Our New AI Reality
AI is rapidly becoming an integral part of the daily lives of people.
From Google's AutoComplete feature in Gmail to Amazon Alexa's voice recognition in homes to Uber's use of AI to match drivers to users, AI is both invisible and visible.
McKinsey estimates that "AI has the potential to deliver additional global economic activity of around $13 trillion by 2030, or about 16 % higher cumulative GDP compared with today - this amounts to 1.2 % additional GDP growth per year."
This article looks at how AI can disrupt product management, what that might mean for Product Managers, and how they have to change their approach to keep up with this trend.
AI And The Next Generation Of Product Management
AI can influence several areas of Product Management, including team management, product design, market research, and development.
This section provides an overview of how AI might change the requirements for the future role of a Product Manager and how it is disrupting the profession.
It looks at the different possibilities and potential of AI from a Product Management perspective.
Market Research: AI can be used in supplementary ways in market research by incorporating AI to collect, analyze and understand consumer behavior. This will free time for Product Managers to have more in-depth conversations with consumers.
For e.g., Qualtrics research estimates that AI is most likely to make support and pure analysis jobs redundant, such as 97% of market research Assistants and 99% of VP Market Research jobs. For Product Managers, this means they get to have their concierge research team via AI.
Design: AI can help design by generating ideas after analyzing what users are saying about a product or implementing concepts that work well according to data.
This could lead to more productive design teams and better design-PM coordination via considering multiple alternatives as a default versus sticking with time and tested options, which many design teams often fall into.
For e.g., UserZoom's research suggests that A/B testing of design options could undergo a fundamental shift with the application of AI.
Team Management and coordination: AI can prioritize tasks by analyzing KPIs, monitoring progress, or finding bottlenecks within the team. This could reduce the need for Product Managers to spend time on these tasks, leading to more time for higher-level decision-making or strategic work.
Additionally, deep learning allows AI to suggest insights or tools that improve the product based on data. Product Managers could rely on these suggestions, freeing up time for higher-level tasks. For e.g., Atlassian's AI research shows that 64% of professionals already moderately or completely trust AI to make good decisions.
AI-Assisted Product Management
AI has the potential to automate routine tasks and thus save time for PMs. Product Managers won't have to go through all customer requests manually but will be provided with an automated and augmented process that lists out all problems by customers.
This list can also include other information like product idea rating or sorting preferences of customers.
Product Managers will be able to rely on AI to gather information about their users. For example, AI can provide PMs insights into user behavior by analyzing raw data..
It will be possible to track usage patterns of customers based on product usage.
This is already happening with chatbots which many Product Managers use. Since AI powers chatbots, they will constantly learn from conversations and interactions with customers. Chatbots can become a helpful assistant to Product Managers in gathering information about customer needs across their platform.
Product Managers won't have to write heavy release documentation as AI will do this by reading through the product's log files. The logs contain all actions users are taking in the product.
Therefore, release notes become redundant, and Product Managers can focus on other tasks without losing track of user behavior.
Another benefit is that AI will collect all feature requests from customers. Product Managers won't have to rely on individual customer feedback anymore but get an automated list of new ideas created by users.
The customer success team can be automated to a certain degree with the help of AI. Features like auto-replies to common issues can free up time for Product Managers and other employees, who then get the chance to focus on value creation instead of basic tasks.
This is especially true in SaaS companies, where AI can directly interact with customers.
AI will help Product Managers and SaaS companies to provide better service for their users by providing them with proactive advice and suggestions.
The AI system will suggest new features based on user behavior in the product and information about common errors or issues that many customers still struggle with even though they were already reported in the feedback.
Conclusion
Product Managers need to adapt to the new world of Artificial Intelligence. No longer can they be solely focused on product features. They must also consider how AI will affect their product and its users. To do this, Product Managers need to understand the principles behind AI; otherwise, it may seem like magic.
Product Managers are already adapting to the new way they work because of new technologies, and though AI will add more pressure, yet create more opportunities.
All this suggests that the Product Management function will change fundamentally and that the future will be AI-Product Managers or AI-Assisted Product Managers.
