Green Computing: How to Merge AI and ESG Goals
Written by Joe Slade
Joe is a writer, engineer and technologist who specializes in translating intricate IT concepts into accessible narratives. His expertise spans from SaaS and cybersecurity to machine learning and AI. As a contributor aligned with Tech Journal’s ethos, Joe bridges the gap between innovation and understanding for IT pros.
ContributorsJuan Orlandini, Carm Taglienti
Increased Environmental, Social and Governance (ESG) regulations and reporting requirements are ratcheting pressure on business leaders to adapt — or face the consequences. From increasing sustainability demands to rising calls from stakeholders who prioritize environmental responsibility, the commitment to green computing is more than just a “feel good” story; it’s a critical, strategic imperative.
As organizations face increasing pressure to reduce their carbon footprints, AI integration offers a promising avenue to enhance energy efficiency, measure progress and advance your ESG commitments.
In fact, integrating AI is a crucial step in the process. That’s because AI-driven solutions can analyze vast amounts of data to monitor and report on ESG metrics effectively — a historically challenging, if not elusive part of ESG progress. With AI, leaders gain exhaustive insights needed to make informed decisions.
IT departments that stay ahead of the curve by adopting AI tools not only enhance business operations and ensure regulatory compliance. They also position themselves as leaders in sustainable business practices — ready to meet the future demands of a greener economy.
AI’s power demand creates a sustainability challenge — but there’s a solution.
AI and generative AI have ushered in a booming tech-fueled renaissance, driving innovation across all industries and technology skill levels. However, this progress comes at a cost.
AI workloads demand substantial computational power, leading to high energy consumption and a significant environmental footprint. As innovation-minded enterprises strive to harness and wield the power of AI, they must also confront the sustainability challenge it poses.
“There’s a lot of conversations around how AI is actually counter to ESG because training models for AI and doing inferencing for models on AI does require these very resource-intensive GPUs and compute and power,” says Insight CTO Juan Orlandini.
Planting the seed: Distinguished Technologist Carm Taglienti explains how different, thoughtful approaches, models, techniques and devices can help reduce the carbon footprint and power consumption of AI.
But the conversation doesn’t end there. “There’s a huge amount of work that’s being done by the industry on how to accelerate the inferencing side of the house. Organizations should start preparing for ESG. The industry as a whole is working very diligently to make sure that we can bring this to market. And we’re working very closely with all of them,” says Orlandini.
The fusion of AI with ESG goals is not just a trend — it’s a transformative shift in the IT landscape. Green computing has become synonymous with smart computing, where AI’s capacity for self-sustainability matches its capacity for innovation.
Green computing, also known as sustainable computing, is the environmentally-responsible use of computers and their resources. This concept extends beyond energy efficiency to encompass a comprehensive approach to minimizing the environmental impact of technology throughout its lifecycle. From design and manufacturing to daily use and eventual disposal, green computing practices strive to conserve energy, reduce waste, reduce plastic through bulk packaging and use materials that are less harmful to the environment.
Ultimately, green computing works to create a sustainable technological ecosystem that meets current computing needs and does so in a way that is mindful of future environmental impacts. By integrating principles of sustainability into IT practices, businesses can accelerate their journey toward a brighter, more sustainable future.
On-device AI is quickly gaining momentum as a viable solution to the sustainability challenge of AI’s power demands. By processing data locally on the device itself, on-device AI significantly reduces the need for constant cloud connectivity, thereby decreasing energy consumption and reliance on data centers. It also comes with the added bonus of data privacy and security since data is stored and processed locally.
Orlandini notes another key sustainability benefit of on-device AI. “The next year or two, we’re going to see devices that have 30, 40 hours of battery life. If you have a large fleet of devices, think of what you’re doing for the environment by having that much longer life device that doesn’t have to be plugged into a main power line almost all the time.”
On-device AI leverages the power of modern processors and edge computing to bring intelligent capabilities directly to users’ fingertips, all while operating within a more sustainable framework.
Just imagine the localized processing of countless AI tasks leading the way to huge reductions in the carbon emissions associated with data transmission and storage. This approach not only positions companies as leaders in responsible computing but also sets a precedent for the future of green technology in the AI era.
In addition to longer battery life, Orlandini expects a longer lifespan for the next generation of PCs. “The device makers are being more intentional in making their devices repairable,” he says. “You can repair it, upgrade it, do all those things so that it has a longer life. And because they are so capable with the AI, they’re probably going to last longer.” For ESG goals, this means less e-waste.
Insight’s dedication to ESG principles is evident not only in internal operations but also through strategic partnerships. Collaborating with over 8,000 technology providers, Insight leverages these relationships to promote sustainable practices across the tech industry.
Partners such as Cisco, IBM, Lenovo and others host circular economy sustainability advisory groups, which, together with Insight, address energy efficiencies, product attributes and lifecycle management opportunities.
These initiatives do more than just help reduce the environmental impact of technology; they also support clients in achieving their own ESG goals. In fact, Insight helped the Walthamstow School for Girls lower their IT costs by two-thirds and achieve their goals for sustainable recycling through participation in the Brighter Futures trade-in program.
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Device as a Service (DaaS) is an efficient, cost-effective approach to IT management that aligns perfectly with sustainability goals. This model enables businesses to lease devices rather than purchase them outright and gain regular refresh cycles while also reducing electronic waste.
The “Service” aspect is key, as DaaS helps IT teams realize cost optimization and efficiencies by providing technology on an “as a Service” basis.
Sustainability and ESG benefits include:
alignment with progressive sustainability and ESG goals
direct access to ESG-compliant device refurbishment and reuse programs
support for the circular economy and e-waste reduction initiatives
DaaS adoption allows organizations to accelerate their sustainability journey by providing all the benefits of a full technology lifecycle service delivered by trusted partners.
As a Solutions Integrator, Insight is in a unique position to recycle and reuse hardware. We focus our programs to ensure clients and the community get the most out of technology and that it’s disposed of responsibly.Our asset disposition services ensure:
EPA- and RCRA-compliant e-waste disposal
Maximized return on remarketable assets
Simplified logistics and transportation
Auditable chain of custody for disposed assets
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Assessment of current IT infrastructure: Identify areas where AI can contribute to sustainability goals.
Partnering with aligned technology providers: Collaborations with partners that share a commitment to sustainability can lead to innovative solutions that benefit both the environment and the bottom line.
Engaging stakeholders: All parties must understand AI-driven ESG initiatives and be committed to their implementation.
Committing to continuous improvement: As technology evolves, so should your approaches to green computing. This means staying informed about the latest AI developments and being willing to adopt new practices that can further ESG objectives.
If you’re ready to integrate AI into your ESG framework, strategic planning is a must. This strategic approach should include:
Following these strategies, sustainability-oriented businesses can navigate the green computing landscape effectively, ensuring that their use of AI not only drives innovation but also upholds their ESG commitments.
Take your sustainability ambitions further, faster.Insight partners with the world’s most sustainable and responsible companies to help organizations like yours see and surpass ESG requirements.
