A Comprehensive Approach to Addressing Business Priorities through AI and ML Roadmap

Case Study

A Comprehensive Approach to Addressing Business Priorities through AI and ML Roadmap

Business Objective

Our client, a leading provider of life insurance, annuity, and retirement services products, wanted to identify the key business priorities that could be appropriately addressed through the application of AI and ML use cases, to drive sustainable and measurable business value.

To address this, the client wanted to

  • Interact with business and analytics teams to understand key business priorities – Design a viable evaluation criteria playbook to prioritize the key business initiatives linked to business priorities
  • Identify AI and ML use cases that will help address the identified business initiatives and priorities through a detailed execution roadmap

Challenges

  • Lack of buy-in from the senior leadership team to leverage AI and ML to address business priorities
  • Lack of clarity on specific business priorities that can be addressed through AI and ML
  • Required managing expectations across business functions and dealing with conflicting priorities

Solution Methodology 

  • Identified two core business priorities by interviewing business stakeholders across business areas
    • Increase revenue from consumers and advisors
    • Increase digital adoption
  • Identified five relevant business initiatives that could help address key priorities
    • Improve cross-sell to existing customers and beneficiaries; Improve acquisition of new customers, Promote direct distribution, Increase digitization for consumers and advisors, Improve personalization based on customer lifetime value
  • Identified 50+ AI/ML use cases and prioritized 16 for execution that could efficiently and effectively address the identified business initiatives and priorities
    • Use cases were prioritized based on — alignment with the organization’s strategic goals, estimated dollar impact, data availability, availability of accelerators (both process and solution), change management effort, investments required in technology, and people

Business Impact

  • Estimated USD 500M to USD 750M impact in top line from the set of AI/ML use cases prioritized for execution
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