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What is an AI product manager?

Last updated

18 April 2024


Dovetail Editorial Team

Reviewed by

Mary Mikhail

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In recent times, it’s impossible to go anywhere online and not be confronted by artificial intelligence (AI) in some shape or form.

Just as robots and automation have transformed the business world during the last 70 years, AI is now at the forefront of technological transformation. Businesses will have to adapt to remain competitive in this new landscape.

AI techniques will even reshape product management approaches. This is a phenomenon that signals greater demand for AI products and that there’s no better time to become an AI product manager.

Learn what an AI product manager is and how to get on track to becoming a part of this exciting transformation.

What is AI product management?

ChatGPT is probably the most familiar AI product to everyone in the business world. It’s a large language model (LLM) tool pre-trained on vast amounts of data. It helps make marketing and customer service tasks more efficient.

AI product management was necessary when OpenAI were developing ChatGPT and continues to be vital while they evolve it into a more efficient and useful tool.

AI product management involves knowledge of AI, deep learning, and machine learning technology. The aim is to develop products like autonomous cars and smart assistants like Apple’s Siri, Microsoft’s Cortana, and Samsung’s Bixby.

New AI products continue to emerge and evolve to transform industries, such as

  • Healthcare

  • Finance

  • Travel and transportation

  • Social media

  • Retail

  • Manufacturing

Businesses need AI product management to get AI-dependent products to the market faster. However, while the technology may be on a soaring trajectory, it will require a flood of AI product managers to enable that to happen.

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What is an AI product manager?

Product managers are responsible for turning a product idea into reality. They define business goals, plan activities, analyze marketing data, and allocate the resources needed to complete the product. They also provide direction, monitor progress, offer solutions to problems, and adapt and adjust the product’s build when changes occur. They are knowledgeable in the relevant technologies and have strong management skills.

AI product managers perform the same duties, but the employees they work with may differ. Additionally, the type of knowledge you need must be suitable for AI products.

As an AI product manager, you may be directing teams that include job titles such as:

  • Computer and information research scientist

  • Machine learning specialist

  • AI researcher

  • Data scientist

  • Data engineer

  • Video game designer

  • Research engineer

  • AI systems engineer

  • AI specialist

The AI-based knowledge and skills you obtain to perform your duties will help you communicate with these team members. They will also help you with the decision-making and problem-solving aspects of your job.

Are AI product managers in demand?

LinkedIn data indicates that job postings mentioning AI or generative AI more than doubled worldwide between July 2021 and July 2023. Other countries, such as the UK, Germany, and France, experienced even more significant increases.

The demand for AI skills is also surging across a wide range of industries. For example, many industries might post jobs listing AI as a required skill for a digital product manager specializing in software tools, apps, or any product used digitally.

AI product manager scope

As an AI product manager, your main goal is to satisfy customer needs and solve their problems with the product you build. To do this, you need to ask the right questions to gain vital customer data. This will help you generate insights to understand the AI system’s objectives and whether the techniques chosen to set it up are necessary to achieve them.

You’ll need to communicate AI-powered specifications to your data teams so they can meet customer requests or deliver solutions. You’ll also have to translate data science language to product development teams, executive staff, marketing teams, and other stakeholders.

Monitoring an AI system’s acceptance criteria is another key component of an AI product manager’s workload. An AI system’s accuracy can be compromised when it’s trained with biased or incomplete data. For this reason, it’s important to continually monitor, test, and fine-tune an AI system’s performance during building and improvement to verify its accuracy.

Education requirements

Some product manager positions require a bachelor’s degree in business management, supply chain and operations management, or marketing. Others may require a bachelor’s degree in their particular field, such as engineering, information technology, or computer science.

Data processing skills, an understanding of statistics, and a working knowledge of data and models can also help AI product managers.

A master’s degree in computer science can give you a better foundation in math, programming, and data science to prepare you for an AI product management role.

Salary and career potential

The average AI product manager salary in the US is $185,602, ranging from $150,000 to $234,000. As demand for this position increases, so may the salary, as evidenced by Netflix’s willingness to pay a machine learning platform product manager between $300,000 and $900,000 in 2023.

Companies dedicated a significant portion of their resources to incorporating AI capabilities when they discovered how AI would fundamentally change how business gets done. These changes include things like how a business grows revenue, handles everyday operations, engages customers and employees, and builds new business models.

Surveys have found that 55% of companies invested in AI as a top-three priority in 2023. Companies will continue to direct 58% more of their investment resources towards AI over other technologies, such as:

  • The Internet of Things (IoT)

  • Virtual reality

  • Advanced robotics

  • Augmented reality

  • Blockchain

  • Quantum computing

  • Neural interfaces

As more and more benefits continue to evolve from AI capabilities, AI product managers can enjoy job security for years to come.

What is an AI ML product manager?

The terms AI and machine learning (ML) may seem interchangeable, but ML is actually a subfield of AI.

ML is a process that allows computers to learn without specific programming or creating detailed instructions for computers to follow. It gives a machine the capability to imitate intelligent human behavior by supplying data, such as numbers, photos, or text. The data the computer receives helps train it to find patterns and make predictions. The more data supplied, the better the computer model’s operation.

This type of product manager focuses on the ML aspects of AI tools and systems. They prioritize algorithm development, oversee training data quality, and ensure computer models created using ML are integrated effectively into the AI product.

How to become an AI product manager

Knowledge of AI technology is important, but you’ll also need non-technical skills, like project management and communication skills.

Here are some things you can do to develop your technical and non-technical skill sets for an AI product management career:

  1. Immerse yourself in an AI-driven company.

  2. Advocate for AI adoption within your current role.

  3. Forge your own path with an AI startup.

Companies like Tesla, iRobot, Motorola Solutions, and others across several industries are AI-driven and need your help as an AI product manager. Other, newly founded companies, like Perplexity AI and Elicit AI, produce products like chatbots and research tools.

Key traits of a successful AI product manager

Understanding technical concepts is a key component of success in this position. You won’t need to know how to perform machine learning yourself, but you’ll need to know the terminology and have a basic idea of how it’s done to communicate the necessary specifications to your teams.

You’ll also need some technical expertise to know if the AI product you are building or improving is behaving as it should and how to make the necessary adjustments when it’s not.

Numerous non-technical traits and skills can contribute to your success. These include the following:

  • Problem-solving

  • Leadership

  • Adaptability

  • Curiosity

  • Analytical thinking

  • Continuous learning

  • Communication

  • Strategic thinking

However, besides having specific technical or non-technical skills, the most important trait for success is feeling empathy for the customer or user. This trait will help you build products that genuinely meet the user’s or customer’s needs and solve their problems.

It’s not enough to create what you envision as a great product. You have to adapt and adjust your vision to build an intuitive, user-friendly, and helpful product that provides solutions.

Top tools for an AI product manager

Unsurprisingly, an AI product manager can use AI tools to enable the seamless, successful outcome of a product’s development. AI tools can help create product roadmaps, identify potential roadblocks, and optimize resource allocation.

You may also need to analyze historical data like development costs and performance metrics.

Here are some examples of tools you might find helpful:

  • ChatGPT for idea prioritization, data management, and launch plans

  • Google Bard’s conversational AI chatbot for answering questions and solving complex problems

  • Missive’s communication platform, which offers streamlined communications and real-time interactions, for effective collaboration with cross-functional teams

Other tools include the following:

  • User flow templates

  • Workflow automation platforms

  • Data analysis assistants

Taking advantage of these tools can enhance your product development success.

Should you become an AI product manager?

AI products are here to stay, and there’s potential for many more. You may want to take advantage of what this field can offer you and your lifestyle.

AI product managers are highly sought after right now and will be even more so in the future.

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