GenAI in Business: Strategies for Successful Execution
Master the "Act" phase of generative AI by building, launching, and scaling solutions with team management, experience optimization, and risk mitigation.
Master the "Act" phase of generative AI by building, launching, and scaling solutions with team management, experience optimization, and risk mitigation.
This course focuses on the "Act" phase of the "See, Plan, Act" framework in the Generative AI in Business series, guiding business professionals through a structured five-step process to build, launch, and scale generative AI solutions. Participants learn the Pilot-Optimize-Rollout (POR) process for bringing planned AI solutions to life and sustaining their impact over time. The course covers critical success factors including assembling and managing the right teams through "innovation pods," designing optimal user experiences, developing effective stakeholder communication strategies, and implementing robust performance tracking and risk management frameworks. Through practical examples and case studies, students gain actionable insights into overcoming common implementation challenges and maximizing the business value of their generative AI investments. This course empowers business leaders with the tools and knowledge needed to confidently execute generative AI initiatives and ensure their long-term success.
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What you'll learn
Implement a structured five-step process to build, launch, and scale generative AI solutions
Assemble and manage "innovation pods" with the right talent mix for AI implementation
Design optimal user experiences to maximize adoption of generative AI solutions
Develop effective communication strategies for different stakeholder groups
Track and quantify the business impact of generative AI implementations
Identify, assess, and mitigate risks unique to generative AI projects
Skills you'll gain
This course includes:
1.9 Hours PreRecorded video
1 assignment
Access on Mobile, Tablet, Desktop
Batch access
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Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
There are 4 modules in this course
This course provides a comprehensive framework for successfully executing generative AI projects in business settings. The curriculum follows the "Act" phase of the "See, Plan, Act" framework, focusing on implementation strategies. Students first learn the Pilot-Optimize-Rollout (POR) process - a structured approach to design, test, launch, and scale AI solutions. The course then explores three critical success factors: the People Factor (assembling and managing effective innovation pods); the Experience Factor (designing optimal user experiences and communication strategies); and the Oversight Factor (implementing performance tracking and risk management systems). Through case studies and practical examples, students learn to avoid common pitfalls and maximize the likelihood of successful generative AI implementation. The course emphasizes both technical and organizational considerations, preparing business professionals to lead AI transformation initiatives.
Efficient Process to Build and Launch your GenAI Solution
Module 1 · 1 Hours to complete
Maximizing Success Probability of Your GenAI Journey: The People Factor
Module 2 · 42 Minutes to complete
Maximizing Success Probability of Your GenAI Journey: The Experience Factor
Module 3 · 25 Minutes to complete
Maximizing Success Probability of Your GenAI Journey: The Oversight Factor
Module 4 · 1 Hours to complete
Fee Structure
Instructor
Pioneering Research in FinTech and Blockchain
Andrew Wu is a prominent researcher in fintech, specializing in blockchain, cryptocurrencies, and robo-advisors. He leverages machine learning and automated text analysis to examine large-scale, unstructured data, with his findings published in the Journal of Financial Economics and featured in op-eds for The Hill. Dr. Wu teaches courses on FinTech Innovations and Global Business Field Projects in FinTech, and he has conducted an Executive Education program on Smart Banking in the Age of FinTech for the Industrial and Commercial Bank of China. He earned his PhD in finance from the Wharton School at the University of Pennsylvania and holds a BA in mathematics and economics from Yale University.
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4.7 course rating
11 ratings
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