CIO Best Practices

Checklist For Implementing Generative AI

Sometimes good initiatives stall. That might be the case with you and generative AI. Don’t let your interest get distracted. Use this checklist to open incredible opportunities for you and your team.

Scott Smeester


August 24, 2023

Photo credit:
Randy Fath

Sometimes good initiatives stall. That might be the case with you and generative AI. Don’t let your interest get distracted. Use this checklist to open incredible opportunities for you and your team.

Mom: Why did you fall out of bed?

Child: I stayed too close to where I got in.

Are you in bed with generative AI? If so, it’s possible you are in but not into it and still on the edge.

Crawl in there. Get comfortable. I’ve been talking with CIOs who are still wondering what to do. I created a checklist to help you introduce and immerse others into it.

Needs Assessment:

Identify the departments and roles that will benefit the most from understanding and using generative AI.

Gauge the current level of AI literacy within these teams.

Establish Clear Objectives:

Define what you want the teams to achieve by the end of the training. For example, understanding the basics of generative AI, being able to integrate AI tools into daily tasks, or even developing AI-based projects in-house.

Foundational Knowledge:

Begin with workshops on the basics of AI and Machine Learning. Understanding foundational concepts is crucial before diving into generative models. Coursera has some good classes to draw from.

Introduce the concept of generative models, with emphasis on their strengths, weaknesses, and typical applications.

Hands-on Training:

Collaborate with AI vendors or consultants to conduct hands-on sessions. These could involve using pre-trained models, fine-tuning them, or even training models from scratch.

Encourage the use of platforms like Google's TensorFlow, OpenAI's playground, or other cloud-based AI platforms that allow for experimentation without significant upfront infrastructure investment.

Real-world Projects:

Assign small projects or use cases relevant to your organization. These should be practical applications where generative AI can make a difference.

Monitor these projects closely, providing resources and expert assistance when necessary.

Ethics and Responsible Use:

Conduct sessions on the ethical implications of AI. This should cover data privacy, model biases, transparency, and the societal implications of AI decisions.

Establish clear guidelines and best practices for the responsible use of generative AI within your organization.

Continuous Learning:

AI is a rapidly evolving field. Ensure that teams have access to up-to-date resources, including online courses, webinars, workshops, and conferences.

Encourage participation in AI communities or forums for knowledge exchange.

Assessment and Feedback:

Periodically assess the teams' proficiency in generative AI to ensure the training is effective.

Gather feedback to improve future training sessions and to understand any additional support teams might need.

Infrastructure and Tools:

Invest in the necessary infrastructure to support AI initiatives. This might include high-performance computing clusters, cloud platforms, or specialized software.

Ensure teams have access to relevant tools, platforms, and APIs that enable them to harness the power of generative AI effectively.

Collaboration and Partnerships:

Consider partnerships with academic institutions, AI research groups, or industry consortia.

CIO Mastermind is available to talk with you about how to build learning communities within your department or organization to get the most out of Gen AI.

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