Coming up with an AI strategy should be every CEO’s business. In the second session of the workshop on “Artificial Intelligence for Business Leaders: Driving for Growth, Innovation and Efficiency” with Dr. Mohanbir Sawhney, the Associate Dean for Digital Innovation at the Kellogg School of Management, Northwestern University, he discussed how businesses can leverage on AI and Generative AI. He indicated that, “AI changes the nature of work, the skills needed to perform the work, and the roles needed to infuse AI into the organization.” Thus, leaders need to build an AI-ready organization.
There are three questions every CEO needs to ask when it comes to AI:
- Where should we play?
- Where do we start?
- How do we play?
In Table 1, he shared key questions every executive needs to ask in developing a Generative AI strategy:
Source: Dr. Mohanbir Sawhney.
Leaders need to address the growing gap between leadership and AI understanding. They will have to be able to understand, coordinate, explain and defend any AI initiatives their company will be embarking on. Since AI will be reshaping the workplace, organizations will have to prepare their workers to be able to operate in this changing landscape. An effective AI and Generative AI strategy will need to have a collaboration between data scientists. IT, domain experts, and partner ecosystem. Asking the right questions will be crucial to designing this strategy: What are the problems we are trying to solve? How much data do we need? What technology do we need? How do we organize?
Deciding on where to focus should be the first step in choosing among the AI and Generative AI initiatives. Criteria needs to be developed in order to enable leaders to choose, prioritize and sequence projects. An AI Radar map (see Figure 1) could be utilized to map and evaluate use cases, enabling leaders to visualize how these initiatives can be used within the organization and provide information on projects that have the highest potential business impact. For businesses to see the maximum effect of Generative AI applications to the organization, Dr. Sawhney stated that, “Enterprises need to drive differentiated value from the training data used to finetune or customize AI models.”
There are two factors critical in this – domain specificity of the data set as well as the incremental impact on model quality resulting from the data set. Additionally, data richness can be assessed across key dimensions of the company’s value chain, namely customer data, operational data, administrative data, as well as risk data. Each dimension is measured using three vectors relating to potential sources and levels of data richness in the dimension. These are mapped in the AI Radar to provide a comprehensive view of data intensity to the organization, enabling leaders to determine which AI projects they should embark on.
Figure 1: The AI Radar
Source: Dr. Mohanbir Sawhney.
Incorporating AI and Generative AI into any business requires the involvement of the C-suite, strategic planning, prioritization of initiatives and collaboration among the different departments and stakeholders. Using the AI Radar can help define those priorities and help leadership look into specific use cases utilizing tools such as Gen AI Canvas.
