Since OpenAI’s public launch of ChatGPT, conversations about the role of artificial intelligence (AI) in the tech industry have become virtually ubiquitous in the press.
In response to the rapid dissemination of AI-powered software, industry leaders have begun to speculate about AI’s role in their product strategy and business operations. While analysts, investors, and technologists have a multiplicity of predictions about how AI will change the discipline of product management (and the tech sector at large), forward-thinking PMs have already begun using AI to enhance their operations and leverage additional expertise.
To help product managers use AI effectively, we’ve asked a group of experts to tell us which AI tools they use on a day-to-day basis and why they’re effective. To make the best recommendations possible, we’ve asked our experts to recommend lesser-known tools and features (outside of popular choices like ChatGPT and Midjourney). Read on to learn how your organization can use AI to improve your product and delight your customers.
Note that each product manager we have asked uses AI for distinct purposes, so their advice on particular tools may not be directly applicable to your work.
We’ll be highlighting the expertise from these professionals:
- Zalak Trivedi, Product Manager at Sigma Computing
- Ritesh Raj, Chief Product Officer at CuddlyNest
- Ravi Parikh, CEO at Parikh Financial (Ex-CEO, RoverPass)
And thanks to Kristen Poli for crafting this piece for GoPractice.
Kristen Poli is a product leader and tech journalist.
She previously held the position of product manager at Contently and was the product management lead at Curacity.
Her articles have been published in outlets like WIRED and Hackernoon.
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Q. Which AI tools do you use the most?
Effective product managers use AI-powered tools to save time and gain expertise across the product lifecycle. Our interviewees have succeeded in using AI to streamline project management processes by using tools that identify dependencies within complex workflows, estimate project completion times, and provide dynamic cost estimates. In addition to using AI to support the timely delivery of new features, experts use these tools to collect, understand, and communicate stakeholder feedback with ease. In addition to the use cases above, AI tools were implemented by PMs to perform customer segmentation analyses, optimize market research, and perform A/B tests.
Uses AI tools to improve stakeholder communication
Notion: I transitioned from using Google Docs for meeting notes to Notion due to its integration of various AI features. I leverage the “summarize” and “improve writing” functions to refine my call notes, facilitating easy sharing with team members.
Gong: I find Gong’s meeting summary feature invaluable, especially during calls with multiple participants generating ideas and action items. The detailed meeting summary keeps me organized. I have also set up trackers for Slack notifications based on specific keywords used in Gong calls. This allows me to efficiently navigate to the relevant sections during customer research, saving me valuable time compared to watching the entire meeting recording.
ChatGPT: I tend to be verbose when writing blogs or expressing new feature requests. I consistently utilize ChatGPT Plus to condense my ideas, aiding in clear and concise communication with stakeholders.
→ Test your product management and data skills with this free Growth Skills Assessment Test.
→ Learn data-driven product management in Simulator by GoPractice.
→ Learn growth and realize the maximum potential of your product in Product Growth Simulator.
→ Learn to apply generative AI to create products and automate processes in Generative AI for Product Managers – Mini Simulator.
→ Learn AI/ML through practice by completing four projects around the most common AI problems in AI/ML Simulator for Product Managers.
Uses AI tools optimize software development and smart decision-making
I use AI tools to enhance our operations and decision-making processes. For project management, we use ClickUp, an AI-powered tool that stands out with its unique features. ClickUp’s customizable views allow us to tailor our workspace to our needs, while the dependency feature helps us understand the relationship between different tasks. The time tracking feature enables us to monitor how much time is spent on each task, aiding in resource allocation. ClickUp’s role-based AI Assistant takes the guesswork out of leveraging AI for different types of work.
Another standout ClickUp feature is Write with AI. This tool allows us to enter custom prompts in multiple languages, making drafting emails or outlining blog posts a breeze. These features not only enhance our productivity but also transform the way we work.
As the CPO, I use Github for product development. This is a platform that not only hosts our code but also provides AI-powered features like semantic code navigation and automated dependency updates. These features help us streamline our development process, catch potential issues early, and ensure our product is always at the forefront of innovation.
By harnessing the power of AI in these ways, we’re able to operate more efficiently, make informed decisions, and ultimately deliver a better experience for our customers.
Uses AI tools for market research, automated testing, and customer segmentation
I use AI across four major areas:
Predictive Analysis. While you have excellent tools like Tableau, TIBCO Data Science, IBM, and Sisense, renowned for their predictive analytics capabilities, I prefer using ClickUp. It is a popular AI tool for collecting project data, improving decision-making, and performing project cost estimations.
Automated Testing. TestGrid is an excellent AI Test Automation platform offering various features to help you test apps on real devices, including automated testing, performance testing, API testing, and security testing. Appvance IQ is another AI-powered test automation tool that tests native mobile, mobile web, and hybrid apps on iOS and Android. I use both of these tools, depending on project requirements.
Sentiment Analysis. Brand24 provides sentiment analysis, helping brands understand how customers feel about their products or services. E-commerce retailers prefer using this tool. However, I use Enthu.AI, a conversation-intelligent software tool that offers sentiment analysis through state-of-the-art ML and AI algorithms.
Conclusion
As AI tools continue to appear (and evolve) at a fast pace, forward-thinking product managers can stay ahead of the curve by researching, testing, and sharing their favorite AI applications with others in the field. While no individual tool currently presents as a one-size-fits-all solution for product managers, AI-powered tools and features can help product managers streamline essential tasks like customer feedback collection, resource allocation, user segmentation, A/B testing, and stakeholder communication. While AI’s long-term role in product management is still uncertain, PMs who find creative ways to use AI in order to provide better customer experiences are well-positioned for the future.
Learn more
— The easiest and hardest parts of a PM’s job
— How do you avoid adding unnecessary features to your product?
— What qualities do successful product managers have in common?
Illustration by Anna Golde for GoPractice
