AI’s Power Paradox: Balance Innovation and Sustainability for a Promising Future

When I was CIO at a construction industry data, analytics, and media company, I was deeply interested in how technology and sustainability would drive the industry’s future. Could a new smart building technology or a green innovation lead to funding new construction that improves people’s experiences and enables a more sustainable future?  

One shining example back then was The Edge in Amsterdam, named the world’s smartest building that received a 98.4 BREEAM sustainability score. The Edge has a 14-story atrium, hot desking capabilities, and over 28,000 sensors to capture motion, light, temperature, humidity, and infrared. The Edge is still one of the top sustainable buildings in the world.

Let’s focus on our responsibilities as Digital Trailblazers – the world of technology, cloud, data centers AI, and IoT – its power utilization, water consumption, and carbon footprint.

The staggering ecological impacts of computation and the cloud reports, “The cloud now has a greater carbon footprint than the airline industry, and a single data center can consume the equivalent electricity of 50,000 homes.” Large data centers can consume between 1 and 5 million gallons of water daily, and 2% of US energy utilization is in data centers.

The problem: AI and LLMs require significant power

These are power, water, and carbon metrics captured at the dawn of the AI age, and the opportunity and hype around generative AI fuels intelligent experimentation while also serving as an invitation to indulge in a technological frenzy.

“Advances in AI, particularly in the realm of Large Language Models (LLMs), have caused a surge in carbon emissions from the tech industry,” says David Talby, CTO of John Snow Labs. “In fact, studies estimate that training a single AI model can emit as much carbon as five cars in its lifetime.

This recent article asking will responsible AI neutralize tech carbon footprint includes an even more alarming data point: “A more recent study by Google and the University of California, Berkeley, reported that training GPT-3 resulted in 552 metric tons of carbon emissions, equivalent to driving a passenger vehicle 1.24 million miles.”

Talby adds, “Sustainability is a key aspect of responsible AI, and aligning with standards like the CarbonNeutral Protocol helps companies offset their emissions and advance their tech without burdening the environment.”

 Read more about the CarbonNeutral Protocol and the World Economic Forum’s view on why we must care about responsible AI. You can also review declarations from Google, Microsoft, AWS, and Meta on their approaches to responsible AI.

Bottom line: Organizations should experiment with AI, but recognize both the economic costs and sustainability factors. When embarking on an AI experiment, are you considering the potential value, cost, and carbon impacts?

The goal: Target carbon neutrality

As digital transformation leaders, our discipline requires stating upfront goals and then reviewing how initiatives can address them.

“Many organizations are developing sustainability goals around environmental commitments like carbon neutrality, net zero, or hitting other greenhouse gas emission targets, according to Infosys’ ESG Radar,” says Sunil Senan, global head of data, analytics, and AI at Infosys. “To support sustainability through digital transformation, organizations should focus on artificial intelligence (AI), actionable data, and analytics to identify areas to measure, improve, and streamline processes and decisions that have a needle-moving impact on ESG achievements.”

The Infosys’ ESG Radar highlights several data points:

• 90% say ESG initiatives show positive financial returns, and 66% within three years
• 70% of companies are tracking carbon footprint
• 45% create ESG leaders as part of their organizational change strategy

That last data point suggests an opportunity for “Sustainability Digital Trailblazers!”

Senan continues, “Considering the recent AI boom, organizations can capitalize on its power to deliver time and cost saving insights that improve ESG outcomes and drive the organization’s bottom line.”

Bottom line: FinOps tools like Hybrid Cloud Management X, Persefoni, and  Microsoft Cloud for Sustainability can help companies measure carbon emissions, and many companies, such as Infosys, offer carbon management solutions.

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One solution: AI to improve resilience and sustainable energy solutions

One promising area is the application of AI and machine learning in energy, resiliency, and sustainability.

“Leveraging artificial intelligence and automation is a key component to ensure resilience and reliability across sustainable energy solutions,” says Vikhyat Chaudhry, CTO, COO and co-founder of Buzz Solutions. “Bolstering the power grid is essential for a grid that can support ongoing clean energy solutions necessary for the continued electrification of industries.”

Chaudhry continues, “AI can and should be used to spot risks and anomalies early on in the production, installation, and ongoing maintenance of clean energy and sustainable solutions. By training AI on data across a wide set of utilities or energy management systems, risks can be automatically spotted and addressed, preventing faults in the grid and potential disruptions to clean energy production.”

Other sustainability initiatives focus on consumption and emissions, and some of the biggest energy consumers state their commitments:

• At Amazon, 90% of the electricity consumed was attributable to renewable energy sources, and “we remain on a path to reach 100% by 2025—five years ahead of our original 2030 target.”
• Microsoft’s commitment to achieve zero carbon emissions and waste by 2030.
• Google’s commitment to replace 120% of the water it consumes.

Bottom line: Nearly all global companies disclose ESG information, including sustainability goals. They are top-down strategic objectives slowly getting on par with profitability and maximizing shareholder value. Executing these goals requires bottom-up execution, and Digital Trailblazers have the opportunity to direct their digital transformation, data science, and DevOps programs toward these objectives.

Some of my other articles on sustainability include five ways devops can reduce energy consumption and three ways CIOs can target sustainability goals in digital transformations.

Join us for a future session of Coffee with Digital Trailblazers, where we discuss topics for aspiring transformation leaders. If you enjoy my thought leadership, please sign up for the Driving Digital Newsletter and read all about my transformation stories in Digital Trailblazer.