How can AI drive your company's ESG Goals?


At UST, our AI experts work at the cutting edge of technology and collaborate with top academic institutions like MIT Computer Science and Artificial Intelligence Lab (CSAIL) and Stanford AI Lab (SAIL) to accelerate innovation and the pace of change.


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As COP28 unfolds with this year's global discussions on climate change, it's evident that we're navigating the most pivotal decade for climate action. In this 21st-century landscape, businesses are intricately entwined with the three pillars of the ESG movement, and whether they realize it or not, they are on a path to sustainability.

According to a PWC survey of investors, 80% of respondents recognize the significant influence of ESG factors when making investment decisions. Changing expectations of consumers and investors are reshaping traditional business models and shifting focus toward sustainability in business practices.


AI and ESG

With AI being at the forefront of technological innovation, it is interesting to observe the intersection of AI and ESG and what it means for corporations and enterprises. The 2022 World Economic Forum underscored how digital technologies, including AI, are transforming environmental protection globally, such as tackling illegal fishing and protecting endangered species.

While AI can calculate ways to reduce environmental impact, it poses challenges as a significant energy consumer, creating a catch-22 situation. Especially for generative AI, concerns about the carbon footprint are growing, but since its inception, Gen AI has rapidly advanced in real-time applications, presenting infinite possibilities for meaningful change. It is vital for organizations to strategically align AI with ESG goals, supporting initiatives while being mindful of sustainability impacts. Balancing AI's boundless potential with sensible safeguards is the need of the hour if the potential benefits of the technology, particularly generative AI, have to outweigh the risks.

Before delving deeper into how technology can accelerate sustainability initiatives, let's look at the ESG factors and goals.


What are ESG goals, and why are they important

The cornerstone for evaluating a company's sustainability and ethical impact is ESG, encompassing environmental, social, and governance factors.

The "E" evaluates energy use, waste, and environmental impact, including carbon emissions, while "S" addresses relationships with employees, customers, and suppliers and ensures equity and diversity in an inclusive environment. "G" involves internal practices and controls for effective self-governance and legal compliance.

ESG goals are a company's commitment for the foreseeable future, such as achieving net zero emissions by 2040 or a particular number of hours committed to community service. Creating goals, setting targets, and reporting annual performance are fundamental to building trustworthiness and accountability for an organization or company. Aligning internal ESG goals with UN sustainable development goals can help establish a vital framework and provide guidance on how to go about if you're new to ESG reporting.

Let us focus on a few core sustainability areas and discuss how introducing AI can fast-track your company's ESG commitments.


How AI can help advance ESG goals

Sustainable supply chains

While almost no company on Earth can reinvent its entire logistics and energy infrastructure overnight, AI offers companies a powerful tool to accelerate their transformations. In a hyper-global world, supply chains are influenced by the intricate interplay of various stakeholders and systems that contribute to the multiple stages in the chain across planning, procurement, manufacturing, and logistics.

Business owners or organizations often don't have end-to-end visibility on the complex processes that shape the entire chain. Primary suppliers may subcontract parts of large orders for key functions like shipping or product assembly. Engaging with a host of third-party vendors that go beyond the immediate circle of the company poses a challenge in tracking sustainability measures such as indirect Scope 3 emissions, unethical sourcing, or human rights violations.

Technology can play a pivotal role in making supply chains sustainable. While technologies like blockchain and RFID are instrumental in improving traceability across the chain, AI can also be leveraged to infuse better predictability in order management that can streamline and reduce waste or emission-intensive processes. Also, algorithmic route optimization paired with intelligent truckload management systems can transform logistics toward better sustainability. These tools may be used to balance speed requirements or automate pick-up planning that optimizes delivery and reduces instances of unnecessary travel-generated emissions.

With AI and AI-based automation, enterprises can enforce better onboarding processes for new vendors through compliance checks and audits that can help evaluate various sustainability aspects, from using single-use plastics to employing child labor. These measures can ensure the integration of reputable partners into the organizational ecosystem who can share the same sustainability vision and commit to your company's ESG goals.

Waste management

The post-pandemic surge in online demand, particularly in fashion e-commerce, has substantially increased returned items, resulting in significant packaging waste and increased emissions. The reverse logistics process, responsible for 24 million metric tons of CO2 and almost 5 billion tons of landfill waste last year in the US alone, has become more pronounced with the heightened pace of online shopping during the COVID-19 pandemic.

Technology can offer a solution to the waste-intensive challenge of reverse logistics. AI-driven historical customer insights can predict return likelihood through cart assessment, and online retailers can provide smart insights to customers with suggested preferences. On the other hand, AR can mitigate excess orders by providing digital overlays for an immersive product evaluation before purchase.

Demand fluctuations can create problems of overstocking and oversupply, which undoubtedly contribute to huge amounts of waste generation. With predictive analytics, systems like Just-In-Time (JIT) fulfillment can be enhanced. Implementing AI for order prediction can streamline processes within the supply chain and better prepare business owners for surges in demand and supply bottlenecks.

In sectors like supermarkets, technology-driven solutions, such as automated markdown recommendations on perishable products, are vital in reducing food and product waste. Similar systems can benefit the apparel industry, where generating sell-through at the optimal price point is critical for waste cutbacks.

Social impact

As mental health continues to be a global concern, organizations must create better avenues for employees' emotional, physical, and mental well-being. AI-powered tools offer valuable support in this realm. Chatbot-based virtual mental health assistants are gaining popularity, and companies are spotting opportunities to incorporate them into their employee assistant programs. Trained on vast behavioral data sets, AI and ML algorithms of LLM-powered Gen AI tools can assess user needs, suggest the best course of action through conversations, and provide immediate alleviation and assistance for panic/anxiety cases. With smart and intuitive dashboards, employee well-being platforms can access better resources, and telehealth conferencing can be quickly facilitated. Again, automated surveys can check for holistic well-being or initial screening for better assignment of mental health professionals.

Additionally, AI proves instrumental in evaluating ethical standards and analyzing large-scale social data on aspects like gender diversity, equal pay, and safety standards within organizations. This pattern recognition contributes to the assurance of sustainable and ethical business practices.


While environmental and social aspects often take center stage in ESG considerations, it's crucial not to overlook the governance factor, which plays a pivotal role in value creation. Without strong governance and risk management, companies may even fail to operate. However, governance processes can be quite complex without proper structure and systems, especially for large companies and retailers who work with a network of partners and deliver to a host of clients.

Utilizing technology to establish a single source of truth, an AI-powered dashboard can benefit the monitoring process. Metrics that include various governance KPIs can be populated and tracked. Of course, such a dashboard would need to rely on robust data acquisition and management.

AI checks also prove valuable in measuring corruption and identifying malpractices, reinforcing the importance of governance in sustaining ethical and responsible business practices.


The future of AI for sustainable business

While the suggested solutions for incorporating AI in ESG projects may seem easier said than done, the reality is more complex. Implementing AI into ESG initiatives will come with challenges, even if your organization is on board from an investment perspective. Understanding the roadmap and having 100% buy-in from all stakeholders is important in setting the wheels in motion.

The use of AI should align with ESG goals, contributing to positive outcomes rather than causing harm to the environment and society. While the possibilities of AI are boundless, the risks are equally daunting. Companies must harness AI with caution and consciousness, identifying issues and minimizing self-perpetuating biases. Unchecked and unregulated use of AI can defeat the social purpose by increasing discrimination and widening inequality. Implementing assurance models and robust regulatory mechanisms is essential if we want a future co-existence with technology. A human-led innovation coupled with an empathy-first approach is key to ensuring that the benefits of AI and ML outweigh the risks.


What are your organization's ESG commitments, and can AI help advance them?

At UST, our AI experts work at the cutting edge of technology and collaborate with top academic institutions like MIT Computer Science and Artificial Intelligence Lab (CSAIL) and Stanford AI Lab (SAIL) to accelerate innovation and the pace of change. Our AI solutions help businesses solve challenges faster, reach their goals, and achieve sustainable growth. Learn more about AI-powered business transformation. Visit