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Product management is a strategic function that ensures that an organization’s offerings align with industry needs, customer expectations, and business goals. In simplest terms, product managers serve as a bridge between a company’s products and the market’s changing demands. That puts them on the front lines of the latest AI revolution.
Let’s dig a little more into how product management is evolving in this new era of AI, including the latest and best skills product managers will need to succeed!
What Does a Product Manager Do?
Product managers are responsible for ensuring that a company’s product is properly positioned in the market—not just from a promotional standpoint, but from a practical and functional perspective.
“A product manager’s job is to align what a company offers with market demands—not in a marketing way, but by ensuring that the product truly meets industry needs,” said CompTIA chief technology evangelist James Stanger.
One of the core responsibilities of a product manager is shaping the message around a product. While marketing teams specialize in amplifying that message and ensuring it reaches the right audience, they often rely on product managers to define the narrative itself.
“Marketing professionals are great at getting the message out at scale, but they don’t always determine what the message should be,” Stanger said. That’s where the product manager steps in—understanding the market, refining the positioning, and ensuring the message reflects the actual value of the product.
A strong product management team functions as a two-way communication channel between the company and its customers. This involves both collecting customer feedback and ensuring that internal teams correctly interpret user behavior and expectations.
“Product managers receive direct feedback from customers about what’s working and what’s not,” Stanger noted. “At the same time, they also help clarify misunderstandings.”
He explained sometimes customers focus on the wrong feature or don’t realize the full capabilities of a product: “It’s the product manager’s job to guide both the internal team and the end users toward better alignment.”
This requires a blend of technical knowledge, business acumen, and market insight: a well-equipped product manager doesn’t just understand how a product works; they also anticipate how it should evolve to stay relevant.
How AI Can Help
Tony Liebel, product manager for Plume, said he’s used AI effectively to develop imagery and mockups in internal pitch decks to really sell an idea.
“Using AI for this task eliminates the need to go through stock imagery or engage with a design team that may have bigger items on their plate,” he explained.
AI can also be used to review hundreds of lines of customer insights, uncovering trends and themes that can help build a deeper understanding of the reasoning behind specific feedback. “Tools like ChatGPT and Perplexity can increase research speeds, and I have heard success from others that have built a custom GPT based on their own knowledge base to iterate on product, which is a fairly complicated process,” he added.
Stanger said Generative AI (GenAI) plays a significant role in product management, particularly in distilling information and streamlining workflows, and can assist by transcribing and summarizing meeting notes, reducing time spent on administrative tasks: “Product managers are constantly in crunch mode, balancing multiple stakeholders… AI helps by tailoring messages to different audiences—whether for government, enterprise, or IT buyers—but it doesn’t replace real expertise.”
Essential Understanding
Liebel’s advice is to treat everything right now as if it is in a beta: “If a product manager, engineer or designer is using AI, then they must keep a close eye on the output.”
Spotting AI “hallucinations” is incredibly challenging, as they can be very convincing or subtle, but they can lead to bad business outcomes if not caught. “Before anything is presented and especially pushed live, it needs a thorough vetting,” Liebel cautioned.
Stanger thinks that, while AI could assist product managers in refining ideas, relying on it for innovation is a mistake. “If you’re looking to AI for ideas, you’re in trouble,” he said. “It can help with nuances and modifications, but a well-trained product manager must distinguish between useful insights and repetition.”
Predictive AI has more value than generative AI in product management, particularly in market modeling and communication flows. “Just as network architects use AI for system modeling, product managers can leverage predictive AI to assess potential markets and internal workflows,” Stanger explained.
AI Training: Where to Go
Thomas Vick, senior regional director with IT staffing specialist Robert Half, said he sees many product managers getting their Project Management Professional (PMP), a globally recognized certification issued by the Project Management Institute (PMI).
“A lot of them are looking at some type of project management component to it,” he explained. Some additional certifications that offer specialized training for AI include:
IBM AI Product Manager Professional Certificate
The 10-course series designed to prepare individuals for a career in technology and AI-driven product management in three months or less, covering product management principles, from ideation to launch, alongside generative AI concepts like prompt engineering and foundation models.
Udacity AI Product Manager
The program offers a foundation in AI and machine learning for business, covering AI fundamentals, data utilization, and generative AI technologies. Learners complete three hands-on projects, including creating a Product Requirements Document (PRD) for AI-driven personalization, developing a roadmap for AI products requiring custom data, and building a strategy for integrating LLMs while measuring performance and bias metrics.
From Liebel’s perspective, the best way to become familiar is with hands-on experimentation: “Take something you developed yourself—whether a piece of technology or writing—and ask the tools to replicate… See if it can adjust what you are already doing or provide insights you might not have considered to improve on something you’ve worked on.”
He finds communities online or in-person are the best to see how people are using these new tools. “If you have a core group of other product managers, either internally or externally, try to start up a conversation with them to see how they may be using AI tools effectively,” he said.
Message boards like Reddit also have endless conversations about understanding how AI works.
Securing Executive Buy-In for Upskilling
Vick explained product managers can make a compelling case for AI investment by demonstrating how these tools enhance market research and trend analysis to justify a product’s potential return.
He emphasized that AI-driven insights can help product managers clearly articulate how executing a project will generate value: “The biggest way is being able to really justify how executing this product might create some type of return.”
By leveraging AI to analyze trends and market opportunities, product managers can present data-backed arguments to secure the resources needed for AI integration.
Liebel agreed that product managers can get support the same way any good product manager should attain executive value: by showing its value. “Bring case studies, examples within the industry or a personal experience,” he said.
Good teams need to balance output with continuing education, and product managers should provide resources for employees to learn a myriad of skills including AI. “If you have the right manager, product line and company risk profile, it can be up to you to decide if it is worth the risk to use the tool on your own before even starting the conversation,” Liebel added.