Finance leaders' action agenda for sustainability acceleration

Starting the journey of accelerating sustainability with artificial intelligence may be tricky, let alone puzzling at times.

AI can help finance leaders close the gap through compounding acceleration of productivity and efficiency gains, and faster innovation.

According to Ernst & Young, a key part of this will be the ability to arrive at insight more rapidly, and make faster and more responsible decisions, through Generative AI.

Realising this potential depends on taking a responsible, people-centered approach that builds confidence in AI and creates value for all.

This entails building confidence in the sustainable development and deployment of AI, taking a holistic approach to applying AI to sustainability challenges and augmenting people’s potential to make sustainable impact by democratising access to GenAI.

The following actions provide finance leaders with an agenda for beginning this journey of accelerating sustainability with AI:

1. Start: GenAI is mature enough to be applied to your sustainability challenges today. Waiting will only cause you to fall behind in your ambitions and your competitors and delay the compounding acceleration AI can bring to your sustainability initiatives.
2. Commit: The digital transformation of the last decade demonstrated the pitfalls of tinkering at the edges or maintaining siloed initiatives. Invest in GenAI, but also the culture change, mindset shift, new talent and upskilling to fully realise its value.
3. Co-create: Achieving change in complex natural, economic and technological systems requires broad-based collaboration with clients, business partners, government, civil society, academia and creatives. But to be effective and just, sustainability solutions must also be developed with the stakeholders most affected by them.
4. Include: Provide access to GenAI throughout the organisation to unlock the passion and creativity of your people for sustainability. Work to ensure that LLMs include diverse insights and life experiences.
5. Experiment: GenAI creates an ability to question and iterate more quickly. Leverage this capability to focus on developing better questions, trialing and learning rather than defining outcomes.
6. Innovate: Drive sustainable innovation by applying AI to automate low-value research tasks and leveraging its ability to process large amounts of data, freeing innovation teams to focus on ideation and complex problem-solving.
7. Govern: Center your AI initiatives on human values to build confidence internally and externally and realise sustainable outcomes.
8. Mitigate: Understand the risks inherent with probabilistic LLMs (e.g., bias, hallucinations) and build confidence with a risk management approach that encompasses the full model life cycle.
9. Report: Measure and report on the differential sustainability impact of AI initiatives. Assess your net impact with Scope 4 and other metrics.
10. Share: Be transparent about AI experiments and initiatives, their success or failure, and lessons learned.