Digital transformation is now a universal phenomenon across industries and cannot be viewed as a discretionary strategy; it must now be deemed essential if an organization expects to compete and survive. AI and sustainability are two areas of digital transformation that are increasingly intermingled. They significantly affect the manner in which companies design Environmental Social and Governance (ESG) frameworks, and how they approach decision-making and structure and assess long-term success.
AI had previously been implemented primarily for efficiency gains and enhancing short-term performance, but it is now believed that AI will allow companies to develop ESG considerations by embedding ESG concepts into their daily operations and decision-making practices. By using AI-enhanced analytics, predictive modelling, and optimization tools, companies will now be able to make better, more informed decisions about balancing short- term business performance with long-term environmental and social impacts.
Why AI and Sustainability Are Becoming Inseparable
Companies need to deal with the impacts of global climate change, scarce resources, and greater energy demand now that global companies are operating in a digital economy. However, the impact on the environment from technology usage and the energy it requires must be considered.
According to the International Energy Agency (IEA), over the last few years, global consumption of electricity in data centres has nearly doubled annually due, in part, to AI and other forms of data-intensive workloads. Additionally, Google's sustainability reports show that the amount of computing effort needed for very large scale applications of AI during both training and production will be substantial.
Nonetheless, AI will allow organisations to create tools to improve operational efficiencies, identify risks before they are realised, automate sustainable practices, and maximise the use of scarce resources across global supply chains. As a result, sustainability is becoming part of the fabric of corporate responsibility due to increased regulatory oversight from governments, investor demand for sustainable business practices, and an overall increase in consumer awareness.
Opportunities: How AI Accelerates Sustainable Transformation
AI enables organizations to identify and implement sustainable practices across operations, products, and supply chains.
- Using real-time data from AI Analytics allows companies the opportunity to monitor their usage of energy, identify any areas that might need improvement on the way that they're using that energy, and eliminate any waste associated with that energy usage. Google Cloud's AI Infrastructure research indicates that deploying intelligent techniques for optimizing workloads and predicting future energy needs helps lessen both the amount of wasted compute capacity as well as greenhouse gas emissions resulting from large-scale computing environments.
- Machine learning models enhance the efficiency of managing resources (e.g., inventory planning) and predicting demand by providing better predictions of inventory levels, thereby decreasing the chances of producing too much or having too much stock and consequently wasting materials as well as improving efficiency in operations.
- AI provides visibility into supply chains (through the use of machine learning to analyse sourcing, logistics and supplier performance data), enabling organisations to minimise their environmental impact due to transportation emissions, enhance their ability to make better procurement decisions and support more ethical and sustainable procurement practices.
- AI tools use satellite images, sensor data and other information to generate actionable insights on conservation of resources, monitoring of the climate and providing large-scale efficiencies for managing resources across multiple organisations.
- AI-driven automation reduces manual effort, streamlines workflows, minimizes redundancy, and improves productivity. As a result, organizations reduce energy consumption associated with inefficient processes.
Enterprise Case Study: AI-Driven Sustainability at Scale
Google DeepMind's collaboration with Google allows the implementation of AI through machine learning to optimize the operation of data centres. By implementing machine learning to optimize the cooling, Google was able to achieve:
- An estimated 40% less energy was used for cooling Data Centres with the help of real-time AI-based optimization.
- Approximately 15% more efficient in total energy for the Data Centres based on reduced energy use.
- The use of less carbon emissions for each workload without the addition of any new physical infrastructure.
This example illustrates that AI can aid in reducing the environmental impact of companies while simultaneously improving their ability to ensure reliability and performance at the enterprise level when it is deployed in a responsible manner.
Challenges: The Sustainability Cost of AI
Although AI has many positive effects, it poses sustainability to organizations.
High Energy Usage:
The training and implementation of large-scale AI models consume a tremendous amount of computing energy, which results in higher energy demand and increased greenhouse gas emissions.
Environmental Damage of Data Centres:
Artificial Intelligence (AI) Computing consumes massive amounts of electricity and uses significantly more water to cool down large data centres.
Ethical and Governance Issues:
Socially responsible AI must be developed in a manner that addresses privacy and data security issues, as well as the issues associated with AI's inherent biases, lack of transparency, and lack of accountability. These factors will directly impact the social sustainability of our society and trust in the public sector.
Difficulty in Measuring impact:
There are very few organisations that have a standardised means of measuring or quantifying the environmental or social impacts of their AI efforts, making it difficult to accurately assess the return on investment (ROI) of their sustainable AI initiatives.
Skill/infrastructure Gaps:
The adoption of sustainable AI will require developing certain skills and capabilities (cross- functional collaboration) as well as having a modernised infrastructure to support it, which many organisations are still in the process of developing.
How Clavrit Helps Organizations Align AI and Sustainability
Clavrit is an organization that works with its clients to develop AI-based solutions that enable businesses to balance innovation and environmental responsibility. Clavrit has expertise in AI, Machine Learning, Digital Engineering, Cloud Modernization, SAP, Salesforce, and
Enterprise Automation; therefore, they enable organizations to implement responsible and scalable solutions for the use of AI.
The support that Clavrit provides to organizations includes:
- Creating Efficient AI architectures that reduce unnecessary compute utilization.
- Using Data-Driven Analytics to optimize all aspects of Operations and Supply Chain.
- Using AI to Improve Productivity and Decrease Energy Use.
- Designing Scalable Cloud Solutions that align with Sustainability Goals.
- Providing Frameworks for Responsible Governance and Adoption of AI.
By aligning technology strategy with sustainability goals, Clavrit empowers organizations to build a Sustainable and Resilient Future-Ready Enterprise.
Conclusion
Sustainability is now one of the main themes driving developments in AI technology. There are many technical challenges related to sustainability, such as increased energy use, lack of governance for newly created AI systems, etc. However, AI provides additional opportunities for organizations to address global climate change through its ability to efficiently analyse large volumes of data to provide complete, real-time information about resource use.
The real benefit of value from AI depends on how we build, govern and deploy AI systems to create positive change for organizations. Organizations can utilize AI to create transformational changes responsibly by creating sound strategies for responsible technology relationships and partnerships. Clavrit helps organizations to adopt AI technologies responsibly so that they can build on these systems' capabilities for creating transformational change, creating accountability and creating sustainable change in the future.
