News in the Channel - issue #37

AI SUSTAINABILITY

established relationship with the buyers.” Adam notes that resellers have a responsibility to move the conversation beyond ‘what’s possible’ to ‘what’s appropriate’. “That means helping customers understand the real cost – environmental as well as financial – of AI adoption,” he says. “Advice should focus on proportionality: choosing tools that match the problem, setting clear success criteria, and avoiding AI for AI’s sake. Resellers should also be asking harder questions around data quality, governance and long-term sustainability, not just performance gains.” Jason says that to support ESG outcomes, resellers need to go beyond basic provisioning and lead the conversation around sustainable AI readiness. “This means educating clients on how to select scalable, modular infrastructure, reduce cooling inefficiencies, and build toward compliance with future regulation,” he says. “Above all, resellers must discourage retrofitting new AI workloads onto legacy systems. The cost may be invisible at first, but it grows quickly in energy waste, carbon emissions, and operational inefficiency. As ESG becomes a board-level priority, resellers that can link infrastructure strategy with sustainability outcomes will gain a competitive edge.” Richard agrees that resellers can help to educate customers on AI tools for emissions tracking and Scope 3 reporting. “They can also promote collaboration between vendors for supply chain transparency,” he adds. Resellers should also highlight ROI, he adds. “Show how AI can deliver predictable

regulators, investors, customers and employees alike. “ESG considerations won’t sit alongside AI strategy; they’ll become part of how AI decisions are evaluated in the first place,” he says. “Businesses that treat sustainability as a core design principle, rather than an afterthought, will be better placed to scale AI responsibly and retain trust over the long-term. “Ultimately, the question isn’t whether businesses should use AI, but how thoughtfully they deploy it. The same principles that underpin responsible ESG strategies, encompassing restraint, transparency and long-term thinking, must also guide AI adoption. “In data-driven sectors like marketing, this means using intelligence to reduce waste, instead of creating more; to respect audiences, instead of making them feel overwhelmed, and to design systems that are efficient. As AI continues to mature, the organisations that succeed will be those that treat sustainability and ethics as a stride towards innovation, as the forming framework that makes it sustainable from the offset.” Simon adds that we are at the start of a revolution in businesses taking accountability for AI’s energy use. “Increased mandatory reporting requirements on scope 3 emissions will bring the large scale energy use of AI into the spotlight,” he says. “Those benefiting from potentially increased profits aided by AI technology will ultimately have to be accountable for the environmental impacts caused.” Richard says that balancing AI’s energy demands with ESG commitments will become a central conversation across the tech channel. “The industry is optimistic but realistic – AI and ESG integration is still in early stages, but the potential for transformative impact is clear,” he says. “Over time, this will evolve from a niche discussion to a mainstream priority for vendors, partners, resellers and end clients alike.” n

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Ultimately, the question isn’t whether businesses should use AI, but how thoughtfully they deploy it. The same principles that underpin responsible

ESG strategies, encompassing restraint,

transparency and long-term thinking, must also guide AI adoption.”

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costs and help smaller businesses compete for ESG-compliant RFPs.”

Growing issue Adam says that as AI becomes more embedded in everyday business operations, scrutiny will increase from