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
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