Operationalizing AI: A Collaborative Guide for Data Scientists and Business Leaders

Businesses face complex decisions daily regarding sourcing, production, inventory, staffing, sales, and budgeting for their products and services. These decisions rely heavily on forecasting and planning work that must incorporate not only historical data but also expert insights and emerging trends. Addressing these challenges requires an AI approach that goes beyond working with time series data. This includes distinguishing between statistically accurate and best (those that best serve the needs of the business) forecasts, AI explainability for trust and understanding, and usability for adoption. As an operational data scientist, you are pivotal to bridging technical expertise with business needs.

This framework will help guide a collaborative approach to operationalizing AI within your business, including how to:

• Engage business leaders
• Explore high-value use cases
• Present time series forecasting capabilities
• Ensure implementation readiness
• Evaluate platform and performance capabilities
• Document technical integration needs

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