AI use cases for sustainability
Here’s a note from Nawar Alsaadi:
This radar infographic from Gartner is good conceptual framework for the different corporate applications of AI in a sustainability context.
First, Gartner divides AI applications in two broad categories:
– Everyday AI is focused on helping organizations drive environmental sustainability more efficiently. Technology for this type of AI can essentially be purchased “off the shelf.” It leverages the work of large models already trained on public data. Currently, the everyday AI side of the radar is where 80% of organizations play.
– Game-changing AI drives deep environmental sustainability changes to products/services and how an organization operates. Game-changing AI comes at a figurative and financial cost. It typically requires sophisticated AI technologies and custom models that need to be trained on large, tailored sets of proprietary and public data.
Second, they split AI usage into two broad groups:
– External customer-facing operations: The upper two opportunity zones of the AI opportunity radar are where AI is used directly in customer interactions or embedded in the environmental sustainability products and services sold to customers.
– Internal operations: The lower two opportunity zones of the AI opportunity radar represent organizations that infuse their internal operations and core capabilities with AI. Here, AI is used behind the scenes by employees.
The totality of the above leads to the creation of four quadrants within the attached infographic, or radar as they call it.
Implementing AI in your organization entails a good strategic understanding of the short and long term implications of AI use within these different quadrants, and where do you see the most attractive use case or opportunity set. This same applies for sustainability solutions providers building AI tools for corporate clients; understanding how and where your AI solution fits within this framework will help you better appreciate the operational and strategic value of your solution.
Finally, and still according to Gartner, those thinking of implementing AI for sustainability purposes, they need to think about three types of feasibility (solutions at the core of the chart are more feasible):
1. Technical feasibility: The organization’s ability to obtain and implement AI for environmental sustainability
2. Internal readiness: The organization’s ability and openness to utilize and incorporate the use case for sustainability
3. External readiness: The extent to which customers/partners and any external parties are accepting of the use case for sustainabilityWhether you like or dislike AI, whether you think it will help or distract from sustainability, AI will likely become an integral part of our personal and professional life. As such, thinking through the personal and professional use case for AI would be a smart use of your time.