Lessons in Building AI for Retail Marketing: From Development to Deployment | 7-Eleven & Home Depot

During this discussion, the panelists will touch upon their successes, failures, tips & tricks from both a technical and business perspective on how to develop, deploy and strategize the implementation of AI.

Topics explored include:

- Strategy; how to best build AI to accurately solve business problems/needs
- Why AI projects fail, how we can overcome these common challenges
- Data: labeling, data science, sources
- Experiences/Challenges in managing data flows, pipelines
- Experiences/Challenges in managing knowledge flows: building cross-functional teams/ documenting work from a technical perspective
- Building teams & managing workflows from a managerial strategy/innovation perspective
- Holistic picture of the dev/deploy lifecycle/workflow & matching this to business needs
- The practicalities of implementing AI solutions
- Matching strategy to end goals & monitoring success
- Reproducibility of results, model accuracy
- AI/ML at scale
- Responsible/Ethical AI - strategies, design, accountability, explainability
- Building & deploying AI to foster customer engagement with the end product/service