Written By Jess Feldman
Course Report strives to create the most trust-worthy content about coding bootcamps. Read more about Course Report’s Editorial Policy and How We Make Money.
Course Report strives to create the most trust-worthy content about coding bootcamps. Read more about Course Report’s Editorial Policy and How We Make Money.
Product managers are an essential part of a technical team, and now these professionals are turning to AI tools to enhance their productivity and impact. From bug identification to market research, learn about five AI tools and how product managers are using them on the job. While AI tools can be a boon to product management, we’re also weighing the pros and cons of incorporating them into a technical team. Plus, find out where to learn product management and artificial intelligence skills!
Pros |
Cons |
Focus on data-driven decision-making |
Data security and privacy |
Optimizes product development |
Over-reliance on AI |
Deeper, real-time understanding of user |
Lacks context |
AI tools can give product managers a serious leg up with their work! By incorporating artificial intelligence tools into their workflow, product managers can streamline and organize their processes. Oftentimes, these AI tools make it easier for technical teams to collaborate and share information. AI tools can also give product managers actionable insights and forecasts, so they can make better informed, data-driven decisions. Certain AI tools can give product managers a deeper understanding of their customers by sifting through data and delivering insights about the user’s patterns, pain points, and needs.
Despite the benefits of integrating AI tools into product management, one of the main detractors is becoming overly reliant on these AI tools. AI tools may help product managers optimize certain tasks, but AI should not replace brainstorming and critical thinking! Similarly, AI recognizes data and patterns, but it does not have the context to grasp concerns related to a specific company or product. Product managers should also be mindful of data security and privacy, ensuring that the AI they are using is compliant with intellectual property and their customers’ privacy.
How ChatGPT is used by Product Managers: Product managers may lean on ChatGPT to help summarize notes, get ideas on how to improve interactions with users, and draft product materials. Depending on the strength of the prompt, ChatGPT can be used to identify customer pain points and needs.
How Mixpanel is used by Product Managers: Mixpanel is an AI tool used for market research. The focus of the tool is to help product managers get the insights they need to make data-driven decisions. Product managers may use Mixpanel to identify patterns, visualize the user journey, A/B testing, and more.
How Notion is used by Product Managers: Notion is a notes-taking AI tool that is able to summarize and create actionable insights. Product managers may use this tool to make company wikis and product roadmaps.
How Collato is used by Product Managers: Collato syncs up a team’s documents so they can be easily searchable for product information. Collato’s visual maps also make it easier for product managers to find and understand information about a specific product or project.
How JamGPT is used by Product Managers: JamGPT helps product managers identify bugs and gives context about how to fix them — Non-technical product managers may especially find this feature helpful! JamGPT makes it easy to share information about bugs within a technical team.
Jess Feldman is an accomplished writer and the Content Manager at Course Report, the leading platform for career changers who are exploring coding bootcamps. With a background in writing, teaching, and social media management, Jess plays a pivotal role in helping Course Report readers make informed decisions about their educational journey.
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