How to scale your AI use cases: A checklist
The business case for AI is realized when the application is scaled, not in the use cases of the pilot phase. Use the checklist below at the outset to ensure the transition...
Brain Circuits
Management mythbusters: The AI vs sustainability trade-off
AI and sustainability are transforming the business landscape, yet many organizations treat the two as separate mandates, led by separate teams pulling in different directions. Instead, they must integrate these forces, using five principles for a twin transformation.
Checklist
- Are we treating AI and sustainability as tech and compliance problems rather than strategic imperatives?
- Are our AI and sustainability teams siloed in opposite ends of the building, rarely sharing a coffee, let alone a strategy?
- Do the people leading digital innovation and those working in sustainability have different (and unaligned) incentives?
Unlocking the synergies
AI can help turn sustainability from a burden into a driver of efficiency, cost savings, and new business opportunities. Properly deployed, it can make sustainability efforts both smarter and more cost-effective. For example, it can:
- Operations
Minimize energy consumption and waste through real-time monitoring and automated control systems.
- Supply chains
Identify carbon-intensive nodes, model supply disruptions, and recommend greener sourcing and logistics alternatives.
- Product and service innovation
Make offerings smarter, enhance design choices, and simulate lifecycle impact, aligning development with sustainability goals and competitive positioning.
- Customer engagement
Personalize sustainability messaging, optimize incentives, and drive large-scale behavioral shifts.
Five principles for leading a twin transformation
- Anchor in ambition
AI can’t just be about efficiency. Sustainability can’t just be about compliance. What’s the bigger opportunity your company is pursuing? Define a shared ambition that transcends departments and KPIs.
- Break the silos
Create cross-functional teams that bring together AI, sustainability, operations, and commercial functions. Integration starts with collaboration, and accountability must be shared.
- Invest in literacy
Equip leaders and teams with a working understanding of both domains. This doesn’t mean everyone should become a data scientist or a sustainability officer, but everyone should know enough to connect the dots.
- Model the mindset
Senior leaders must demonstrate that this transformation matters. Celebrate experiments. Talk about failures. Reward cross-functional wins. Culture change starts at the top.
- Tell the story
Strategy alone won’t inspire. Build a narrative that links tech and sustainability to human impact on your customers, employees, and communities. Make it real, make it relatable, and repeat it often.
Key learning
Treating AI and sustainability as complementary levers, not competing priorities, will make you more adaptive, more resilient, and more trusted by your stakeholders – and well placed to respond to the next wave of disruption.
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