Product School

The Future of AI in Product

Carlos headshot

Carlos González De Villaumbrosia

July 27, 2023 - 7 min read

Updated: May 6, 2024 - 7 min read

Artificial Intelligence (AI) is no longer the stuff of sci-fi fantasy. If every company has become a software company, then every company has the potential to become an AI company. Product teams will be at the forefront of this change, developing, updating, and marketing these changes across sectors. The implications are vast and game-changing. Today, let's delve into what the future may hold for AI in product.

Editorial note: This post is based on a panel discussion at ProductCon London 2023. The participants of the panel were Carlos González De Villaumbrosia, Founder & CEO of Product School (Moderator), Jessica Hall, CPO at Just Eat Takeaway, Yi-Wei Ang, CPO at Delivery Hero, talabat, and Subhayu Ghosh, VP of Product and Growth at Tier Mobility. You can watch the full discussion below.

Applications of AI in product

Blog image 1: The Future of AI in Product

Just as we've witnessed with Web 3, NFTs, and cryptocurrency, AI is surrounded by a whirlwind of anticipation. While the initial hype is focused on the novelty, what truly matters is the real, practical applications of AI, especially in product. Innovative companies are already dipping their toes in AI waters to explore ways it can enhance customer experiences.

AI's impact isn't confined to just text analysis. The scope is far-reaching – from geospatial imaging to cancer treatment, and of course, creating software products. By training teams to effectively engage with AI and providing opportunities for hands-on experience, organizations can tap into its vast potential and discover new ways to improve efficiency and develop talent.

Product people have a wealth of opportunities to leverage AI for enhancing their work processes and delivering better customer experiences. Here are some examples of how AI can be applied:

1. Personalized User Experiences

AI can analyze vast amounts of data to understand customer preferences, enabling product teams to tailor user experiences. By implementing AI, you can create a product that automatically adjusts according to the user's behavior, preferences, and anticipated needs.

2. AI product analytics

Predictive analytics is one of the most exciting applications of AI product analytics. Product Teams can use AI to analyze past behavior and predict future actions, and make suggestions for experiments. 

For instance, AI can help identify patterns that might indicate when a user is likely to stop using a product, allowing the team to intervene proactively and retain the customer. AI can also analyze historical data and user behavior to predict what kind of messaging will be most effective for different customer segments.

In terms of product performance, AI can automatically track, analyze, and report on KPIs and OKRs, giving product people a real-time overview of their efforts and freeing up time for more strategic tasks.

In addition, AI can help with external data. It can scan social media, reviews, and other sources of customer feedback to identify public sentiment towards a product, helping Product marketers adjust their strategies accordingly.

3. User segmentation & customer journey mapping

Blog image 2: The Future of AI in Product

AI can group users based on shared characteristics and behavior, allowing Product people to target different user segments with customized features or enhancements. AI can also track and analyze customer interactions across multiple channels, helping create more precise and effective customer journey maps.

AI capabilities like natural language processing and image recognition can provide voice and visual search options, enhancing user interaction and engagement with the product. This in turn can translate into more user data that you can then use to improve the product.

5. Cross-functional engagement

Experimentation is key when it comes to AI. Not only should Product Teams dabble with this technology, but all business functions should engage with it. Using AI tools to discover problem spaces before developing solutions can lead to more informed and effective decision-making. 

Product AI trailblazers: real examples from product teams

Blog image 3: The Future of AI in Product

Many companies, both big and small have started experimenting with AI in their products. Here are some you’re familiar with (and most likely use!):

1. Spotify: personalized playlists and recommendations

It’s not a new year without everyone posting their Spotify Wrapped on their social media. And Spotify uses AI to deliver this personalized experience. It applies machine learning algorithms to analyze user behavior, including song preferences, listening history, and even the time of day users listen to certain tracks. From this, Spotify generates personalized playlists and recommendations.

2. Netflix: content recommendation

Netflix was one of the earliest adopters of AI, using it to drive its content recommendation engine. By analyzing viewing history, ratings given by users, and even the viewing patterns of similar users, Netflix's AI creates personalized content recommendations. This helps users discover new shows and movies they might like, enhancing user engagement and retention. Moreover, Netflix also uses AI for optimizing streaming quality and even predicting which shows or movies will be successful based on historical data.

3. Amazon: customer experience and operational efficiency

Amazon applies AI in multiple facets of its business. Its recommendation engine is one of the most well-known applications, but Amazon also uses AI for fraud detection, warehouse automation, and dynamic pricing. Furthermore, Amazon's voice assistant, Alexa, uses AI and machine learning for natural language processing, which is what enables it to understand and respond to voice commands from users. 

Each of these examples demonstrates the potential of AI to enhance product functionality, personalize user experiences, and improve operational efficiencies. Machine learning algorithms enable companies to analyze large volumes of data and generate insights that humans might not readily perceive. And with AI becoming more accessible, it’s no longer just these giants who can use AI to deliver more value to their users and drive business growth.

Dealing with AI doubts

Blog image 4: The Future of AI in Product

AI has raised some eyebrows, primarily due to fears of job losses and potential bias embedded in data sets. However, it's crucial to understand that AI is not a threat but a tool to enhance our capabilities. As this technology advances, it's our responsibility to continually adjust and correct potential biases, ensuring AI serves as an impartial, fair assistant.

Skepticism surrounding AI isn't surprising, or even unwarranted. After all, technologies like virtual reality, NFTs, and blockchain haven't quite lived up to the hype. But what sets AI apart is its accessibility and ability to complement existing work processes, making it far more practical and applicable.

Yes, AI has its limits. And at least for now it can’t replace many key human skills. But Product Teams can use it to complement their human strengths such as vision, connection, and culture building by leveraging its strength in processing large databases. The future is about coexisting with AI in a win-win relationship.

Predictions for AI in product 

Looking ahead, AI is set to become more accessible and integrated into our everyday lives. Expect to see a rise of services catering to specific tasks like reducing customer service response time, detecting fraud, and more. Also, the advent of product-as-a-service models that embrace APIs and instant plugins will enable small cross-functional teams to unlock extreme potential.

In five years' time, we'll likely interact with AI daily. The key skill we'll need to develop is learning how to effectively interact with AI and incorporate it seamlessly into our operations. Tools like Github’s Copilot are already aiding this process, marking the beginning of an era where AI is not a separate, specialist subject, but a part of our everyday products and services. 

Learn more about the future of AI in product

Prepare your product team for the future

AI is poised to reshape the future of product. To stay ahead of the curve, it's critical to train your team to navigate this AI-infused landscape effectively. At Product School, we offer custom product training to align your team, upskill them, and set your organization up for success in this exciting era. Our training programs are flexible, designed to integrate seamlessly into your workflow, ensuring minimal disruption while maximizing impact. Join us today and be a part of shaping the future of AI in Product.

Updated: May 6, 2024

Subscribe to The Product Blog

Discover Where Product is Heading Next

Share this post

By sharing your email, you agree to our Privacy Policy and Terms of Service