Creating Intelligent Experiences: The Role of AI for Product Managers

The topic of artificial intelligence (AI) is on everyone’s lips. It still remains one of the current product management trends. “The genie is out of the bottle,” as they say, and there’s no way you can squeeze it back into it.

Are you excited or uncertain about what to do with AI in product management (PM)? In fact, 92% of product leaders expect a lasting impact of artificial intelligence on the PM landscape.

What happens when these two abbreviations, AI and PM, collide? Is AI influencing PM that much? What are its essential functions in it? More importantly, how can you take advantage of AI to manage products more effectively?

Answer these questions step by step.

The Impact of Artificial Intelligence on Product Management

As you’re reading this article, AI is already making irreversible changes to the terrain of PM. Let’s see how exactly and start with the evolving AI product management that expanded the list of today’s product management buzzwords.

The Evolution of AI Product Management

Based on IBM’s research, product managers appear among the top ten user groups of AI. Project professionals also predict a noticeable rise in adopting AI for handling projects. The number of those powered by AI is expected to jump from 23% to 37% in the forthcoming three years.

A rapid AI revolution gave rise to a new, multi-dimensional area in PM, similar to fresh, out-of-the-oven disciplines like product-led growth.

It is AI product management, also known as AI PM. It refers to using machine learning (ML), natural language processing (NLP), and other subsets of artificial intelligence for building, launching, operating, and improving products.

It also spurred the appearance of a safe career direction for product managers in the modern digital era. Namely, the path of an AI product manager. Consider this. The number of AI product manager job openings on LinkedIn grew from 13,558 to 26,269 in less than one year (check the graph below).

Source: Toptal.com

Netflix, for instance, has recently opened an AI-focused PM position with a salary range of $300K to $900K.

Why are companies looking for AI and ML awareness in the skillset of a product manager and hunting for the keys to unlock the full potential of artificial intelligence?

Due to the numerous perks it offers, of course. 

The Benefits of Artificial Intelligence for a Product Manager

AI can significantly empower you on your PM journey. It makes an invaluable contribution to the following:

• Ideation and visual roadmapping
• Streamlining workflows and prioritizing tasks
• Achieving a cost- and time-efficient product development
• Collecting customer feedback
• Enhancing customers’ experiences
• Leveraging predictive analysis
• Determining potential risks and making smarter, data-driven decisions

6 Tips for Product Managers to Get the Most From AI

Follow these recommendations from business owners and product leaders.‍

1. Set your AI budget

To begin with, you should know that 51% of organizations plan to increase investment in artificial intelligence by 10% in the upcoming years.

What about your company? Do you have a dedicated budget for AI product management solutions?

“A well-thought AI budget,” says Anthony Martin, Founder and CEO of Choice Mutual, “goes a long way in reaching your PM goals.” He adds, “No matter whether you’re only getting started with artificial intelligence and machine learning for product management or already trying out AI/ML, you should begin budgeting small but consistently for it. Your budget for AI will largely depend on the business size, revenue, objectives, and industry-specific needs.”

In general, the smaller the revenue, the less money companies lay out on AI. 26% of decision-makers report an annual budget of less than $500,000 allocated for artificial intelligence. Some larger enterprises surveyed by Omdia plan to spend as much as $2 million or even $5 million on AI in 2023.

In times of economic uncertainty, you can always turn to some inexpensive AI resources and instruments. Find them all listed below.‍

2. Pick the right AI tools for your needs

Take this piece of advice from Eric Mills, Owner of Lightning Card Collection: 

“As a product or business leader, you can’t open the box of AI advantages for product management without preparing an AI toolkit that caters to your specific requirements. You might also need to diversify it to address every aspect of your work: ideation, designing and prototyping, strategizing, etc.”

Here’s a ready-made collection of AI tools for product leaders and their particular needs:

• For brainstorming ideas: ChatGPT
• For software prototypes: Visily.ai
• For product discovery, team collaboration, and development strategy – Zeda.io
• For productivity and time-tracking: Timemaster.ai
• For product descriptions: GetGenie.ai
• For neuromarketing: Brainvine.ai
• For customer self-service: Tidio

You can rely on any of those or all of them at once to ace product management and customer success management. Why not start your free trial with Zeda.io right now and see the power of artificial intelligence in action?

3. Let AI help you hear your customer’s voice

Understanding your customer is of the utmost value in product marketing and management. When you get a better sense of customers’ feelings, wants, and needs, you can develop your product precisely in line with those.

Stephan Baldwin, Founder of Assisted Living, provides an example from the healthcare industry:

“Let’s imagine you develop an application for healthcare professionals. You would definitely want to know how they feel about using your medical app, why they have difficulties managing electronic prescriptions or patients’ records, or why they delete it right after downloading. That’s when accumulating and analyzing in-app user feedback becomes vital. And that’s when artificial intelligence should be involved.”

Just for the record, 25% of downloaded apps are used only once and then get abandoned. If that’s one of the cases with your app, the moment has come for AI to be called on stage. Even when you don’t see any obvious issues but want to come closer to your customers and hear their voices more clearly, consider some practical ways of collecting feedback from users:

• Interview
• Focus group
• Feedback form
• Live chat
• Heatmap
• Usability test
• Survey
• Customer portal, etc.

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Using Zeda.io’s AI system, you can capture feedback from multiple sources and centralize it in one place. After that, use custom filters for categorizing and clustering the collected data into groups for further customer feedback analysis.

4. Elevate personalization to the highest possible level

To develop more personalized products with AI, you should start with creating your user personas based on:

• Geography (climate, country, time zone)
• Needs (preferred features and functions)
• Demographics (gender, income, age)
• Psychographics (personality type, motivations)
• Behavioral factors (user behavior, purchase frequency)
• Firmographics (industry, company size, executive title)
• Technographics (technology stack, preferred communication tool)

However, segmenting customers into groups isn’t enough. You should go beyond that and reach the next level. It is hyper-personalization.

“Product hyper-personalization is the highest possible level of personalization you can achieve only with AI,” says Jerry Han, CMO at PrizeRebel. “It implies using real-time data in combination with artificial intelligence. By merging these two, you can enable smoother product adoption and customize user experiences with personalized trials, messages, rewards, etc. For example, AI can generate a personalized bonus or individual discount code to every user on your website or in-app, based on the real-time information it receives,” he explains.

Likewise, artificial intelligence can help you create a personalized pricing plan or product recommendation for every customer on the spot.

Froomle.ai is an excellent example of an AI-powered recommender system for eCommerce products.

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6. Beware of legal risks

Welcome to the dark side of artificial intelligence for PMs.

Mark Pierce, CEO of Colorado LLC Attorney, says: “AI-driven legal issues may result in devastating reputational and financial consequences. Not to mention that they ruin customer trust.” He enumerates four major cases when AI can expose you to legal trouble:

• IP rights infringement
• Disinformation
• Discriminatory statements
• Data privacy violation

As for the latter, every AI tool you use must comply with such laws as the California Online Privacy Protection Act (CalOPPA) in the US and the General Data Protection Regulation (GDPR) in the EU.

Zeda.io, for example, takes the data protection rights under GDPR and CalOPPA seriously. Check its Privacy Policy page.‍

7. Foster a cybersecurity-first environment

From data poisoning and model theft to other cyberattacks on AI, poorly protected artificial intelligence can face tons of vulnerabilities and threats.

Delta Airlines, for instance, experienced a cyberattack on its website-based AI chatbot in 2017. It resulted in compromised and leaked payment information of Delta’s customers.

“A lack of cybersecurity protection is the primary reason that allows cyber-criminals to hack AI,” notes Volodymyr Shchegel, VP of Engineering at Clario. “That is why when using artificial intelligence in product management, you should make sure the system regularly undergoes third-party penetration testing, model obfuscation, and multi-layered threat protection.

Besides, product managers can organize IT security training for their teams to educate them about social engineering, spam, and other cybersecurity risks.”

Examples of Using Artificial Intelligence in PM

At every stage of the product management process, you can tie AI to PM. Take a look at some examples of how others did that:

• Content Beta recorded product onboarding videos and cut the video creation costs by 15% with Synthesia.io (case study).
• Netflix uses AI algorithms to create tailored movie recommendations (read more).
• The Muse leveraged Blueshift to hyper-personalize emails and saw a 200% increase in site visits (case study).
• iRobot used Pendo.io to segment in-app users and tailor feature launch announcements, reducing engineering efforts by 75% (case study)
• Nimble built more precise product roadmaps and increased collaboration with Zeda.io (case study).

High Time to Merge AI with PM

As you have seen above, AI innovation is worth the hype. Artificial intelligence offers unprecedented opportunities for product managers.

But are you AI-armed to the fullest?

Make product management more straightforward and more efficient with Zeda.io’s AI.

Try it here for free, or book a demo to see how it works.

Brooke Webber is a passionate content writer with a love for storytelling. Brooke has 5 years of experience in crafting compelling narratives that resonate with audiences across industries. Total coffee addict. During her spare time, she immerses herself in literature.