The Product Manager’s Survival Guide: Embracing AI as Your Smart Intern
AI is not coming for your job… but maybe for your Jira board! There has been SO much written lately about the “end of the… <insert product manager and other product trifecta roles here>” that it has become a cliche. 87% of these articles are eye-roll-inducing clickbait. 12% are people working through their anxiety by way of speculation (I don’t blame them). And the remaining 1%? I’d like to think that includes articles like mine — the radical practical that helps drive the conversation forward in a productive way.
You can decide for yourself, though, if this article falls into the 12% or the 1%. And in full transparency, those seemingly precise percentages are my guestimates and not scientifically derived. But I digress…
Generative and agentic AI will significantly impact product management and virtually all other corporate roles. No one has a crystal ball to know EXACTLY how this all plays out ; however, there is no shortage of opinions and perspectives that attempt to provide an educated guess.
One line of thinking is that we should view generative AI as a really smart intern that can provide us with “assisted intelligence” in multiple ways. Another line of thinking is that the same intern will flat-out replace many tasks and roles we currently do today. Others wisely state it depends; the truth is likely somewhere in the middle (always a safe bet). I have my thoughts on product management and automation, and how this plays out in the future of the product trifecta. But first, let’s begin with an overview of what kind of tasks and scenarios lend themselves to being streamlined by our agentic AI intern.
Personal Intern or Job Usurper? Automation vs. Assisted Intelligence
Many types of tasks and use cases lend themselves to being taken over by generative AI tools. Digital functions with lots of data available that are repetitive (or boring) are the basic criteria. Furthermore, when those criteria intersect with situations that involve human bottlenecks, a need for 24–7 access, or a desire for highly personalized experiences, you have a prime opportunity for AI agents to take over. There is a difference, however, in tasks that AI can partially or fully automate vs. tasks where AI can provide assisted intelligence. Let’s dive deeper.
Venn Diagram depicting AI opportunity for companies undergoing an AI Transformation
Let’s look at scenarios specific to product management and product teams. Responsibilities like writing PRDs, user stories, release notes, and conducting data analysis check the boxes for being digital, repetitive, and where a human could reasonably be a bottleneck. Depending on the level of organization in the company’s data systems, there is potentially a significant amount of data that a company could rely on to streamline these tasks. We may or may not be able to automate these tasks fully. At the very least, however, they can be significantly streamlined when we think of AI agents as capable interns.
Next, there are product management tasks that do not lend themselves to significant automation, but AI can still greatly assist us. These include activities such as market research, prototyping, and even prioritization. Note: I would not rely on AI to prioritize your roadmap for you, but AI can provide input or analyze data that assists in your decision-making.
User/market research, prototyping, and prioritization are not repetitive in the same way as the tasks I listed earlier, but there are patterns, templates, and frameworks that AI can leverage. This is where the brilliant intern can provide assisted intelligence, benefiting all roles in the product trifecta by streamlining and enhancing work output, if not fully automating it.
Finally, the remaining responsibilities will still sit with the product manager or leader. These tasks become even more critical as AI accelerates prototyping and delivery of products and features. Product vision and strategy, negotiating with stakeholders, and aligning executive leadership all become even more vital to a product manager. AI can provide assisted intelligence in these scenarios, but more as a thought partner to enhance the work, rather than as a catalyst for streamlining the process.
We can think of these tasks, therefore, as being on a spectrum where on one end, tasks can be (nearly) fully automated while at the other end of the spectrum, tasks do not lend themselves to automation but do lend themselves to being enhanced by AI-assisted intelligence. In the middle of the spectrum is, of course, a blend of (partial) automation and AI-assisted intelligence.
Image depicting a list of product development tasks on a spectrum of automation to assisted intelligence.
The Future of the PO and the Product Trifecta
If we zoom out and simplify the implications of AI on product roles, AI-driven automation will primarily disrupt the traditional Product Owner (PO) role — the left side of the spectrum in the diagram above. As discussed in a recent Product Therapy podcast and blog article by SVPG (see links at the bottom of this article), Christian Idiodi and Marty Cagan highlight how AI significantly impacts product delivery— the phase primarily managed by Product Owners and Engineers. As generative AI tools rapidly streamline tasks related to coding, testing, deployment, and delivery, process-oriented roles become increasingly vulnerable.
However, AI will serve primarily as assisted intelligence for product management roles, particularly in strategic areas such as product discovery and strategy — the middle and right-side of the diagram above. Product managers, designers, and engineers — collectively referred to in the Product Therapy episode as the “discovery trio” — will remain vital, with AI augmenting their cognitive load rather than replacing them outright. The podcast notably emphasizes the continued importance of human judgment/taste, emotional intelligence, and creative problem-solving — skills AI cannot yet replicate fully but can enhance significantly.
The dramatic shift outlined by SVPG projects smaller product teams with more scope and responsibility, centered on the discovery trio. This model promotes greater autonomy, quicker decision-making, and faster innovation cycles. AI, thus, acts less as a job replacer in strategic product roles and more as a powerful tool that amplifies human capability and productivity.
Embrace the “AI as an Intern” Approach
Think of AI as your highly capable intern — cost-effective, tireless, and rapidly improving. AI excels in automating repetitive, data-intensive tasks, but its most significant contribution is in enhancing human intelligence on tasks that genuinely require judgment and strategic thought.
Product owners, product managers engineers and designers alike should leverage AI to focus their efforts on higher-value strategic activities that will be augmented — but not replaced — by AI. My recommendation for people in this space is to do the following.
Strategically Position Your Skillset: Invest deeply in product strategy and discovery skills, increasingly critical as AI manages more and more routine tasks.
Lean into Soft Skills: Build expertise in stakeholder negotiation, organizational alignment, emotional intelligence, innovative thinking and decision-making — areas where human insight is indispensable.
Proactively Upskill: Continuously identify and address skills gaps. Successful future roles working alongside AI will demand broad capabilities, autonomy, and strategic depth.
Ultimately, think of AI as handling the output, while product professionals can focus on the outcomes. Your primary responsibility — solving the right problems at the right time in the right way (with the right organizational alignment) — remains as vital as ever. If you can see the big picture and make smart moves to position yourself in the future, you will realize that the core functions of the product trio — product strategy, product discovery, and driving alignment in complex organizations — remain as vital as ever.
