IBM Consulting Q&A: How can AI be used for Sustainability?
AI is one of the most rapidly developing tools available. Making its way into company operations around the world, the technology has incredible potential – but how can we ensure its development is sustainable, as well as its use?
Oday joined IBM Consulting as the Global Sustainability Leader in August 2023, bringing extensive experience in scaling businesses and a background in management consulting. Before joining IBM, Oday was the Founder & CEO of Better All Round (BAR), a B-Corp certified, innovative, ESG-focused diversified fibre-based business. Under his leadership, BAR launched Ora Household Towel, a revolutionary product developed from initial concept to market within a year.
Prior to launching BAR, Oday worked for over 20 years as a management consultant, starting his career at KPMG before moving to Accenture, where he held various leadership roles. At Accenture, Oday served as Global Head of Media & Entertainment, Global Head of Business Consulting for Communications, Media & High Tech, and Global Go-to-Market Lead of Accenture's Analytics business.
Throughout his career, Oday has built strong teams and alliances while serving clients worldwide. In addition to his professional achievements, Oday has served as an advisor to several innovative start-ups and as a founding mentor for Henkel X.
Oday shares his expert insights with Sustainability Magazine.
How can organisations use AI to drive impact in sustainability?
AI can help organisations advance sustainability impact in a number of ways.
In particular, generative AI can help accelerate data-driven decision making by turning data into insights faster. This enables businesses to drive forward sustainability in meaningful ways including optimising production levels, minimising waste, promoting efficient energy consumption, and meeting regulatory and voluntary reporting requirements.
A great example of this is Wintershall Dea. As they transition from a leading gas and oil company to a leading gas and carbon management company, they recognise the importance of leveraging generative AI to overcome data silos and unlock the value of data across the enterprise.
In partnership with IBM, they’ve created Generative AI-based tools that enable faster and more accurate evaluation of potential Carbon Capture & Storage (CCS) sites, with the potential to speed up the evaluation process by up to 40%.
Can AI itself be sustainable?
While AI and generative AI are impressive technologies that can certainly bring benefits to both business and sustainability, it's essential to acknowledge that no path forward is without its challenges.
Like all computing, increased use of AI can lead to increased energy and water consumption. However, when used strategically, AI can offer solutions to stubborn sustainability challenges by providing valuable insights into environmental changes, assessing the environmental impact of business decisions, and empowering organisations to reduce their ecological footprint.
Fortunately, there are several ways to reap the benefits while minimising the environmental impact, and new ones are continually emerging.
What can be done to reduce the negative sustainable impact of AI?
Start by making smart choices about your AI model. One strategy is to utilise foundation models which can be fine-tuned for specific purposes but only require training once. For instance, IBM’s geospatial foundation model can be fine-tuned by organisations to use NASA data for their own purpose – whether that’s tracking deforestation, detecting GHGs, or predicting crop yields.
It’s also important to keep in mind model size – bigger isn’t always better. In fact, smaller models trained on high-quality, curated data can often achieve similar or even better results while being more energy-efficient.
Another important consideration is where you process your data. Co-locating your data next to your processing can lead to significant energy savings, and doing this in a data centre with available renewable energy sources can help reduce your carbon footprint even further.
Infrastructure behind your model also plays a critical role. Since up to 90% of a model's lifespan is spent in use, choosing the right chips and infrastructure can make a significant difference in an organisation’s energy consumption.
Prioritising transparency and open-source collaboration is important. By embracing open-source, we can tap into the ‘wisdom of crowds’, enabling us to pool collective expertise, resources and perspectives to develop better, more energy-efficient, and more sustainable AI solutions.
How do reporting guidelines and regulations impact AI?
Many companies face a number of regulations and reporting requirements, nationally, internationally, and sometimes even regionally.
AI impacts this in at least two ways. As a tool that is rapidly being adopted, it will contribute to companies’ overall impact and have to be accounted for in their sustainability reporting. However, AI can also be leveraged to make operations more efficient and significantly decrease the burden of the actual reporting.
According to a recent IBM Institute for Business Value study, spending on sustainability reporting exceeds spending on sustainability innovation by 43%. AI can help rebalance these dollars toward innovation, by streamlining data collection and enabling organisations to take more targeted actions that allow them to drive meaningful sustainability progress.
How is IBM helping organisations make progress on their sustainability initiatives?
IBM believes that everyone has a role to play in addressing today's environmental challenges. That's why we're committed to helping organisations develop and implement sustainable practices, as well as leveraging data-driven technologies to deliver positive environmental impact.
We work closely with companies to integrate sustainability into their decision-making processes, driving measurable improvements to operations, performance, and progress towards their sustainability goals.
By empowering organisations with AI and other technologies, we can help streamline reporting, mitigate climate-related risks, reduce carbon footprint and much more.
For instance, IBM Consulting and Hera SpA, a leading multi-utility in Italy, worked together to use AI to help minimise landfill waste. By leveraging AI to analyse video footage of incoming waste, Hera SpA was able to better identify the characteristics of items and materials that can be recovered and reused, achieving greater efficiency across 89 facilities and more sustainable outcomes.
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