Synthetic Intelligence (AI) is an business mainstay that’s altering how we construct, launch, and handle merchandise. However there’s a brand new taste on the block: Agentic AI in Product Administration, a complicated type of AI that not solely processes information or generates content material but in addition acts autonomously in pursuit of aims.
Throughout a latest Productside webinar, our resident AI professional, Dean Peters, and host Roger Snider explored a essential query: Is Agentic AI a pal or a foe to product managers? Drawing on reside demos, real-world examples (together with a memorable fruit-salad analogy), and viewers Q&A, they provided a recent take a look at how PMs can harness AI’s decision-making prowess—with out getting changed.
On this publish, we’ll discover the ideas they mentioned:
- What units Agentic AI aside from conventional or generative AI
- Concrete methods AI-driven product technique can velocity up (and shake up) product workflows
- Why ethics, guardrails, and transparency matter now greater than ever
- How one can adapt your enterprise mannequin to remain related in a market that expects outcomes, not simply options
In case you’ve been questioning whether or not the rise of AI means you’ll be out of a job—or whether or not it’s your secret weapon—that is the breakdown you want.
What Is Agentic AI?
Most product of us have kicked the tires on generative AI (suppose ChatGPT) for duties like producing consumer tales or brainstorming advertising copy.
Agentic AI, nevertheless, goes a number of steps additional by including autonomy, company, and accountability—generally referred to as “the three A’s.” As Dean Peters defined within the webinar, Agentic AI methods don’t simply spit out solutions; they:
- Plan duties independently
- Adapt to real-time information
- Act with minimal or zero human oversight
In different phrases, Agentic AI for Product Managers isn’t ready round on your subsequent immediate. Like a young person despatched to the grocery retailer, it has the authority to make on-the-fly choices, change ways if Plan A fails, and keep accountable for the result. In line with Dean:
“Agentic AI isn’t simply reasoning. It’s additionally performing. It’s designed to take motion primarily based on context and aims, minimizing human enter.”
The end result? AI strikes from a passive help function to an lively participant in your product’s lifecycle.
Past Generative AI: Autonomy in Motion
Throughout the webinar, Roger Snider used a playful instance of sending his teenage daughter to purchase fruit. She had the liberty to pivot from strawberries to blueberries if shares have been low—demonstrating autonomy, company, and accountability.
That very same logic can apply to AI-driven product administration instruments:
- Autonomy: The system operates out of your direct line of sight, evaluating choices and forging forward when it’s positive of the subsequent transfer.
- Company: It has the latitude to make choices past a single algorithm. The AI may determine new alternatives (e.g., “No strawberries? Let’s attempt berries which can be in inventory—or discover a retailer that has them.”).
- Accountability: It’s constructed with guardrails in order that if one thing goes incorrect, the AI’s “proprietor” (an organization, a product supervisor, or a developer) can audit the method, see what occurred, and proper course.
In different phrases, the AI doesn’t simply generate a to-do checklist. It executes duties—very similar to Tesla’s self-driving system or an automated AI-powered market analysis platform that “decides” when and the way usually to e-mail prospects. degree of ambiguity could be overwhelming. However Scott thrives in it, continually validating assumptions and iterating on insights.
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From Outputs to Outcomes: Why Agentic AI Modifications the Sport
Conventional AI helps with discrete duties (predicting churn, producing textual content, or discovering patterns in information). Agentic AI, although, can orchestrate complete workflows. Primarily based on the webinar, listed here are just a few key eventualities:
- Autonomy for Market Analysis and Insights
Market analysis can eat up a product supervisor’s week. An Agentic AI for market analysis can pull information from a number of information sources, competitor websites, and social channels, then synthesize it—mechanically. Within the webinar’s Q&A, Dean talked about how some options generate “artificial consumer personas,” successfully operating simulations and consumer exams with out human intervention. Product managers can then deal with strategic evaluation as an alternative of drowning in uncooked information.
- Computerized Stakeholder Administration
Constructing alignment is core to profitable product administration. Sure AI-driven instruments for stakeholder administration now observe stakeholder conversations (e-mail, chat logs) and predict potential “pink flags.” If a stakeholder’s sentiment sours, the AI can attain out proactively, suggest options, and notify the PM in actual time. That is greater than easy automation—it’s an AI that learns from habits and acts earlier than you even understand there’s an issue.
- Determination-Making and Roadmap Prioritization
Due to AI-powered decision-making, Agentic AI can juggle a number of information factors—like characteristic utilization, consumer suggestions, and income metrics—and rank the backlog accordingly. The system may even suggest complete epics or resolution bushes. Within the webinar, Dean demoed a circulate the place the AI independently selected to focus on a selected phase (“working mother and father”) after scanning a fictional e-mail from “the boss.” Whilst you’d nonetheless confirm the info and weigh enterprise aims, the heavy lifting is off your plate.
Potential Pitfalls: Ethics, Drift, and Over-Reliance
No expertise is with out dangers, and Agentic AI amplifies sure issues:
- Information Drift: Over time, fashions can turn out to be stale or biased. You’ll possible want an “agent to observe your agent,” guaranteeing it’s utilizing related information and hasn’t veered off beam.
- Compliance and Guardrails: In regulated industries—suppose healthcare or finance—totally autonomous choices could be dangerous. AI-powered governance methods can hold your AI from going rogue.
- Transparency: Customers and stakeholders have to know when AI is making choices. With out a clear “present your work” method, belief can erode shortly.
PWC estimates that 40–70% of data work (together with product administration duties) may very well be automated by AI. However Roger Snider famous within the session that whereas AI can “pull the set off” on routine duties, it can’t exchange management or strategic imaginative and prescient. That’s nonetheless on you.
Agentic AI: Buddy, Foe, or Co-Pilot?
So, do it is advisable fear about shedding your function to an AI agent? In line with Dean Peters, the actual hazard lies in ignoring how shortly AI is evolving. In case your complete job revolves round manually writing consumer tales or producing PRDs, you could possibly end up outdated.
Nevertheless:
- Visionary PMs are extra essential than ever, bringing strategic pondering, consumer empathy, and cross-functional management that no AI can replicate.
- Moral Stewards are wanted to set guardrails, guaranteeing AI doesn’t create authorized or reputational nightmares.
- Information-Conscious Leaders who can harness AI’s insights—and feed it the best information—will outpace rivals.
To borrow Dean’s phrase from the webinar, “Agentic AI makes an awesome co-pilot—however it nonetheless wants a pilot.”
Mastering Zero-to-One Product Administration Begins Right here
Agentic AI is redefining what it means to handle merchandise. By understanding find out how to leverage its autonomy, company, and accountability, product managers can transfer from job execution to strategic management, utilizing AI as a co-pilot—not a substitute.
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February 20, 2025
