Last month, we spoke to a panel of expert product managers who have successully implemented AI solutions in their organizations. This post recaps some of the key strategies and insights they shared.

AI has been on the minds of many leaders these days. The prevailing assumption is that if you are not innovating with AI, you are going to be left behind. For the companies who are new to AI, the first instinct may be to get immersed in its complexities in order to build successful products. But our panelists make the case that even with this disruptive technology, fundamentals are more important than ever.

We had the pleasure of hearing from the following experts:

• Evelyn Chou: Senior PM, insightsoftware
• Jessica Hall: Author, The Product Mindset
• Sebastian Sobolev: VP of Product Development
• Max Gabriel: CEO, AX Intelligence and Managing Partner, G&T Partners

Here is a recap of the discussion. Here is the link to the video if you would like to watch the replay.

AI Product Strategy

Sebastian posited that AI Strategy is not separate from product strategy. Regardless of whether the ways and means (technology used) change over time, the ends remain the same (business outcomes). Keeping the ends in mind helps the business focus on figuring out how to solve the problem rather than chasing after the latest shiny object. Evelyn and Jessica stressed the importance of taking costs into consideration as part of the strategy. Evelyn stated that businesses should use AI after having exhausted traditional software engineering or other cheaper means due to the higher costs associated with AI. Evelyn said that while customers may be impressed by AI products but are not necessarily willing to fork over the money to purchase them.

On the “build versus buy” topic, Max pointed out that the obsolescence cycle of AI models is very short and so businesses need to take that into consideration. He also observed that executives tend to fall into two ends of the spectrum, i.e, hyper-reactive FOMO or passive indifference and suggested that work needs to be done to get them closer to the middle so they can be more measured in their approach.

In the current high interest rate climate, Jessica stated that many companies are making fewer strategic bets and are using revenue to fund AI projects instead of securing funding from outside sources.

In the discussion around AI native companies versus incumbents, Sebastian pointed out that incumbents have experience and data under their belt and as long as they leverage this edge and adapt, they will continue to have an advantage over newer players in the market.

Use Cases

Jessica took a cue from Andrew Ng’s AI playbook and said that companies can test out pilots to get a feel for AI but should not start before they figure out a baseline measure of performance that answers the question: is it useful? Expanding on that, Evelyn stated that she sees AI agents as being part of an automated workflow as opposed to a human being putting instructions into ChatGPT and getting a response. She stressed, however, that AI will not replace creativity.

Red Flags

Jessica said she does not trust anyone who does not hedge, who makes the claim that it is easy to solve a customer’s problem with AI. Sebastian noted the importance of data governance and does not trust any company that does not have a data governance strategy in place. Max does not believe anyone who says they are AI expert consultants who can solve an organization’s AI problem.

State of AI in 2030

Looking to the future, Jessica predicted that we would look back at this point in time and say that what we’re using today is the worst it ever is, drawing a parallel to the iPhone when it was first introduced in the market. Max expected AI to be ubiquitous and in the hands of everyone. These days we say there is an app for everything, in the future we will say there is an AI agent for everything. Building on Max’s comments, Evelyn stated that AI agents will develop the ability to predict ahead of time what we need based on our previous interactions as opposed to us opening up a console to ask the AI questions every single time. Sebastian used this opportunity to highlight that despite all the disruption, what will not change is the need for a product manager to keep their stakeholders in the problem space rather than the solution space, i.e., get them to articulate their use case rather than focusing on the technical solution.

Career Advice

Evelyn favors learning by doing as opposed to getting the latest certification. Jessica stated that people should focus on building their brand, communicating their value, and developing their network.

What AI features excite them the most

When asked what AI features excite them the most, Jessica mentioned drug discovery applications. She added that there are a lot of opportunities in many areas such as DevOps where AI can be used to manage costs and to speed up deployments. Sebastian quipped that he would love to have AI create slide decks for him. Evelyn took it one step further and is excited about the product that she is building that will streamline board meetings and quaterly business reviews, which includes creating the slides and cleaning up the data. Max is excited about agents, including the product that his team built that summarized a dashboard that saved 30 minutes of time by removing the need to answer rudimentary questions.

Final Thoughts

• Jessica: Get in there and play. Lead from strategy. Work on storytelling and influence.
• Max: Maximize productivity - think about productivity carefully and intentionally. Many technologists have failed on the faster and cheaper promise.
• Sebastian: It’s a great time to be a product manager. Focus on the fundamentals: the business outcome, the client outcome.
• Evelyn: It’s back to the first principles - data quality and security and focus on the customer.

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