed for growth.
Innovation without governance can become extraction. Data can be extracted from citizens. Minerals can be extracted from vulnerable regions. Water can be consumed by digital infrastructure. Waste can be exported to communities with fewer protections. Public services can become dependent on systems they do not understand or control.
Governance is what prevents innovation from becoming merely another form of concentration.
Good governance does not mean blocking technology. It means setting rules that allow innovation to earn public trust. It means transparency around environmental impacts, accountability in AI systems, standards for data protection, responsible supply chains and public institutions that know enough about technology to regulate and procure it intelligently.
Many of the technologies shaping the SDGs are moving faster than the institutions responsible for governing them. The answer is not to slow everything down. The answer is to build adaptive institutions that can learn, update and respond.
Governance is not the opposite of innovation. It is what makes innovation durable. The real task is not to admire technology, but to build the conditions under which technology improves lives. Communities need the ability to shape the technologies deployed around them. Countries need local skills rather than simple access to imported tools. AI systems need transparency and accountability. Digital infrastructure needs to grow without deepening environmental stress. Young entrepreneurs need access to markets. International cooperation needs to build capability rather than dependency.
The most important shift is from access to agency. Access means people can use technology. Agency means they can shape it, govern it, repair it, improve it and build from it.
The SDGs describe the world countries are trying to build. Science, technology and innovation provide part of the machinery. But machinery only works when people have the skills, institutions and trust to operate it.
The best case for science, technology and innovation is not that they will save the world. That is too easy, and too false. The better case is that they can help people build better systems. That is a hopeful story, but not a naïve one. Technology brings tradeoffs. AI consumes resources. Digital systems create waste. Clean-energy transitions require planning. Innovation can concentrate power as easily as it can distribute it.
But that is exactly why science, technology and innovation matter. They force societies to decide not only what can be built, but what should be built, who gets to build it and who benefits when it succeeds.
The SDGs may provide the destination. But science, technology and innovation are part of the road, the vehicles, the fuel, the traffic rules and the repair crews.
They are not magic. They are infrastructure. And if built well, they can make the future feel less like a promise and more like something people can actually use.
Key Takeaways
- Science, technology and innovation are best understood as economic infrastructure, not abstract development language.
- The key development divide is shifting from access to capability.
- Digital tools are spreading quickly, but billions of people remain outside full digital participation.
- AI is becoming public infrastructure even when it is built through private companies.
- AI adoption is rapid, but usage and readiness remain sharply uneven across income groups.
- Data centers make the digital economy a physical infrastructure issue involving energy, water and grids.
- Solar power has become economically competitive, but its development value depends on storage, maintenance and recycling.
- E-waste shows that digital inclusion creates environmental obligations as well as opportunity.
- Technology transfer works when imported tools become domestic learning and productive capacity.
- Youth and entrepreneurs are not symbolic participants in STI; they are part of the workforce building the next economy.
- Governance is not a brake on innovation; it is what makes innovation trustworthy and scalable.
- The SDGs provide the destination, but capability determines whether countries can build the road.
Sources
- UN DESA; 11th Multi-stakeholder Forum on Science, Technology and Innovation for the SDGs; – Link
- UN DESA; Concept Note: STI Forum 2026; – Link
- World Bank Group; Digital and AI; – Link
- International Telecommunication Union; Facts and Figures 2024: Internet Use; – Link
- GSMA Intelligence; The Mobile Economy 2025; – Link
- United Nations Development Programme; The Next Great Divergence: Why AI May Widen Inequality Between Countries; – Link
- UNCTAD; AI Investment Boom Risks Widening Global Development Divide; – Link
- International Energy Agency; Energy Demand from AI; – Link
- International Renewable Energy Agency; Renewable Power Generation Costs in 2024; – Link
- International Telecommunication Union and UNITAR; The Global E-waste Monitor 2024; – Link
- International Monetary Fund; From Adoption to Innovation: State-Dependent Technology Policy in Developing Countries; – Link
- OECD; AI Principles; – Link
