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Episode 102: AI Readiness: Why Most Companies Aren't Ready (And What To Do About It)

Written By: Hannah Rose

Jess Cardenas

The fact that I get to work to solve wicked difficult problems for clients (and sometimes internally) and collaborate with great team members and great clients to do so.

Chief of Staff

Published: Jan 29, 2025 6:21:57 PM

What does it mean for a company to be “AI ready?” Doug and Jess explore this question and how revenue operations teams should approach AI. They cover the opportunities and dangers of AI, as well as key areas like strategy, data, processes, people and technology that RevOps leaders need to consider when adopting AI.

Audio:


Video:


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Show Notes:

Editor's Note:

  • We have launched a YouTube channel for The RevOps Show where we'll be posting the video version and shorts from episodes. We'd really appreciate it if you took a minute to go and subscribe to our channel! 

Pre-Show Banter: 

  • It’s official. Doug has seen Bruce Springsteen 50 times in concert.
  • Doug is abandoning Jess and going on a much needed cruise to Aruba, Curacao and Bonaire.

Main Discussion Points: 

  • The dangers of treating AI like an “easy button” and letting it drive strategy rather than supporting it.
  • Assessing your company’s AI maturity across 5 levels: 
    • 1. Experimentation: Test, test, test!
    • 2. Isolated Usage
    • 3. Partially Synchronized: Part of the organization is using AI, not using part of the AI.
    • 4. Fully Synchronized: AI is connected across the organization.
    • 5. Integrated: AI is a core part of your operating system.
  • Making sure your data architecture and datasets are ready before diving deep into AI.
  • Using AI initially for “smart automation” to eliminate high effort, low value activities.
  • Developing the skills and culture needed to take advantage of AI investments.
  • Ensuring your tech stack is capable of supporting extensive AI usage.

Jess’s Takeaways: 

  • AI is a solution looking for a problem which is enabling folks to be able to easily fall into an “all i need is…” trap. It’s going to give you an answer no matter what, and it’s only as good as the data you give it.
  • You need to be thinking about the people who are going to lead the effort and take a combined horizontal and vertical approach to AI. This reminds Jess of Lift’s approach to implementations–having folks from different expertise leading the effort.
  • Remember the prime directive: You need to be driving AI; don’t let it drive you.
  • Don’t try to use AI as an easy button.

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