Product Management

AI Product Management: A Guide for Product Leaders

Content Writer

Athira V S

January 24, 2024

7 mins read

AI Product Management: A Guide for Product Leaders

According to a recent survey, an average product manager spends almost half their time firefighting instead of focusing on planned strategic activities. Product managers often complain that they're spread too thin and wearing multiple hats.

This was a big issue before, especially for companies that didn't have the resources to hire additional help. However, all of that can change due to the growing popularity and accessibility of AI solutions.

AI product management is revolutionizing the business world and AI product manager is becoming a highly requested profession. In this article, you'll learn everything you need to know about AI initiatives in product management and how they can benefit you.

What is AI product management?

It's a modern approach to product management, using AI and machine learning to help you create better products or improve the existing ones.

AI product management focuses on helping you understand your customers better and create products based on their needs.

You can use artificial intelligence during all phases of the product management process: from product discovery and mapping out stages of the user journey to development and optimization.

Who is an AI product manager?

Source: Freepik.com

The AI product manager leads a team developing or managing products that leverage AI technologies and machine learning.

They need to be familiar with traditional product management principles but leverage them using AI-based products.

This role requires some technical skills like data analysis and communication with data science teams.

However, any product manager could specialize in AI product management if they're tech-savvy, interested in AI and ML and following trends in product management.

Suggested Read: All Product Managers to Become AI Product Managers?

AI product management: benefits

Here are the main benefits of using AI in product management.

Predictive analytics & data insights

Creating great products is a data-driven process. Good product managers know they shouldn't rely on intuition but instead collect the right data to understand customers and the market.

Artificial intelligence helps you collect and analyze large sets of data to understand customer behavior and the usability of your product. It can also predict future customer demands and behavior based on historical data.

Better user experience

Providing a great user experience is all about understanding your customers’ pain points, wants and needs. AI allows you to do detailed user research to discover their preferences and uncover patterns in their behavior.

With these insights, you can build a product that's solving your customers' needs, improving their experience, satisfaction and loyalty to your company.

Great UX is the best competitive advantage in product management.

Increased efficiency & better decision-making

AI speeds up the product development process and makes it more effective. It also enables product managers to make informed decisions because it can evaluate massive amounts of data for you. You no longer have to search customer data manually – AI systems can do it for you.

As humans, we're prone to bias, but artificial intelligence helps you by minimizing bias from the decision-making process.

Money and time saving

With the help of artificial intelligence, you can eliminate or automate many time-consuming tasks like data analysis. It saves you a lot of time, so you can focus on improving your product instead of doing repetitive tasks.

On the other hand, AI can also help you avoid unnecessary costs by identifying product flaws and quality issues early in the development cycle.

AI product management: Challenges

Artificial intelligence can revolutionize product management as we know it today, but there are some challenges you should be aware of.

Data privacy

The rise of AI has raised questions about privacy and ethical standards. Like any other technology, AI can be vulnerable to attacks. That's why it's vital to protect your data and ensure your company has strong security protocols in place.

Biased information

While AI can reduce some types of bias, at the same time, it can also be a source of biased information. Artificial intelligence is based on algorithms that require training and human input.

If the data you enter is inaccurate or contains biased information, that could lead to algorithmic bias, which can negatively affect your company. 

However, you can avoid this by ensuring your input is accurate and unbiased. Also, people who train AI algorithms in your organization should have the technical knowledge and build skills necessary to do it properly.

Building cross-functional teams with AI expertise

There's a lot of evidence that cross-functional teams can perform better in product development because joint expertise allows you to see the problem from different angles. However, it can be challenging to build a team whose members all have AI skills.

Your data engineers are familiar with AI and machine learning, but what about marketing and sales? For successful AI product management, you need to promote AI adoption across the whole company and maybe organize additional training on AI technology.

AI product management lifecycle

Source: Freepik.com

Here's how you can apply AI to different product management operations.

Product discovery

According to recent research, one in five products delivered fails to meet customers' needs. This issue usually arises when product discovery isn't done correctly. Thankfully, today we have tools like Zeda.io that can help you uncover burning customer problems and build products that actually solve them.

Zeda.io can help you detect pain points and prioritize problems you can solve first. With our tool, you can segmentize customer groups and do sentiment analysis to see what has the most significant impact.

Product strategy

According to McKinsey, product managers spend more time defining product strategy than any other activity, so anything that can save them some time during this phase could be a game-changer.

AI can help you develop more accurate strategies thanks to its predictive analytics. Based on your historical data, it can predict:

  • Customer behavior
  • Demand patterns 
  • Future trends

You can also use it to do split tests and test various hypotheses before investing in creating your product. These insights and predictions can help you build a product roadmap and decide which features to prioritize.

In this phase, you can use Zeda.io to create visual strategy plans, a customizable roadmap and goals and targets whose progress you can track.

Product execution & development

AI can help you avoid wasting time and money when developing a product by creating prototypes you can test and validate with fewer resources than an actual product.

You can use generative design algorithms to get multiple design options that can be tested and compared.

Once the product is created, you can use AI to do an automated code review before you publish it because it can detect bugs much faster than human QA testers.

Monitoring & optimization

AI can be used for continuous iteration and optimization, and you can also automate a big part of the process. It can help you with product management analytics.

You can train AI to analyze real-time data, performance and user feedback. This approach empowers you to make data-driven decisions that can improve the quality of your product.

AI product management: best practices

Here are some final tips and key takeaways.

Set clear goals

You need to know what you want to achieve to get the most out of AI's potential. What's your motivation for using AI in product management?

The best way to fully use AI capabilities is to set some SMART goals, which means they should be:

  1. Specific
  2. Measurable
  3. Achievable
  4. Relevant 
  5. Time-bound

Gather customer data

AI and ML, just like any other product management tools, are just instruments that can help you – the core of product management is still the same and it's about focusing on your customers and their pain points and gathering as much data as possible.

Before you start developing a product, it's essential to do user research and detailed market analyses to discover customer problems and needs that haven't been met. Once the product is launched, gather customer feedback to help you optimize and improve the product.

Zeda.io can help you gather customer feedback from different channels and analyze customer segments and their sentiments.

Always remember that AI output depends on your input and the data you provide, so make sure it's always detailed and accurate.

Regularly evaluate AI performance

The best way to improve the use of AI systems is to track, measure and evaluate their performance. The first step is to set clear goals and KPIs you want to track (for example, reducing the time needed to finish some tasks).

Then, evaluate your performance regularly and use the insights you gather to improve the use of AI in your organization.

Read this article to learn how to measure product management success and what metrics to track.

Prioritize continuous learning

AI and machine learning are two sectors that are continuously developing and expanding. That's why it's not enough to understand AI, you need to stay ahead of the curve by monitoring the latest trends and new AI capabilities.

In such a fast-paced sector, continuous learning is the main competitive advantage that will help you create exceptional products and solve complex problems.

Again, learning about AI isn't reserved only for data engineering teams but for all aspiring professionals who want to create innovative products.

Conclusion

Artificial intelligence and machine learning have the power to revolutionize product management. You can use them in all phases, from product discovery to developing and optimizing the product.

AI initiatives benefit both sides: they save time for product managers, help them improve the decision-making process and test and optimize new products. On the other hand, users benefit as well as they get products that better meet their needs.

You don't need multiple AI-powered products, as we've integrated everything you need into one solution. Zeda.io covers the whole product management lifecycle, from product discovery to building and shipping.

Start your free trial today.

Also checkout a comprehensive look into AI Product Management: AI Product Management 101: What You Need to Know

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FAQs

What does an AI product manager do?

AI product managers are responsible for defining product strategy, collaborating with data scientists and engineering team leaders on developing AI models, planning a product roadmap and monitoring product development and performance.

What are the basics of AI product management?

The basics of AI product management include: Understanding the data science process Deep learning Machine learning AI-powered user research Creating strategy Managing software engineering teams

Will AI replace product management?

AI can't replace product management but can improve it by speeding up the process, helping you with data collection, analyzing large data sets and creating accurate predictions.

Can product management be automated?

Product management can't be fully automated because it requires a particular set of skills and technical expertise that machine learning can't replicate. However, some phases of product management can be automated by AI and ML, leaving product managers more time to focus on important things that require human intelligence and input.

Product Management

AI Product Management: A Guide for Product Leaders

Athira V S
Content Writer
January 24, 2024
7 mins read
14-day free trial

Decide what to build next with AI-powered Insights

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IN THIS ARTICLE:
  1. What are product discovery techniques?
  2. 8 key product discovery techniques link
  3. Conclusion
IN THIS ARTICLE:
  1. What are product discovery techniques?
  2. 8 key product discovery techniques link
  3. Conclusion

According to a recent survey, an average product manager spends almost half their time firefighting instead of focusing on planned strategic activities. Product managers often complain that they're spread too thin and wearing multiple hats.

This was a big issue before, especially for companies that didn't have the resources to hire additional help. However, all of that can change due to the growing popularity and accessibility of AI solutions.

AI product management is revolutionizing the business world and AI product manager is becoming a highly requested profession. In this article, you'll learn everything you need to know about AI initiatives in product management and how they can benefit you.

What is AI product management?

It's a modern approach to product management, using AI and machine learning to help you create better products or improve the existing ones.

AI product management focuses on helping you understand your customers better and create products based on their needs.

You can use artificial intelligence during all phases of the product management process: from product discovery and mapping out stages of the user journey to development and optimization.

Who is an AI product manager?

Source: Freepik.com

The AI product manager leads a team developing or managing products that leverage AI technologies and machine learning.

They need to be familiar with traditional product management principles but leverage them using AI-based products.

This role requires some technical skills like data analysis and communication with data science teams.

However, any product manager could specialize in AI product management if they're tech-savvy, interested in AI and ML and following trends in product management.

Suggested Read: All Product Managers to Become AI Product Managers?

AI product management: benefits

Here are the main benefits of using AI in product management.

Predictive analytics & data insights

Creating great products is a data-driven process. Good product managers know they shouldn't rely on intuition but instead collect the right data to understand customers and the market.

Artificial intelligence helps you collect and analyze large sets of data to understand customer behavior and the usability of your product. It can also predict future customer demands and behavior based on historical data.

Better user experience

Providing a great user experience is all about understanding your customers’ pain points, wants and needs. AI allows you to do detailed user research to discover their preferences and uncover patterns in their behavior.

With these insights, you can build a product that's solving your customers' needs, improving their experience, satisfaction and loyalty to your company.

Great UX is the best competitive advantage in product management.

Increased efficiency & better decision-making

AI speeds up the product development process and makes it more effective. It also enables product managers to make informed decisions because it can evaluate massive amounts of data for you. You no longer have to search customer data manually – AI systems can do it for you.

As humans, we're prone to bias, but artificial intelligence helps you by minimizing bias from the decision-making process.

Money and time saving

With the help of artificial intelligence, you can eliminate or automate many time-consuming tasks like data analysis. It saves you a lot of time, so you can focus on improving your product instead of doing repetitive tasks.

On the other hand, AI can also help you avoid unnecessary costs by identifying product flaws and quality issues early in the development cycle.

AI product management: Challenges

Artificial intelligence can revolutionize product management as we know it today, but there are some challenges you should be aware of.

Data privacy

The rise of AI has raised questions about privacy and ethical standards. Like any other technology, AI can be vulnerable to attacks. That's why it's vital to protect your data and ensure your company has strong security protocols in place.

Biased information

While AI can reduce some types of bias, at the same time, it can also be a source of biased information. Artificial intelligence is based on algorithms that require training and human input.

If the data you enter is inaccurate or contains biased information, that could lead to algorithmic bias, which can negatively affect your company. 

However, you can avoid this by ensuring your input is accurate and unbiased. Also, people who train AI algorithms in your organization should have the technical knowledge and build skills necessary to do it properly.

Building cross-functional teams with AI expertise

There's a lot of evidence that cross-functional teams can perform better in product development because joint expertise allows you to see the problem from different angles. However, it can be challenging to build a team whose members all have AI skills.

Your data engineers are familiar with AI and machine learning, but what about marketing and sales? For successful AI product management, you need to promote AI adoption across the whole company and maybe organize additional training on AI technology.

AI product management lifecycle

Source: Freepik.com

Here's how you can apply AI to different product management operations.

Product discovery

According to recent research, one in five products delivered fails to meet customers' needs. This issue usually arises when product discovery isn't done correctly. Thankfully, today we have tools like Zeda.io that can help you uncover burning customer problems and build products that actually solve them.

Zeda.io can help you detect pain points and prioritize problems you can solve first. With our tool, you can segmentize customer groups and do sentiment analysis to see what has the most significant impact.

Product strategy

According to McKinsey, product managers spend more time defining product strategy than any other activity, so anything that can save them some time during this phase could be a game-changer.

AI can help you develop more accurate strategies thanks to its predictive analytics. Based on your historical data, it can predict:

  • Customer behavior
  • Demand patterns 
  • Future trends

You can also use it to do split tests and test various hypotheses before investing in creating your product. These insights and predictions can help you build a product roadmap and decide which features to prioritize.

In this phase, you can use Zeda.io to create visual strategy plans, a customizable roadmap and goals and targets whose progress you can track.

Product execution & development

AI can help you avoid wasting time and money when developing a product by creating prototypes you can test and validate with fewer resources than an actual product.

You can use generative design algorithms to get multiple design options that can be tested and compared.

Once the product is created, you can use AI to do an automated code review before you publish it because it can detect bugs much faster than human QA testers.

Monitoring & optimization

AI can be used for continuous iteration and optimization, and you can also automate a big part of the process. It can help you with product management analytics.

You can train AI to analyze real-time data, performance and user feedback. This approach empowers you to make data-driven decisions that can improve the quality of your product.

AI product management: best practices

Here are some final tips and key takeaways.

Set clear goals

You need to know what you want to achieve to get the most out of AI's potential. What's your motivation for using AI in product management?

The best way to fully use AI capabilities is to set some SMART goals, which means they should be:

  1. Specific
  2. Measurable
  3. Achievable
  4. Relevant 
  5. Time-bound

Gather customer data

AI and ML, just like any other product management tools, are just instruments that can help you – the core of product management is still the same and it's about focusing on your customers and their pain points and gathering as much data as possible.

Before you start developing a product, it's essential to do user research and detailed market analyses to discover customer problems and needs that haven't been met. Once the product is launched, gather customer feedback to help you optimize and improve the product.

Zeda.io can help you gather customer feedback from different channels and analyze customer segments and their sentiments.

Always remember that AI output depends on your input and the data you provide, so make sure it's always detailed and accurate.

Regularly evaluate AI performance

The best way to improve the use of AI systems is to track, measure and evaluate their performance. The first step is to set clear goals and KPIs you want to track (for example, reducing the time needed to finish some tasks).

Then, evaluate your performance regularly and use the insights you gather to improve the use of AI in your organization.

Read this article to learn how to measure product management success and what metrics to track.

Prioritize continuous learning

AI and machine learning are two sectors that are continuously developing and expanding. That's why it's not enough to understand AI, you need to stay ahead of the curve by monitoring the latest trends and new AI capabilities.

In such a fast-paced sector, continuous learning is the main competitive advantage that will help you create exceptional products and solve complex problems.

Again, learning about AI isn't reserved only for data engineering teams but for all aspiring professionals who want to create innovative products.

Conclusion

Artificial intelligence and machine learning have the power to revolutionize product management. You can use them in all phases, from product discovery to developing and optimizing the product.

AI initiatives benefit both sides: they save time for product managers, help them improve the decision-making process and test and optimize new products. On the other hand, users benefit as well as they get products that better meet their needs.

You don't need multiple AI-powered products, as we've integrated everything you need into one solution. Zeda.io covers the whole product management lifecycle, from product discovery to building and shipping.

Start your free trial today.

Also checkout a comprehensive look into AI Product Management: AI Product Management 101: What You Need to Know

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