Have there been any changes in AI-hype among your closest collaborators that have led you to re-evaluate AI-centered investments for data and analytics this year?

38 views3 Comments

Sort By:

Oldest

President & Chief Data Officer in Services (non-Government)6 months ago

There's been a lot of focus on the technical aspects like prompt engineering versus fine tuning, but not enough on how to actually leverage AI to create value. The focus seems to be more on proving that we've used AI, rather than proving that we've gotten value out of it. From what I've seen, the value creation side of AI has been more on automation. While there's a lot of potential and promise around automation, there's also a lack of discipline in understanding when and how it should be used.

I think we are in the disillusionment stage. I feel like the hype around generative AI has overshadowed the power of traditional analytics and machine learning models.

Partner / Principal in Services (non-Government)6 months ago

We're seeing a lot of AI fatigue due to the sheer amount of conversations around it. Initially, there was a lot of focus on use cases, but this distracted from the conversation about the value and benefits of AI. Now, we're seeing a pivot towards thinking about broader enterprise strategy and readiness around AI, especially generative AI.

There are three themes emerging from this.

There's a focus on data - do organizations have the right data to scale AI across different value chain areas?

There's a focus on organization - how can we upskill people to understand and use these tools?

There's a focus on responsible AI and governance - how can we protect our enterprise as we experiment with these tools? These are the emerging themes starting out.

Please join or sign in to view more content.

By joining the Peer Community, you'll get:

Peer Discussions and Polls
One-Minute Insights
Connect with like-minded individuals

Chief Data Officer in Travel and Hospitality6 months ago

In my experience, the hype cycles around AI have been quite fast. Initially, there was a lot of confusion about what generative AI is, with many fearing it would take over the world. However, it seems that most of our clients have moved past that stage and have a better understanding of what AI is.

We've also seen a shift in focus towards what we call "accelerators" - helper applications within platforms like Microsoft that assist in tasks like Copilot-type capabilities. However, the other side of the coin, using generative AI on personal data for tasks like reviewing policies and making recommendations, requires more discipline and many companies are realizing they're not ready for that due to the data work required.