Unless you’ve been living under a rock or in a cave chances are you’ve been inundated with posts, memes, and all sorts of information about AI over the last year. Whether it’s changing hiring practices or replacing jobs, everybody seems to have an opinion on the technology and its global impact. There are a significant number of doomsday activists but, equally those who think it’s all a lot of hype. Whatever the case may be, there’s no denying it has got a lot of humankind waking up and thinking about what the future will look like and how they need to try and navigate this new, AI-driven world.
The big boys of AI
Enough has already been mentioned about the history and evolution of AI not to warrant further discussion; however, the value that it can potentially bring across all industries, sectors, and fields is truly significant. Today’s generative AI is the latest advancement in artificial intelligence and is capable of producing a variety of content types (text, audio, video, etc.) in a matter of seconds. It does this by leveraging neural networks, which are more complex than traditional machine learning (ML) models. Some well-known examples of include:
- ChatGPT
- Google Bard
- LLaMA AI from Meta
However, it must be noted that the use of AI across many walks of life is not new. From way back in the 1960s/70, research into speech recognition and natural language processing (NLP) was already being done, which paved the way for digital assistants like today’s Siri and Alexa. Interestingly, AI applications at the time were also already being used across factory floor assembly line work, basic medical data-driven patient health diagnosis, as well as playing games at a competitive level!
Hype vs. reality
Within business, AI has already been put to use for many years. From automation of repetitive, data-heavy tasks and chatbots for enhanced customer service, to personalized content and product recommendations like those used by Netflix and Amazon. However, all of this must be taken with many spoons of salt. Despite generative AI being heralded as a potential life-and game changer, we need to separate the reality from the hype. Remember, technology continues to evolve, and though we may well be at the cusp of a huge technological revolution, it’s worth noting that we simply don’t know enough. Potential and hype are all well and good but the reality may be very different. Remember cloud computing and SaaS (software-as-a-service)? In their infancy they were all the rage with many similar utterances being mentioned. But now? Well, not so much. In fact, the fact that cloud adoption has reached a level of maturity and distance from when it started has also led to a better understanding about its true potential and how it fits into the entire technological landscape. The same could be said about AI.
AI in product management
So how does AI fit into product management? Will PMs lose their jobs? And will the entire industry spin on its head?
Well, the answer to the last two questions is ‘no’.
But let’s look at the first one. Undoubtedly AI can play a significant role in product management. Some of these include:
- Automating data-driven tasks
- Usability testing
- Writing product specs, collateral; use cases for content and marketing
- Leveraging customer feedback
- Performing market/competitor research
- Crunching data to gain insights
Of course, these roles can increase efficiency, better streamline processes and time, and add potential cost savings, as well as provide PMs with more time to spend on other, “creative” tasks.
For those PMs already hitting the panic button, it’s time to take stock and embrace the power of AI. Some ways the two can work together could be by creating product prompts to help ideate and build better user personas, stories and product descriptions. AI can also support with product iterations and feature prioritization as well as enable faster testing, feedback, and implementation. Predictive forecasting and models driven by AI tools can further lead to better business decisions and more personalized customer experiences. Thus, any future PM-AI partnership could potentially yield better business results if used appropriately.
AI is also not just helpful in saving time and carrying out tasks at speed; it can also be used to better determine your product strategy and support better product positioning. By deep diving into customer needs and requirements (research, analysis and insights), AI can be beneficial across the entire product development phase.
Don’t put all your eggs in the AI basket
PMs, all of this doesn’t mean you can sit back and let AI do all the work. The human element is still required. And of course, AI is far from fool-proof. There are still many issues surrounding data security, implementation costs and staff training, as well as AI’s innate biases, which are still prevalent. All of this means PMs must stay on top of the technology and continually monitor its progress and look for – and overcome – possible gaps or deficiencies within it. Its good practice to set realistic goals and objectives at the onset of implementation rather than letting AI forge its own path. With time and practice, AI can be a great asset to product managers. So don’t lose sleep over becoming redundant, at least not just yet.
The future is here and now
Generative AI is here to stay — and there’s no way to ignore it. For a technology that is predicted to add trillions of dollars to the global economy, product managers need to find the best methods to work with it. Though still very much in its infancy AI has huge potential. But this needs to be distilled into a form that best suits humans and businesses. The AI hype may be too much today but let’s learn to embrace its current reality.