Artificial Intelligence

How technology can drive sustainability goals for people and planet

In China, pilot cities improved cardiac arrest survival rates by using digital platforms to connect citizens. How can technology also help sustainability?

Scaling sustainability solutions means transforming how systems function in all industries – from healthcare to supply chains and infrastructure. Image: Unsplash/VitalyGariev

Caitlyn Chen Juhong
Vice-President; Head, Sustainable Social Value, Tencent Holdings
Denise Rotondo
Lead, Community of Sustainability Officers, World Economic Forum
This article is part of: Centre for Nature and Climate
  • Most companies have created targets to drive sustainability efforts, but progress on scaling related solutions often lags ambition.
  • To scale sustainability solutions, companies in all industries must rethink how entire systems function.
  • Artificial intelligence will play a central role in this, but effectiveness will depend on the ability to fundamentally redesign systems.

From climate targets to resource constraints, today’s business leaders face a common challenge: how to translate sustainability ambitions into measurable, scalable outcomes.

Across industries, companies have set targets on net zero, nature and social impact, but progress often lags behind commitments. The gap is financial, as well as operational.

Delivering sustainability at scale means transforming how systems function – from healthcare and supply chains to consumption and infrastructure.

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Aligning tech with system-level challenges

A central question for many companies is where technology can have the greatest impact on sustainability. In practice, this often comes down to identifying points of friction in complex systems, where information gaps, coordination failures, or lack of trust limit outcomes.

In China, out-of-hospital cardiac arrest survival rates have historically been around 1%, reflecting challenges in emergency response coordination. Through the use of digital platforms to connect citizens, first responders and medical professionals in real time, survival rates in pilot cities significantly improved.

While healthcare is not always framed as a sustainability issue, the same kind of digital connectivity can strengthen the resilience and performance of systems that underpin sustainable development, too.

A similar dynamic can be seen in philanthropy. Lack of transparency has long constrained participation, as donors struggle to verify how funds are used. By embedding traceability into digital donation systems, making contributions as seamless and verifiable as everyday transactions, platforms can build trust and encourage more consistent engagement.

In both cases, the role of technology is not simply to innovate, but to enable systems to function more effectively at scale.

Sustainability: from innovation to adoption

One of the most persistent barriers to sustainability is the difficulty of moving from innovation to widespread adoption of solutions. Many low-carbon and resource-efficient solutions remain stuck at pilot stage due to fragmented ecosystems and misaligned incentives.

Efforts to advance carbon neutrality, for example, increasingly depend on collaboration between scientists, engineers and companies. Scientists focus on new knowledge breakthroughs, engineers on optimizing performance and companies on creating scalable, commercially viable solutions.

Bringing them together in a collaborative way creates real-world benefits. And digital platforms can help bridge the gaps between these groups by facilitating knowledge exchange, connecting stakeholders and accelerating feedback loops between research and deployment.

Such collaborations could reveal that a problem that has vexed professionals in one arena may have already been solved in another. Real-time rendering technologies originally developed for video games are now being used to enhance cultural heritage preservation, for example, enabling more immersive and accessible museum experiences. At the same time, advances in artificial intelligence (AI) are supporting researchers in decoding ancient inscriptions, helping to preserve cultural and natural capital.

Scaling sustainability often depends on combining existing capabilities across sectors, rather than relying solely on new inventions.

How to drive sustainability performance

The rapid development of AI is adding a new dimension to sustainability strategies.

AI enables organizations to analyze complex systems in real time, optimize resource use and improve decision-making. In operational contexts, this can translate into more efficient energy use, reduced waste and better supply chain visibility. In consumer-facing environments, it can help make the impacts of everyday choices more visible and actionable.

The sustainability implications of AI are not unidirectional, however. The growing energy demand of data centers, alongside questions around data governance and equitable access, highlights the need for responsible deployment.

Technology alone does not guarantee positive outcomes. Its impact depends on how it is governed, integrated and aligned with broader sustainability goals.

Trust, governance and scalability

As digital solutions become more central to sustainability, trust is a critical factor. Whether in philanthropy, supply chains, or climate data, participation depends on confidence in how information is used and shared.

For businesses, this creates a dual imperative to use technology for impact, while ensuring robust governance frameworks. Without this balance, even the most advanced technological solutions may struggle to gain widespread adoption.

At a system level, scaling these approaches will also require greater interoperability and collaboration across sectors. Fragmented data and siloed systems remain significant barriers globally – across industries and geographies alike.

Implications for business leaders

For chief sustainability officers and business leaders, several priorities are emerging:

  • Embed sustainability into core digital strategies, aligning it with existing platforms and capabilities.
  • Use data and AI to drive measurable outcomes, particularly in areas such as emissions, resource efficiency and system performance.
  • Engage in ecosystem partnerships to scale solutions beyond organizational boundaries.
  • Invest in trust and governance, ensuring responsible use of technology.

These priorities are increasingly reflected in global discussions, including within the World Economic Forum’s chief sustainability officer community, which is working to accelerate the role of business in delivering climate and nature outcomes through innovation and collaboration.

When incentives are aligned across stakeholders and sustainability is embedded into the tools people already use every day, change becomes a natural byproduct of the system rather than an uphill battle.

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Executing on sustainability commitments

The next phase of the sustainability transition will be defined by execution. Corporate commitments are widespread, now the challenge is to deliver tangible results.

Technology, particularly data and AI, will play a central role in this. But its effectiveness will depend on whether it is used to incrementally improve existing processes or to fundamentally redesign systems.

When digital capabilities are deployed with genuine purpose – when co-creation is given real structure, when digital technology is deeply integrated into daily life and when the question of who benefits stays at the centre of the work – technology becomes something more than a tool. It becomes a pathway.

Growth is not linear. It involves stumbling, getting back up and standing a little firmer each time you rise. This is a difficult approach to take, but it can also be the most rewarding.

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The views expressed in this article are those of the author alone and not the World Economic Forum.

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