The role of a product manager (PM) is changing. What was once a niche, engineering-adjacent position limited to shipping product and feature updates has evolved into a holistic function critical to business health. In the face of an economic downturn, business leaders are turning to PMs and the tools they use to drive better outcomes—including higher growth, lower churn, and reined-in costs.
And this is just what was changing before AI exploded onto the scene.
Product teams are wondering how their lives and work will change in the age of AI. With the impact of this transformative technology only beginning to be felt across the business world, no part of the product management voyage will be left untouched. Throughout each stage of product development, PMs will be able to embrace AI as a partner and execute like never before. What will it look like? Let’s take a high-level look at each phase of the product management lifecycle and how AI will transform it.
Phase 1: Discovery
A successful discovery process comes down to understanding pain points—both of users and of the greater market. This means asking the right questions—e.g., What are users’ top product and feature requests? What’s stopping users from achieving their goals?—and successfully synthesizing and analyzing the data to get the right answers.
With the right AI-powered tools, PMs will be better able to synthesize data from customer support, NPS, feedback, sales and support calls, product usage, and a host of other sources. AI tools will save PMs precious time by identifying patterns across multiple data sources. The analysis these tools will produce will come with actionable recommendations and evidence to justify the proposed investment(s).
Phase 2: Validate
There will always be multiple workable solutions to the problems or pain points you identify in the discovery phase. But which is the right solution—the one most likely to hit that sweet spot of maximizing customer both satisfaction and ROI for the business? This is where the validate phase comes in, and with the power of AI, PMs will be able to confidently decide what to build like never before.
To start, AI will make building product prototypes faster and easier than ever before. By providing prompts informed by customer and other data to an AI tool, PMs can quickly generate a prototype ready to validate. (You can ask an LLM such as GPT-4, for example, to write you better code with less explicit instructions.) What’s more, AI will enable PMs to test many such prototypes simultaneously, giving teams more time to work on building the right solution and increasing confidence before engineers build.
Phase 3: Build
Once the time comes to begin building a product or feature, it usually falls on the product manager to help put together the roadmap. Remember, a product manager sits at the intersection of engineering, customer success, marketing, and increasingly finance and sales, so there is no one in a better position to lay out the scope, work required, and end goals in order for all of the above to begin executing.
With AI, PMs can now incorporate testing of the product into that roadmap earlier. AI tools will be able to map their product’s codebase and quickly suggest how feature changes impact the overall product, saving precious time. This innovation will dramatically shorten the QA process, allowing the volume of releases to increase.
Phase 4: Launch
When a product is finally ready for release, it’s up to the PM to align sales and marketing efforts in order to maximize reach to the target customers and prospects. Working hand in hand with product marketing managers (PMMs), product managers normally provide crucial guidance on the timing of a launch, and how a product or feature should be positioned when it goes live. They also typically help decide which features to make paid vs. which should remain free, or what the paid cutoff for a feature should be in order to maximize conversion and retention.
With an assist from emerging AI tech, PMs will no longer manually define the timing of a release. Instead, products will undergo “smart” releases, with a controlled rollout of both the product/feature and the marketing promotional content tied to them based on usage and feedback from users. With this data-driven launch process, PMs will be able to monitor goals with auto-created dashboards and reports to track adoption and the impact on business outcomes (gained revenue, impact on churn, etc.)
AI will also enable product-led growth mechanisms to any product launch. AI-powered tools will be able to identify what new products or features make sense to highlight to individual users in their journey. It can then guide them towards the next step in their adoption journey and ensure they convert on the right paid products at the right time. The result will be increased conversion rates and greater product-led revenue.
Phase 5: Evaluate
A new product or feature rollout doesn’t end with a “go live.” In order to ensure continued success, PMs need to evaluate what’s resonating and working about a release vs. what isn’t. This requires analyzing product usage data, going through user feedback, and ascertaining whether support tickets are coming in tied to the release and if so, what’s generating them.
AI will radically optimize the evaluate phase by auto-determining what is and is not working about a new product and giving PMs recommendations on what to do next. The right AI-powered tools will also create dashboards for PMs to monitor and match up release performance with business outcomes and goals.
Phase 6: Iterate
Once they’ve evaluated a new product or feature launch, PMs will come back to the question of whether it generated the desired business outcome. If it didn’t (and even if it did), chances are they will be iterating to improve the product and achieve even better business results. Here AI will once again prove transformative, in all the ways mentioned above.
The AI revolution in business will accelerate a pre-exisitng trend in product teams. More and more, the PM of the future will be measured by business outcomes achieved rather than features shipped. AI will accelerate the product management process, and make product success increasingly synonymous with business success as a whole.
To learn more about the amazing ways product managers are inspiring and delighting users (including by leveraging AI), check out Pendo’s PLG Teardown video series.
