Stop complaining about AI emissions: Get renewables and think positive outcomes

The technology sector produces (only?) 2-3% of global emissions, including hardware and chip manufacturing. Artificial Intelligence makes up a fraction of that (see Exhibit 1). Technology emissions—and water, material, and social impacts—must, of course, be addressed. And they are being. But for most business leaders, that is not the best use of your time and energy. Instead, you should focus on using AI—and all technology—to target positive outcomes for the environment, people, and your business. Don’t let the talk about AI’s energy consumption dominate the conversation at the expense of those outcomes.

This report covers a selection of stories and takeaways from a recent HFS Research summit. You can listen to a short summary here.

Exhibit 1: Breaking down the global context lets you focus on addressing the most material—positive and negative—sustainability spheres of influence

Source: HFS Research, World Data Lab, and World Economic Forum, 2024

Misinformation fuels the climate and sustainability emergency—but so does the lack of context

Insufficient context impacts our ability to tackle the climate and sustainability emergency. Climate denial is consigned to the fringes, while climate delay is now more mainstream in politics and business. But often, even with positive intentions, leaders lack the context to devote their time, energy, and resources to addressing their most material positive and negative spheres of influence.

The world needs to address technology’s emissions, water, and resource footprint, including AI. But the entire technology industry’s footprint does not compare to major emissions sources such as energy, buildings, transport, agriculture, and industrial manufacturing. The largest technology firms are also working on their footprints, including building and procuring renewable and nuclear energy. There’s so much more to do, but most business leaders should focus instead on the positive outcomes technology can help achieve. It is, however, worth spending a little time considering the teams that must address the sustainability of the technology they source.

For leaders and organizations with direct and indirect responsibility for technology emissions—both physical and digital—there are straightforward ways to measure and mitigate that impact

Hyperscalers’ efforts to decarbonize their operations and the data they publish makes quantifying sourced technology footprints relatively straightforward. That quantification provides a good idea of your material impacts and what your organization must address. Businesses can, of course, also source their own decarbonized energy. Most suppliers have data (or a conversion factor exists) for hardware to calculate a ballpark figure that can lead to prioritized action.

Energy and water consumption from data centers are absolutely local infrastructure challenges. So is the global sourcing of materials, including precious metals, for technology. You can read more here in our outline for addressing sustainability—we have most of the context and solutions we need.

Technology’s positive potential is the most important sphere of influence for the majority of business leaders, and that goes far beyond GenAI

Chief sustainability officers never complain of having too many resources. Sustainability teams are desperate for more time and energy to address sustainability—not only finding data and reporting to various regulations and voluntary standards and disclosure bodies. AI, whether generative or otherwise, is quickly showing its value in analyzing and connecting disclosure requirements, building reports, and enabling teams to focus on which reports need more work and how they can move from reporting to action. As you read this, all platform companies are offering and adding to their sustainability data and reporting solutions. Data and reporting are also the main entry point for new consulting, technology, and business services company clients.

2025 is set to be the year of the CSRD, the EU’s Corporate Sustainability Reporting Directive. It should be more. Beyond sustainability reporting, supply chains need new circular ideas and new efficiencies. Fuels need new chemistries. Communication needs new levels of storytelling. Waste needs to find new life. Cities need to become healthier places. We’ll be expanding on these themes soon. In the meantime, plenty of enterprise examples exist.

Financial services organizations, including asset managers, banks, and insurers, need the best data, risk, and opportunity analysis they can get—but they also need auditable processes and data for new and existing regulations (sector-specific and sustainability), which will be an additional demand for new tech including GenAI. AI developments also improve notoriously complex climate models and weather forecasts, improving risk assessments for insurers, investors, policymakers, asset managers, and others. Those models are also crucially helping societies better prepare and adapt to extreme weather and the changing global climate.

A somewhat cliché sustainability example these days is moving from spreadsheets to automated data and processes. But when you have hundreds of assets or more to manage, the value of automation, analytics, and more advanced AI technology enables better asset monitoring and predictive maintenance, improving operating efficiency, sustainability, and reliability with the ability to assess both assets and their surroundings.

A consumer goods company outlined how it integrates sustainable practices through its supply chain and procurement—needing new models, data, assessment efficiency, and innovative recommendations. Our broader procurement and supply chain research at HFS has, for some time (including at COP26, the UN climate summit in 2022), illustrated how transparent supplier assessments, incorporating sustainability metrics in buying decisions, and supply chain efficiencies are delivering distinct value now.

New supply chains, for example, in more transparent human rights-complying chocolate sourcing, scoping out new energy development projects, or producing sustainable aviation fuel (through non-traditional feedstocks), require finding new supplies and navigating those new networks flexibly. Visibility with non-established suppliers and risk management is vital. It is also essential to build a picture of, say, Scope 3 emissions and—more broadly—how to manage supply chains efficiently.

The Bottom Line: If we consistently focus on outcomes for the environment, society, and our economies—using the 17 UN Sustainable Development Goals as a guide—technology will find its best self for sustainability.

Many examples in this piece balance innovation for the now—improving existing systems—and for the future. Immediate proof of value enables sustainability and innovation teams to find the budget and support to go beyond reporting and deliver real business value while improving environmental and social outcomes with clear tie-ins to business goals and strategies. We cover this innovation balance in related research. The planet, society, and businesses—including their leaders—cannot afford to ignore the positive opportunities of technology. Especially not because the conversation was dominated by fear of AI’s energy consumption.