Intelligent Transport Greener Future 2025

Three approaches to adopting AI FIGURE 6 Deploying AI for decarbonization clearly involves costs, but the benefits of proactive action could outweigh these expenses in the long run. For instance, prioritizing decarbonization could maintain investor confidence and improve financial stability. Equally, tightening regulation will increase the costs of GHG emissions. For example, given that the annual cap on EU carbon allowances (EUAs) – which allow companies to emit a certain amount of CO2e under the Emissions Trading System (ETS) – will tighten towards 2030, pushing the projected price per tonne over €150, early investment could mitigate future costs.34 However, when looking at AI solutions, companies will have to factor in the carbon emissions associated with using AI itself, as the technology requires large data centres that require huge amounts of energy. Training an LLM can emit around 284,000 kg of CO2 – as much carbon as five cars emit in their lifetimes.35 It is important for leaders to implement AI responsibly to maximize its impact on sustainability. Globally, there has been a significant push from large technology companies to decarbonize AI operations. For example, Google has set a target of operating 24/7 on carbon-free energy by 203036 and Microsoft intends to have 100% of its electricity consumption matched by zero-carbon energy purchases by 2030.37 So the deployment of AI to reduce emissions must be evaluated against its cost and impact to ensure it makes the most sense for any given application. Companies across the freight logistics ecosystem could consider the actions summarized in Table 2 to kickstart or accelerate adoption of AI in support of their decarbonization goals.Taker Shaper Maker Integrate commercial off-the-shelf AI/ML solution into workflows as-is, with little to no customizationAugment existing AI/ML models for specific geographic, sector and business case needs, leveraging proprietary data and insightsDevelop a new foundational model from scratch, tailored to the organization Source: McKinsey & Company. Intelligent Transport, Greener Future: AI as a Catalyst to Decarbonize Global Logistics 24