Artificial intelligence has rapidly moved from experimentation to execution. But as AI adoption accelerates, a crucial question is emerging in boardrooms around the world: how do you scale AI without scaling energy consumption, operational costs and carbon emissions?

For many organisations, circularity starts and stops with recycling. It’s visible, easy to measure, and widely understood. But focusing only on what happens at the end of an asset’s life means missing the biggest opportunity: keeping technology in use for longer.

Sustainability has become one of the most powerful levers for profitability, resilience, and long-term organisational value. Senior leaders who recognise this shift are positioning their businesses to outperform competitors, attract stronger talent, and meet the rising expectations of customers, regulators, and investors.

COP30 in Belém, Brazil marked a turning point for climate action, elevating technology and AI as key drivers of sustainability. Discover how digital innovation, from emissions tracking to AI-powered resilience, is shaping the future of climate strategy and operational excellence.

COP30 was held in Brazil this year, with much attention focused on adaptation finance and forest protection but for the first time we saw the rise of technology and AI on the agenda.

A strong focus on people, planet and communities has driven several notable achievements, including carbon neutrality for Scope 1 and 2 emissions, more women in leadership positions and more under-represented groups reached through community STEM education programmes.

Logicalis CEO Bob Bailkoski is leading by example on sustainability, helping customers cut carbon and energy costs while driving internal carbon neutrality and community impact.

Explore how Logicalis tackles sustainability data challenges using IBM Envizi, blending ESG metrics with qualitative insights for meaningful impact.

Artificial intelligence has moved from the fringes of operational considerations to the forefront of operations. As organisations race to implement AI innovations, we all face a critical question, how do we reconcile the energy-intensive nature of AI with existing sustainability commitments?