How to navigate the explosion of AI tools aimed at product managers

According to a 2024 Forbes Advisor poll, the vast majority of people (79%) in the UK are already using generative AI, such as ChatGPT, to help them with their work while one in six UK organisations have embraced at least one AI technology.

To give an example of the impact AI is having in workplaces – after a 10-week trial of using a computer vision technology, Marks & Spencer reported an 80% reduction in warehouse accidents. So, with most people agreeing that AI adoption at work is here to stay and that it will become a significant feature of many of our jobs (if it isn't already), product mangers are finding themselves needing to embrace it and learn about it.

Here Nick Jemetta, an AI Product Coach and Human Skills Speaker, shares some key tips with Mind the Product on how product managers can navigate the explosion of AI tools and the constant pressure hanging over them to integrating them into their workstream quickly. 

Be tech and tool agnostic – at first

When asked about how he is navigating the explosion of AI tools, Nick says: “I start with first principles and practices which should be technology and tool agnostic!”

Nick says before even starting to make a plan around which AI tools to consider, you should ask yourself some key questions about your organisation and/or your work:

1. What is our vision and strategy? 
2. What are our goals? 
3. What outcomes do we need to realise to achieve our goals? 
4. What bets are we placing to move the needle on our outcomes? 

Nick explains: “By first asking these questions, PM's are then in a position to ask 'How might AI improve the speed and quality with which we progress our outcomes?

“AI won't always be the answer but when it is, I always advise adopting an experimental or pilot mindset. Choose one high value use case and a tool you think can solve for that use case. Run an experiment, measure the impact then either continue, pivot or move to the next use case."

Set healthy boundaries

How can product managers set healthy boundaries around adopting new technology like AI without falling behind? And what about choosing which frameworks to use when evaluating which AI tools are worth your time?

Nick said: “Every PM knows themselves better than anyone else does. How much friction do you feel when it comes to AI? Is it exciting or overwhelming? Are you ready to embrace AI or are you resistant?

“Depending on your answers your approach will be different. If you're excited and ready to embrace, the boundaries you put in place will need to contain and focus that energy towards finding genuine use cases for AI that help you achieve specific outcomes (at work or in your personal life). 

“If you feel overwhelmed or resistant, you will need to push past the resistance and force time into your diary where you explore one very small slice of the AI landscape perhaps to automate a simple but laborious task.”

When it comes to filters and frameworks, Nick advises to always return to those first principles, in particular what outcome you want to achieve and how you'll measure success. 

Nick said: “Documenting your current workflows is an effective strategy to reduce what you hold in your head and to visualise where there might be opportunities to automate, iterate or evolve particular stages in the workflow. I also recommend doing some lightweight research on the data privacy and security of any tools you use. You need to know how data will be stored, where and to who it will be shared and whether you should refrain from sharing sensitive company or personal data.”

Advocate for realistic timelines

So how can product managers push back or slow down AI adoption responsibly and advocate for realistic timelines while still being seen as innovators?

Nick recommends: “Articulate your principles as lenses through which AI adoption should be evaluated. AI is no different from any other technology in the sense that it should be used when it meaningfully solves a problem or makes a solution possible in a way that no other technology can (either because it's faster, cheaper, more secure, more scalable, more future-proofed, or a combo of these).

“Being realistic with timelines means doubling down on discovery to surface assumptions and test hypotheses so that risks become better understood and confidence increases. Overindexing on discovery also enables teams to innovate and ship value continuously, reducing the pressure on shipping to specific (and often arbitrary) dates.”

Nick talks about mentally sustainable product development as being “largely influenced by the clarity of the product strategy and team ways of working”. He said product managers should ask the following questions to achieve this in the age of AI:

1. Have Product Leaders been intentional and explicit about the choices they've made?
2. Is it clear what strategic problems teams should prioritise and which problems teams should not prioritise? 
3. How do Product Leaders respond to “shiny object syndrome" where leadership gets excited about a new problem or opportunity without properly considering the strategic context and the cost to switch focus? 
4. Who is considering the cognitive load of each team and the effectiveness of team topology to fairly distribute that cognitive effort?

Nick continued: “PM's can remain innovative whilst keeping product development mentally sustainable by getting confident saying 'No' and integrating continuous innovation into the fabric of how they work with their teams. For example, regular hackathons encourage innovation and collaboration, and can be focused on exploring a particular AI use case."

Navigate ‘AI pressure’ effectively

So, ultimately, how do we reframe ‘AI pressure’ into a healthier, more strategic conversation?

Nick said empathy is key.

He elaborated: “Put yourself in the shoes of your stakeholder – get curious. Why might they be feeling 'AI pressure'? What do they hope to achieve with AI which they can't currently? How might I be able to work with them to convert this pressure into real learning and results?”

Nick said it’s important for product managers to embrace continuous learning and always be thinking of ways to feed insights developed from this into a strategy or set of principles that “guide the role of AI in our products, our product ways of working and our wider organisation”.