How artificial intelligence can help the enterprise meet sustainability goals | HCLTech

How artificial intelligence can help the enterprise meet sustainability goals

As ESG ambitions grow for organizations, AI-driven ESG capabilities can help enterprises accelerate their sustainability journeys and meet stakeholder expectations
7 min. read
Jordan Smith
Jordan Smith
US Reporter, HCLTech
7 min. read
How artificial intelligence can help the enterprise meet sustainability goals

Sustainability practices have permeated the technology sector for some time now, as customers and stakeholders demand more from corporations and localities to establish rules and regulations to reduce humanity’s impact on the climate.

Although a very broad topic, sustainability practices from companies have evolved from focusing primarily on reducing carbon emissions to expanding into additional environmental, social and economic themes. Sustainability can be a key strategic technology initiative that enables environmental, social and governance (ESG) outcomes at scale.

A 2022 report from Gartner noted that sustainability frameworks are essential to accelerating digital transformation plans. It is important operationally for optimizing costs, energy performance and asset utilization.

As a data intensive area, ESG can utilize AI and the capabilities it brings to analyze large volumes of data and provide meaningful and actionable recommendations to meet ESG goals.

When to adopt ESG strategies

It’s never too late to adopt sustainability practices to meet ESG goals, but before doing so, an organization should consider the impact on immediate business goals as well as the legacy to be created.

Shyam Enjeti, Executive Vice President, Digital Business, HCLTech, explains that not every organization is on the same path for adoption and estimates that fewer than 10% of organizations are in the early ESG adoption category.

“These organizations have significantly evolved in analyzing the impact of climate risk on their business and are transforming their business models to stay relevant and also contribute to the larger goals that we have set ourselves,” he says.

The middle majority, Enjeti estimates, is about 50 to 60% of enterprises, and they have identified the material topics, the KPIs and sustainability-specific transformation initiatives for their ESG goals.

The remaining enterprises are still playing the waiting game before beginning the journey. They’re waiting for either regulations or reporting requirements for the countries in which they operate. Enjeti also suggests that they may be waiting for competition to adopt some of the sustainability initiatives to see how they would fare before beginning their own journeys.

How AI is helping the adoption journey

AI and data science can be invaluable for organizations in meeting their ESG goals. Recent advancements in AI, and the availability of open source AI that works on large language model-based techniques, are key to enterprises meeting their ESG ambitions.

To determine which AI tools to trust, Enjeti recommends conducting experiments with AI tools and then scaling those experiments.

“In an enterprise, you can’t just randomly adopt some of these tools—you have to experiment,” explains Enjeti. “You have to scale your experiments to ensure that you can rely on the insights that these AI tools actually provide and get to that point of being able to trust some of these tools.”

Through the adoption of AI tools, timeframes for meeting ESG goals can be reduced by as much as 20%, according to Enjeti.

How organizations can accelerate sustainability as business critical

While it is important to consider laws and regulations when accelerating sustainability’s position as a business-critical function, it is in the best interest of the enterprise and the consumers they serve to have a sustainability policy.

There is no single approach to creating frameworks for sustainability, but if an organization is able to create a governance framework with the right visibility from the top down, then sustainability becomes a large part of the business strategy.

“It kind of seeps into every part of the organization,” says Enjeti. “Then comes the cultural aspects, so you’ve got to foster sustainability as a culture, increase awareness through consistent training programs and augment an organization’s capabilities in the ESG space with an ecosystem of partners.”

Designing a sustainable enterprise

Read the report

Helping enterprises meet sustainability goals

HCLTech is committed to ensuring its customers have solutions to meet their sustainability goals with their ESG capabilities.

In Australia, HCLTech worked with a utilities company called Unity Water by leveraging AI capabilities to assist with their sustainability efforts.

“What we did for them was build a data platform and leveraged AI capabilities on top of it to create advanced analytical models, which helped them improve asset management, reduce energy consumption and proactively detect water leakages on the network by analyzing large volumes of data for anomaly detection,” says Enjeti.

In a different instance, HCLTech has helped Mexico City’s local government deploy solutions to help them with better governance to fight crime through deploying an edge-based solution. Essentially, all the traffic cameras in Mexico City have solutions built by HCLTech with AI capabilities and they’re able to detect simple things like fire, smoke or even weapons. Additionally, they detect any incidents that happen and analyze traffic patterns to reroute traffic, if need be.

“Mexico City has one of the most densely populated road networks and these solutions are possible today because of the use of AI,” adds Enjeti.

Additionally, HCLTech works with logistics companies to develop AI-driven ESG solutions and has developed a sustainable finance platform, Sustainable Finance 360, for enterprises in the financial services industry.

ESG is essential to helping enterprises align values with goals, but deploying AI-driven technologies to help meet ESG goals is essential to accelerating these efforts and creating value. By processing mountains of data, collecting and analyzing data with AI, a dramatic impact on meeting ESG goals at scale. 

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