5 Critical Priorities for CIOs to Lead on Generative AI and ChatGPT

I recently shared recommendations with over 100 CEOs and Board of Director members on how they should prepare their businesses for the impacts of ChatGPT and Generative AI.

The Driving Digital Standup video embedded here has some background, including several ways I use ChatGPT today. I tell these executives, “Ignorance is not bliss” because of the major evolutions just over the last six months. In addition to GPT-4’s release, we’re learning every day about Microsoft Copilot, Google’s Bard, and Adobe’s Firefly, and I am certain of many more initiatives from big tech to come.

My recommendations for CIOs and Digital Trailblazers

For the last decade, I have been advising CIOs to establish digital transformation core competencies, drive data-driven organizations, and leverage hyperautomation. I believe generative AI will drive a new wave of customer and employee expectations, including the consumerization of search and disruptive changes to creativity and innovation – especially in marketing and software development.

Here are five critical priorities for CIOs:

1. Drive education and experimentation. How can employees use generative AI in their current workflows? What data, content, and other intellectual property should employees not expose to these generative AI tools? Focus on tactical workflow improvements, what Agarwal, Gans, and Goldfarb label as AI point solutions in their new book,  Power and Prediction.

2. Accelerate blue sky planning. It’s conceivable that many customer experiences and workflows will require radical reengineering over the next several years as integrated generative AIs, machine learning, and automation capabilities become embedded in more SaaS and enterprise platforms. CIOs should plan to facilitate brainstorming, update their vision statements, and review agile roadmaps at higher frequencies.

3. Pivot data governance to an offense strategy. Many data governance initiatives focus on defensive measures around policies, privacy, access rights, and security. These are all critical, but I help organizations consider proactive data governance practices that include developing data catalogs, documenting data dictionaries, and instituting governance in citizen data science programs. The opportunities around generative AI expand the scope – if I were to enable this capability inside the enterprise, how much of the organization’s content and data would be cleansed and readily accessible to support large language models and natural language queries?

4. Partner on ethics, brand risks, and legal. Even if your organization elects to be a laggard in using generative AI tools, many employees won’t wait for green lights or stop at red ones. How quickly can you provide employees with the guidance required to accelerate the desired experimentation while avoiding new risks?

5. Develop question-asking as a core skillset. Generative AI has enabled many more employees to accelerate their expertise by asking ChatGPT questions and prompting it to refine its answers. You’ll see several of my examples in the video and a shift in mindset. Instead of researching answers, I spend my time formulating the right questions. In some cases, I get useful answers; in others, I experience ChatGPT’s boundaries. Unfortunately, ChatGPT doesn’t reference its sources, an issue I hope and suspect they’ll address in newer versions.

Below is the Driving Digital Standup video, and I’d love to hear how you’re using ChatGPT and generative AI.