Kyndryl Q&A: Do AI Climate Tools Actually Exist?

AI is rapidly being adopted across industries, but its potential for sustainability is double edged due to its significant energy and cooling requirements.

Faith Taylor is the Senior Vice President of Global Corporate Citizenship and Sustainability Officer at Kyndryl. 

Her role has been to build, lead and drive its sustainability and ESG strategy, ensuring that it integrates responsible business practices and innovative solutions into our operations and client engagements. 

Faith shares her expertise with Sustainability Magazine. 

Where do you see AI's role in sustainability?

AI has immense potential to transform sustainability efforts by enabling smarter decision-making through data analytics, optimising resource use and driving efficiencies across industries. 

From predictive analytics for energy management to AI-powered climate modelling, technology is helping organisations reduce their environmental footprint. AI can process vast amounts of data to uncover insights that would be impossible or highly time-consuming for humans to analyse. It is also facilitating the transition to a circular economy by improving supply chain transparency and waste reduction strategies.

Generative AI, in particular, adds a new dimension. While this is an industry growth area, it can require substantial computational power and it also offers powerful capabilities to enhance decision-making, automate complex tasks and surface insights that drive more sustainable outcomes. When designed and operated with sustainability in mind - by measuring energy consumption baselines, optimising workloads, designing energy-efficient systems and sourcing cleaner energy - generative AI can unlock new efficiencies while mitigating its own energy use. We call this decarbonising growth. 

Last year, our Global Sustainability Barometer Study, which underscored AI’s growing impact in sustainability found that 55% of organisations believe AI will significantly affect their sustainability goals, yet many are not fully leveraging its capabilities beyond reporting and monitoring. This highlights the opportunity to scale AI-driven insights for more proactive, predictive decision-making. However, despite 80% of organisations acknowledging technology’s role in sustainability, only 32% feel they effectively harness its full potential. This signals a need for greater integration and adoption of AI-driven sustainability solutions.

Do the AI climate tools we need exist yet?

While many AI-powered climate tools exist today, we are still in the early stages of unlocking their full potential. We see advancements in AI-driven carbon accounting, emissions tracking and climate risk assessment tools. However, these tools must continue to evolve to provide more granular and accurate insights. A key challenge is ensuring the data they rely on is comprehensive, standardised and accessible to report externally. More collaboration is needed between policymakers, businesses and technology providers to refine these solutions and maximise their impact. 

Our data found that only 21% of organisations fully integrate technology to reduce their carbon footprints while advancing broader sustainability goals. Which suggests that while AI tools exist, they need to be better integrated into business processes to drive real impact. A significant opportunity lies in using AI for predictive analytics - while 61% of companies use AI to monitor energy consumption, only 34% leverage it to predict future energy use, underscoring the untapped potential of AI-driven insights.

Are industry-specific tools needed?

Absolutely - each industry has unique challenges and sustainability goals, requiring tailored AI solutions. For example, AI applications in manufacturing focus on optimising production efficiency and reducing waste, while in agriculture, AI is used for precision farming and soil health monitoring. In the financial sector, AI is helping with climate risk assessment and sustainable investment strategies. Industry-specific tools ensure that AI delivers targeted, actionable insights that align with sector-specific sustainability objectives. 

The ability to tailor AI tools to industry needs will be crucial in moving from measurement to action. Moreover, extending AI’s role beyond carbon emissions tracking to broader IT operations – such as procurement, management and disposal – can further drive sustainability impact across entire value chains.

What skills are needed to use AI to its maximum potential?

To harness AI effectively for sustainability, a combination of technical, analytical and strategic skills is essential. Organisations need professionals who understand AI algorithms, data science and machine learning. Equally important are domain expertise and sustainability knowledge to interpret AI-driven insights correctly. Additionally, skills in ethical AI governance and responsible data management are critical to ensure AI solutions are fair, unbiased and aligned with environmental and social priorities. Cross-functional collaboration between technologists, sustainability experts and business leaders is key to driving impactful AI adoption.

One of the biggest barriers to achieving meaningful sustainability action is alignment within organisations. While sustainability is a strategic priority, many companies struggle to integrate it fully with finance and technology. Only 24% of companies with long-standing sustainability initiatives have full alignment with finance and 44% with technology. Bridging this gap will be key to realising AI’s full potential in sustainability.

How do you see AI affecting sustainability in the future?

AI will play an increasingly vital role in achieving sustainability goals and adapting to climate risks. As AI models become more sophisticated, they will enable more precise climate predictions, optimise resource use in real time and help businesses transition to more sustainable practices. AI-driven automation will enhance operational efficiencies, while generative AI will contribute to innovative solutions for energy management, materials science and biodiversity conservation. However, to fully realise AI’s potential, organisations must ensure its deployment aligns with ethical and responsible principles, balancing technological advancement with environmental and social considerations.

Organisations that invest in AI-driven sustainability strategies will be better positioned to navigate the complexities of a changing climate while driving long-term business value. Moreover, AI’s role in assessing Scope 3 emissions like the supply chain, forecasting energy consumption and anticipating climate risks – such as natural disasters – will be pivotal in future sustainability initiatives.

Generative AI in particular could help automate the continual assessment of an organisation’s carbon footprint by parsing vast amounts of data in real time. But it also requires more energy for training and deployment than traditional models, making it essential to embed sustainability at every stage - from designing lighter, more efficient models to seeking cleaner energy sources for AI infrastructure.

AI is not a silver bullet, but when integrated effectively into sustainability strategies, it can be a powerful enabler of change.

Explore the latest edition of Sustainability Magazine and be part of the conversation at our global conference series, Sustainability LIVE. 

Discover all our upcoming events and secure your tickets today.

Sustainability Magazine is a BizClik brand