Only 21% of Firms Leverage Tech to Meet Environmental Goals

A Microsoft and Kyndryl study showed that only 21% of companies worldwide use technology to reduce their environmental footprint and shape their strategies. The report highlights the growing role of data and AI in helping organizations turn their environmental goals into actionable, data-driven plans.

The second Global Sustainability Barometer report, conducted by Ecosystm, a digital research and advisory company, revealed that while 84% of organizations place high strategic importance on achieving sustainability goals, only about a quarter of them rely on digital tools for these purposes. The research, conducted between August and September 2024, surveyed the perspectives of 1,355 global sustainability leaders from 20 countries and 9 industry groups.

According to the study, the financial services, manufacturing, and retail sectors are leading in digitalizing their operations, with 40%, 15%, and 15% adoption rates, respectively. In contrast, industries like construction, energy, hospitality, primary industries, media, and logistics are falling behind, with only 5% implementing digital tools in their supply chains. In terms of countries, the leaders were Canada, India, and the United States. In Mexico, only 4% of companies reported utilizing digital tools to support sustainability efforts.

Faith Taylor, Corporate Citizenship and Sustainability Director, Kyndryl, emphasized the urgency of having viable strategies to transition toward sustainable development. “As the world faces growing climate challenges, companies are under pressure to act decisively and prioritize sustainability. This year’s Global Sustainability Barometer highlights that organizations must move from intention to collective action to drive change,” she said. The report stresses that by embedding technology into sustainability strategies, enterprises can turn abstract goals into actionable, data-driven plans.

The study showed that only 21% of organizations globally recognize technology’s dual role in reducing their carbon footprints and advancing broader sustainability goals. Furthermore, while 54% of businesses say sustainability goals and initiatives are integrated into existing reporting processes, only 19% fully use data for strategic planning and decision-making. Similarly, 55% believe artificial intelligence (AI) will significantly impact on their sustainability goals, but 62% limit initiatives to analyzing historical data for monitoring and reporting.

To improve this situation, the report outlines a series of guiding principles to achieve sustainability potential through strategic innovation. First, integrating digital solutions into sustainability strategies is essential. Data integration, measurement, and reporting tools can align sustainability objectives with core business priorities. The document emphasizes that this approach not only helps corporations manage risks and reduce costs but also opens new revenue opportunities, driving impactful sustainability initiatives. Additionally, the report advises supporting technology teams in achieving sustainability goals and adopting sustainable practices. Modernizing systems for competitiveness and efficiency is now crucial. "Green IT" initiatives should extend beyond reducing carbon emissions from infrastructure to include emissions related to procurement, management systems, processes, and IT operations disposals.

The study also highlights AI's potential to transform efforts by optimizing resources, enhancing energy efficiency, and proactively addressing challenges. “Beyond reducing environmental footprints, predictive AI assesses climate risks, guiding strategies to protect operations and ensure business continuity. It also evaluates the entire value chain for climate risk, promoting a holistic approach to environmental responsibility and readiness for future challenges,” the report states.

On the other hand, it acknowledges that as AI models become more complex and data-intensive, their training and operation may increase the energy and water consumption required to run data centers. To address this dilemma, companies should optimize AI architectures for efficiency. This involves leveraging specialized processors, adopting efficient training methods such as transfer learning, using smaller language models, and implementing edge inference to reduce data processing needs. Firms should also invest in renewable energy sources and energy-efficient data centers to offset the environmental footprint associated with cloud computing.

“As organizations increasingly recognize sustainability as a strategic imperative, we are witnessing a rise in innovation and collaboration. AI is at the forefront of this movement, enabling businesses to optimize resource consumption, reduce waste, and drive a positive environmental impact,” stated Ullrich Loeffler, CEO, Ecosystm.