As a product manager, staying ahead of the curve is essential, and AI is a powerful tool to help you achieve that. A recent LinkedIn survey shows 91% of professionals are incorporating AI into their daily workflows. Despite its widespread use, AI often remains an under-discussed topic among product people.
This article covers how product managers integrate AI into their product management daily work. From learning to use AI with prompts to leveraging AI for data-driven insights, you'll discover how product managers are using AI today and in the future.
AI Usage Today
Based on an informal survey on LinkedIn, most professionals are using AI pretty often in their work.
20% of the survey viewers were product managers. Over half the respondents are using AI daily.
What are product managers doing with AI today? How will product managers use AI in the future?
AI Usage in the Real World Today
In a recent interview with Mustafa Kapadia on product manager usage of AI, product managers are using AI for:
Generating preliminary requirements documents
Outlines of next steps for product initiatives
Sparring partner in preparation of a presentation to stakeholders
Generic advice to solve product management issues
Discussion of trade-offs
Product managers are shifting their mindset as they overcome challenges in using AI. Some of the ways product managers work around the challenges in using AI are:
Re-package AI-generated requirements into a hierarchy aligned with the product organization
Summarize detailed market data into a meaningful business opportunity
Present trade-offs on decision options to stakeholders
Understand the context of engineering, finance, sales, marketing, and executives
Adding their unique perspectives to AI-generated responses
Additionally, product managers are learning to use the different AI tools out in the market. A big focus is on the protection of intellectual property when using AI.
AI Usage Experiments
Product managers are quickly finding new ways to use AI. Some ways to integrate AI further into product management are:
AI Product Toolset - Build up a set of AI prompts and specialized tools to accomplish a specific task in product management
AI Product Analytics - Use AI to evaluate data and find insights
AI Product Advisory Board - Improve general management skills through AI-generated perspectives of each product team role
AI Usage in the Future
As these experiments evolve into full capabilities for product managers, then what is next?
In the future when product managers have years of experience in using AI daily, there are more ways to elevate product managers to very broad and influential roles in their organizations.
Looking ahead product managers can leverage AI in these ways:
Decision support from AI - Rapid evaluation of scenarios and outcomes on product decisions
Risk management from AI - Spotting specific product risks and flagging them for product managers
AI-generated critical thinking prompts - Predictive analytics, evolving compliance requirements, and ethical practices are anticipated in time for product management action
The benefit of these changes is product managers have more time for product strategy and prevention of product issues. In the future, AI can take over many of the worries of product managers. The result is product managers can be focused on customers and business growth.
Conclusion - AI and Product Management Are Evolving
Product managers are using AI more than ever before. AI literacy is becoming a basic job requirement for most product management roles. As product managers experiment and become proficient with AI tools, they can leverage AI for increasingly complex aspects of product management. The future is bright for product managers who incorporate AI into their daily work!
A big thank you to Mustafa Kapadia at Echo Point for inspiring this article. His posts and articles on AI Productivity are useful for product people!
Last week’s backstory for paid subscribers was about resilience in product management. Extra Steps to Resilience in Action
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PMs who aren't using AI are going to fall behind. It has a lot of use cases. I've been using it for discovery, analyzing data, as well as assisting in PRD writing. This is a useful reminder.
I'm currently building http://derisky.ai
I would love to hear your feedback on it.