Guide to Adoption of Generative AI for CXOs

CellStrat
2 min readJul 24, 2023

McKinsey reports that Generative AI has the potential and could add the equivalent of $2.6 trillion to $4.4 trillion of value.

CXOs have a critical role to play in capturing that value. However, we have had significant learnings from the past when new technologies emerged like, internet, social media and mobile how ever any significant value was harder to come by even with melee of experiments. Many of the lessons learned from those developments still apply, especially when it comes to getting past the pilot stage to reach scale.

Through conversations with dozens of executives at more than 50 companies including their own, McKinsey has identified nine-point action plan all CXOs can take to create value, orchestrate technology and data, scale solutions and manage risks for Generative AI:

1. Quickly decide how your company will use generative AI and make it easy for employees to access and understand the technology.

2. Explore new ways to improve productivity, growth, and business models using generative AI. Create a tool to estimate the costs and benefits of using generative AI.

3. Redesign how your technology team works, focusing on using generative AI in software development, reducing technical debt, and automating manual tasks in IT operations.

4. Use existing services or modify open-source generative AI models to create your own unique capabilities. Building and operating your own generative AI models can be very expensive often running into thousands to millions of dollars.

5. Update your company’s technology systems to work with generative AI models and integrate them with other AI and machine learning models, applications, and data sources.

6. Create a plan for managing and accessing high-quality data, including both structured and unstructured data sources.

7. Set up a team that includes people from different departments to oversee generative AI. This team will provide approved models to other teams when they need them.

8. Invest in training for key roles like software developers, data engineers, MLOps engineers, and security experts. Make sure the training is tailored to each role’s needs and expertise level.

9. Evaluate the new risks that come with using generative AI and put in place ongoing measures to manage and minimize those risks. This includes addressing concerns about models, data, and company policies.

(Src: McKinsey Article)

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