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In this Strategies for Lowering Barriers to AI Use course, you’ll learn how to assess your organization’s AI readiness, develop a targeted AI strategy, manage change, and measure the success of AI initiatives. Adopting AI offers enormous potential, but organizations often face challenges related to infrastructure, workforce skills, and operational culture.
This course provides a comprehensive framework for understanding and overcoming these challenges. You’ll explore tools like the AI Maturity Model to evaluate readiness and the People, Process, and Technology model to identify gaps. Scenario planning will help you anticipate and manage change. Learn how to align AI projects with organizational goals, create a structured implementation plan, and set clear performance metrics. The course also covers strategies for creating a culture of innovation, providing hands-on training, and promoting ethical and responsible AI use. By the end of this course, you’ll have the knowledge and resources to drive sustainable, organization-wide AI adoption effectively.
You'll learn how to assess your organization's AI readiness, develop a targeted AI strategy, manage change, and measure the success of AI initiatives. It covers tools like the AI Maturity Model and the People, Process, and Technology model, scenario planning, implementation planning, performance metrics, building a culture of innovation, hands-on training, and ethical AI use.
It is suited to those responsible for driving sustainable, organization-wide AI adoption, helping them overcome challenges related to infrastructure, workforce skills, and operational culture.
You'll build skills in Artificial Intelligence Systems, Change Management, and Performance Metrics.
Lessons include an Introduction, Developing an AI Strategy, Managing Change and Uncertainty, Investing in AI Education and Training, Leveraging AI Tools and Platforms, and Measuring and Communicating AI Success, along with Test Your Knowledge checkpoints.
The course teaches you to identify key performance indicators and set clear performance metrics to measure and communicate AI success.