How AI is changing product management and what you need to know
guest column
For the past 14 months, everyone has been talking about ways artificial intelligence is changing the world, and product management is not an exception. The challenge, as with every new technology, is not only adopting it but understanding what old habits, workflows, and processes are affected by it.
Product managers — as well as startup founders leading a product function — more than any other role, face a challenge of bringing new life-changing products to market that may or may not be received well by their users. A product manager’s goal is complex — bring value, stay ahead of the competition, be innovative. Yet, the "behind the scenes" grind requires endless decision making and trade offs to inspire stakeholders to move forward and deliver.
As we dive into 2024, it is obvious that AI tools do not only transform the way we work but also help product managers create products that exceed customer expectation and drive businesses forward.
Market research and trends analysis
As product managers, we process enormous amounts of market data — from reviewing global and industry trend analysis, to social media posts, predictions, competition, and company goals. AI, however, can now replace hours, if not days, of analyzing massive amounts of data in an instant, revealing market trends, anticipating needs, and foreseeing what's coming next. As a result, it is easier to make effective product decisions and identify new market opportunities.
Competitive analysis
Constantly following competitors, reviewing their new releases, product updates, or monitoring reviews to identify competitor strengths and weaknesses is an overwhelming and time consuming task. With AI, you can quickly analyze competitors’ products, pricing, promotions, and feedback. You can easily compare multiple attributes, including metrics, and identify gaps and areas for improvement — all the insights that are otherwise much harder to reveal quickly and efficiently.
Customer and product discovery
Of course, the most intuitive use case that comes to mind is the adoption of AI in product and customer discovery. For example:
- Use AI for customer segmentation and persona creation to help visualize personas, prioritize user motivations and expectations, and uncover hidden behavior and needs. You can then create and simplify customer questionnaires for interviews and user groups and target customers more accurately.
- Analyze quantitative and qualitative data from surveys, support tickets, reviews, and in-person interviews to identify pain points and unmet user needs and help prioritize features for future updates and releases.
Roadmap and sprint management
AI provides value in simplifying roadmap planning and sprint management. Resource optimization is often a gruesome task and AI can help with feature prioritization and resource allocation. It helps teams focus on critical work and increase their productivity. You can even analyze and manage dependencies and improve results across multiple sprints months in advance.
Prototyping and mockup generation
There is no product manager’s routine without multiple mockups, wireframes, and prototypes that explain concepts and collect feedback among stakeholders. AI has become a critical tool in simplifying this process and bringing ideas to life from concept to visualization.
Today, you can use textual or voice descriptions to instantly create multiple visuals with slight variations, run A/B tests and gather valuable feedback at the earliest stage of a product life cycle.
Job search and job interviews
Consider it as a bonus but one of the less obvious but crucial advantages of AI is using it in job search. With the vulnerable and unstable job market, especially for product roles, AI is a valuable assistant. From getting the latest news and updates on a company you want to join, to summarizing insights on the executive team, or company goals, compiling lists of interview questions, and running mock interviews, AI has become a non-judgmental assistant in a distressing and often discouraging job search process.
Use AI to draft cold emails to recruiters and hiring managers, compare your skills to open positions’ requirements, identify gaps, and outline ideas for test assignments.
We already know that AI is not a hype; it is here to stay. However, remember that customers do not consume AI, they consume your product for its value. Customers care whether your product gets their need, solves their problem, and makes their lives easier. The goal of a product manager is to create magic combining human brain capabilities and latest technology. And the best result is with a human at the core of any product.
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Natasha Gorodetsky is the founder and CEO of Product Pursuits, a Houston company that helps early stage and venture-backed startups build products and create impact.
