As the effects of climate change continue to intensify, enterprises are under increasing pressure to integrate sustainability into their core operations. For business leaders in Asia Pacific (Apac), the goal extends beyond compliance or reputation management — it is about embedding sustainability into the very DNA of the organisation.
Today, sustainability is becoming a fundamental pillar of brand value, business performance, employee engagement and responsible risk management.
But how can business leaders turn sustainability from a theoretical ideal into a tangible reality and do so while continuing to drive business performance?
A potential enabler might be AI and, importantly, in how the technology is applied across the enterprise.
The business case for sustainability
Historically, the rise of sustainability in business was largely driven by regulatory compliance. However, recent research reveals a more nuanced picture. A combination of ethical considerations, financial advantages and external pressures is driving the adoption of corporate environmental, social and governance (ESG) strategies.
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According to a study commissioned by IBM titled “Sustainability technology guide for executives”, only 25% of Apac organisations identify regulatory obligations as a key driver of sustainability practices, while 42% cite demand for sustainable products and services.
Other factors include demand from supply chain partners, employees, investors and insurers, as well as access to ESG-focused funding.
Despite these pressures, a significant gap remains between recognising the value of sustainability and embedding it into operations.
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The IBM study found that only 21% of Apac organisations have a truly strategic approach to sustainability. This gap presents an opportunity to gain a competitive advantage.
According to the “Beyond Checking the Box” study by the IBM Institute for Business Value (IBV) that I co-authored, organisations that deeply embed sustainability into their operations are 52% more likely to outperform their peers on profitability.
These organisations are also twice as likely to see significant reductions in operating costs and are 75% more likely to attribute substantial revenue growth to their sustainability efforts. These findings underscore the importance of viewing sustainability not just as a regulatory requirement but as a strategic imperative that can drive business transformation.
The role of AI AI leverages machine learning, predictive analytics and optimisation algorithms to help businesses make data-driven decisions that improve sustainability and performance KPIs.
Additionally, AI allows real-time monitoring of greenhouse gas (GHG) emissions and proactive emission reduction. Generative AI broadens these applications, aiding in energy optimisation, waste management and emissions monitoring.
AI can enhance the energy efficiency of enterprise operations and facilities, leading to cost and carbon savings. For example, IBM’s Global Real Estate team oversees 42 million sq ft of space in 600 locations across 100 countries.
We have implemented an AI-driven solution to optimise the heating and cooling systems in our buildings and facilities. This initiative has saved over 250,000 megawatt-hours (MWh) of energy since 2021 and lowered our energy expenses.
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Another notable instance is IBM’s partnership with steel and cement manufacturers in Asia to use AI to optimise their energy-intensive operations.
Steel production is notably energy- and carbon-intensive. By collaborating with one of India’s largest steel producers, we developed an AI-powered optimisation engine called the “process brain”. This innovation reduced the consumption of carbon-heavy coke by 3% and increased production yield by 15%, thereby reducing energy use, costs and carbon emissions without requiring substantial capital expenditure.
Physical asset efficiency
If we maintain our assets better, operate them more efficiently and extend their life spans, then we can save on materials, carbon and costs.
We collaborated with an Australian infrastructure services company to create an AI-powered asset management platform, cutting Scope 1 and 2 emissions by 50%, enhancing asset efficiency by 20% and boosting service reliability by 51%.
Similarly, Quezon City’s IT Department used the AI-driven IBM Maximo solution to streamline asset management and municipal operations, improving service delivery and promoting sustainable urban development.
Accelerating the energy transition
Renewable energy is crucial for achieving net-zero emissions. AI aids in integrating and optimising these systems by predicting output, managing storage and optimising distribution.
For instance, IBM partners with global utilities to enhance grid management using AI. A Brazilian utility improved forecasting accuracy by 30%, saving over US$3 million ($3.8 million) annually with AI-driven models. Similarly, an Australian utility improved medium-term forecast accuracy by over 20% and cut preparation time by 90%.
Emissions monitoring and reporting
We collaborate with enterprise clients to use satellite data for emissions detection, though resolution issues and time lags exist. AI bridges these gaps by analysing data from multiple satellites to identify patterns.
In an Australian gas utility pilot, we detected methane and propane leaks in pipelines, potentially reducing emissions and preventing revenue loss.
Partnering with Nasa, we created an AI model for earth sciences to ease accessing and searching satellite data. An open-source version is available on AI the community platform Hugging Face for public use.
Businesses’ carbon footprints extend beyond operations, with over 75% linked to their value chain. AI can sift through complex supply chain data to pinpoint carbon hotspots, helping businesses make sustainable sourcing choices and optimise logistics.
Overcoming barriers
While AI offers immense potential, realising its full benefits requires addressing certain challenges.
Firstly, the successful implementation of AI solutions requires access to high-quality data. As more businesses make sustainability a core part of their growth strategy, they are learning that timely and trusted data is the lifeblood of sustainability efforts.
AI accelerates the conversion of data into sustainability insights that help leaders make informed decisions in real time.
However, for maximum benefit to be derived from AI automation, sustainability data and metrics need to be embedded in operations, processes and workflows.
Secondly, a skilled workforce is essential to develop, maintain and interpret AI-generated insights. Governments and educational institutions need to invest in training programs to bridge the AI talent gap in the region.
Thirdly, ethical considerations surrounding AI inaccuracies, biases and data privacy need to be addressed. Businesses must ensure their AI solutions are developed and implemented responsibly, with proper governance and safeguards in place.
Finally, to maximise AI’s sustainability benefits, it is important to consider the efficiency and carbon footprint of AI solutions, not just their effectiveness. For example, IBM’s Granite foundation models are trained on industry-specific data, making them just as accurate but faster and more efficient than models that are three to five times larger.
In addition, AI itself can be optimised with tools like IBM’s Turbonomic, which enhances hybrid cloud performance and costs and AIready infrastructure, such as IBM’s Telum II processor.
With tools like these, sustainability can be embedded into all IT and business operations.
The urgency to act
We are running out of time. 2023 was the hottest year on record and 2024 is all set to beat this target. Midway through the decade we are not on track to meet our global net-zero objectives. Business leaders have the responsibility of building a sustainable future while driving business performance.
This is not easy. We need transformative business and economic models as well as exponential technologies. AI is one such technology that can help businesses drive both business performance and sustainability KPIs, provided it is used in a responsible manner.
Arun Biswas is managing partner, strategic sales and sustainability consulting at IBM Asia-Pacific
