How to build your 3-minute AI stories: Take a Boilerplate Approach
Here is a simple AI-SWITCH Boilerplate for building 3-minute AI stories:
- Problem definitions: What are the top 2-3 business problems that the AI initiatives are targeting to solve (pre)/ have solved (post)? How were these problems measured and compared to peer/ industry benchmarks?
- Strategy: What AI MVS (Minimum Viable Strategies) have been executed/ are planned, to complete these initiative successfully?
- Workforce: What MVT (Minimum Viable Talent) strategies/ human capital have been leveraged/ is required, to work on these initiatives? [Quick 1-liner Ref. to industry AI practice benchmarks if available]
- Information: What datasets have been used/ are required, to implement these usecases? What were/ are the data quality, volume, speed, relevance challenges if any, and how were/ are they handled?
- Technology: What partner tech-stacks and tools have been/ are planned to be used? In what model (Iaas, PaaS, SaaS, hybrid, multi)?
- Culture: What culture changes were/ are required to scale up adoption of these usecases in prod, post UAT and deployment? How are these org change levers executed/ planned for success?
- Human-AI augmentation: What % impact have been observed/ are expected out of the AI programs, on the key business metrics of the targeted problems (that were articulated at step 1)?