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We recently had the pleasure of hosting a fascinating AMA that delved into the topic of Artificial Intelligence (AI) and product management. Emily Tate, Managing Director at Mind the Product, was joined by Chris Butler, Group Product Manager – Machine Learning at Google, who provided valuable insights into the current landscape of AI, its applications in product management, and the evolving role of product managers. Watch the video in full, or read on for their key points.

Navigating the AI age in product

As it’s been a year since ChatGPT’s release date on 30 November 2022, Chris began by offering insights on navigating the intersection of AI and product management. Irrespective of AI, he emphasised the importance of product managers concentrating on addressing customer issues and making effective decisions, regardless of the technological advances.

Chris further noted the inevitability of emerging technologies in the market and suggested a proactive approach to adaptability. Experimenting with new LLM models can help us explore their potential advantages in our roles. According to Chris, “We’re currently in the hype stage of AI; the subsequent phase involves integrating AI into products that genuinely address human problems.”

The rise of an AI product manager

Chris argued that the term ‘AI product manager’ is redundant. “Right now, because of the rise in Machine Learning, the role sounds so much more interesting, but a decade from now, the role won’t exist; product managers will just be working on machine learning technologies,” Companies are starting to realise that it’s more about the types of things that you own, over the specific technologies that you are working with. Chris clarified, “It’s not about a role profile; we’re essentially continuing the core responsibilities of product management within an AI product,”

The evolving product landscape

“I don’t foresee AI replacing product management roles,” Chris clarified when discussing the impact of new LLMs. Initial effects may be prevalent in professions like full-stack development. Nevertheless, the role of a product manager remains indispensable for engaging in strategic discussions, presenting arguments, and fostering innovation. Genuine decision-making, he emphasised, remains inherently human, grounded in relationships with real people.

Despite this, Chris pointed out that AI has the potential to enhance our work by synthesising conversations and identifying potential issues with our products. He suggested incorporating AI into our toolkit to broaden our perspectives to initiate projects from scratch, such as crafting an outline for a PRD.

Looking ahead, Chris envisions a future where human and machine teams collaborate extensively. “In the long term, machine agents could contribute valuable data and information, expanding the decision-making landscape,” he noted. “Ultimately, it will be the responsibility of the human or a small team to assimilate the data and make informed decisions.”

Privacy implication with product

A conversation raised throughout the session was privacy concerns about user and product data. Chris said that companies can use these without risk if they create and own LLM models. However, he said, “Be wary of how you use confidential information and consider how it might impact your product in the future if data and security breaches occur when using third-party models,” he said.

When dealing with new technological models, Chris stressed being aware of how data is collected and you are adhering to how the laws are changing over time. Additionally,  a collaborative relationship with legal and security teams is critical, noting that they play a crucial role in raising awareness of potential risks and can add significant value to the overall process, as highlighted by Emily.

Non-technical product managers

According to Chris, navigating the new AI age doesn’t require intense technical proficiency for product professionals. He emphasised that the key lies in developing a shared language across teams. Instead of prioritising technical prowess, Chris said, “Product managers should focus on managing and facilitating conversation between highly technical individuals and those less acquainted with technical knowledge.”

“Companies stand to gain from non-technical product managers who can bring a unique perspective, asking the bigger questions that lead to the development of products rather than creating something for its technical appeal,” he noted.

Continuous adaptation

The landscape of AI and machine learning is continually evolving. Product managers must stay adaptable, embracing new technologies while focusing on core product principles such as effective communication, problem-solving, and decision-making.

Did you watch the talk or have any further thoughts on AI’s impact on product management? Let us know in the comments below.

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