Essential Consideration : Harnessing the Power of Generative AI

#ai #designsystem

Intro:

To demystify the hype around generative AI and identify suitable use cases, I recently had the privilege of conducting three workshops with various user groups. Our goal was to evaluate common scenarios where data could be leveraged for decision-making and to assess the machine learning methodologies applicable to these use cases. The evaluation process was structured to first explain each use case, followed by a discussion on different themes. We then used Wooclap to vote and reach a consensus on the best approach for each use case.

Use case for discussion:

Use Case	Description
Forecasting / Prediction	Using historical data to predict future outcomes, trends, or behaviors.
Planning	Assisting in the creation of strategic plans by analyzing data and providing actionable insights.
Segmentation / Classification	Grouping data into categories for better analysis and decision-making.
Recommendation Systems	Suggesting products, services, or content to users based on their preferences and behaviors.
Content Generation	Creating text, images, or other media using AI algorithms.
Conversational AI	Enabling machines to interact with humans through natural language processing.
Knowledge Management	Organizing and retrieving information to improve decision-making and efficiency.
Decision Intelligence	Enhancing decision-making processes by integrating data, analytics, and AI techniques.

Methodology considered :

The working group in each workshop debated on how each of the below methodology would be effective to solve a specific use case

Concept	Description
Gen AI	Generative AI involves creating new content, such as text, images, or music, using AI algorithms.
Classical ML	Classical Machine Learning focuses on using algorithms to learn from data and make predictions or decisions.
Optimisation	Optimization involves finding the best solution from a set of possible solutions, often under constraints.
Simulation	Simulation is the process of creating a model to study the behavior and performance of a system.

Criteria for evaluation:

Theme	Dimension	Explanation
Value	Revenue	The potential of the use case to deliver additional funding to the organization through sale of new products and services, cost savings allocations, or grant funding that will support long-term growth.
Value	Efficiency	The potential of the use case to meet or exceed performance goals with less costs and improved service operations, resulting in reduced investment in current margin.
Value	Risk	The potential of the use case to cost or exceed current margins resulting in reduced investments in service operations.
Value	Nonfinancial Risk	The potential of the use case to assist the organization in meeting its nonfinancial mission-related goals: These goals can include environmental (E), social (S), governance (G), diversity equity and inclusion (DEI) sustainability; innovation; quality improvement.
Feasibility	Technical	The organization's ability to meet the technical requirements of a potential use case. Considerations include the core capabilities of the technology itself, the availability of vendor support, the current state of the organization's technology infrastructure, and the technical talent required by the use case.
Feasibility	Internal	The organization's ability and openness to use and incorporate potential use cases. This includes the willingness of internal stakeholders to understand, trust, and effectively execute these use cases.
Feasibility	External	The extent to which the environment outside of the organization is conducive to successful execution of potential use cases. This includes consideration of the legal and regulatory environment, public opinion regarding use cases, and digital access, literacy, and customer engagement by users.