State of AI Product Management Report
Explore; critical AI PM skills. The key metrics to track AI-powered success. Expert AI insights on what the future holds.
Welcome to the State of AI Product Management Report 2023. In the last report we wanted to get a full lay of the land of AI product management; this year we’ve gone even bigger.👇
The field of AI and machine learning in product management is evolving rapidly, and, together with Flatfile, we’ve uncovered the current state of the industry.
We’ve taken a deep dive into everything from the tactics required to build effective AI products to the continued importance of quality data.
For this report we’ve once again surveyed product professionals from around the world, whether they’re currently working with AI or they’re close to it, to uncover as much as we can.
Check out a selection of those we surveyed:
What’s in the report?
In the following stat and insight-laden pages, you’ll find:
⬆️ How product orgs are really taking advantage of AI in 2023.
🔑 The key skills and responsibilities of successful AI product managers.
🔢 The critical metrics to track to ensure AI-powered product success.
🤔 The expert takes on ethics and building AI products responsibly.
🔮 What the future holds for AI product management?
And more…
And here’s a little taster of some of the findings:
The majority of our surveyed product pros (71%) cited the ability to solve and prioritize user problems as the most important responsibility for an AI PM in 2023.
Well over half (59%) placed data privacy concerns at the top of the challenges facing those in AI product management, with the lack of understanding about AI among stakeholders following very closely behind (58%).
71% agreed that ensuring AI systems are trained on diverse and representative data sets is critical for maintaining a level of responsibility in AI product development.
“...I worry that we require that PMs reach some technical bar when the reality is what PMs shouldn’t have to be that technical. You shouldn’t have to know how a transformer works to be able to have a good conversation with an engineer or research scientist about the tradeoffs of those systems. They should be customer-obsessed, managing the uncertainty for the team, and be great at decision facilitation. It doesn’t matter what technology is used, including machine learning...”
Chris Butler, Lead Product Manager at Google
Wanna know more? Of course you do! Explore everything we’ve uncovered on AI product management in 2023 by downloading your FREE copy now.
