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.
