With all the exciting advancements happening in the realm of AI and language models, we are curious about where it's all heading. We're eager to uncover what these models can achieve and excel at or even where they surpass us, whether we're ready or not. There's a lot of buzz, interest, and valid concerns. But one thing's for sure, it's worth our attention, particularly when it comes to answering the question: How can they help us?
We sat down with four senior product people to discuss the topic. We ended up having a fun and inspiring discussion. The fast-developing Large Language Models (LLMs) such as ChatGPT can already do a lot. How far it will go in the future remains to be seen. Below are some key takeaways from our chat.
Learning Accelerator
For product managers, LLMs are particularly valuable as they can quickly process vast amounts of information and present it in an easy-to-digest format, which can significantly accelerate our learning process. By leveraging LLMs, we can gain new insights and perspectives on complex topics, widen our horizons, and help us learn about markets, trends or new frameworks. LLMs are like an untiring sparring partner that allow us to explore various topics and ask questions on the same subject for as long as needed; if this were a person, they might go nuts in the process.
Insights from Data
LLMs excel at analyzing large volumes of unstructured data, such as feedback, customer service tickets, or free-form text in Net Promoter Score questionnaires. By utilizing LLMs to organize, categorize, and summarize this data, we can derive meaningful insights into customer needs and experiences far more efficiently than before. However, just like with a human analyst, it is crucial to provide the LLM context to generate valuable insights from the available data. Our discussion reminded us of numerous instances where the ability to process unstructured data would have saved us significant time. Another reminder was the "survivor bias" that could lead us to incorrect conclusions because of incomplete data.
Asking Good Questions
A questioning mind and the skill of asking questions right are critical for any product manager. Effective use of LLMs heavily depends on it. We have to approach the tasks with a curious mindset and not focus on confirming our assumptions; or biases. Instead, keep an open mind and genuinely want to learn more about the topics. It is essential to validate the given answers and refrain from settling for the early responses given. Instead, we should dig deeper and question what we can to ensure the best understanding.
Decision-making
AI-assisted product management highlights the importance of essential product management skills, particularly critical thinking and decision-making. Just like having a superfast vehicle only helps if we know how to steer it, a lack of critical thinking and poorly formulated questions can lead to bad decisions. Therefore, product managers should continuously hone their critical thinking and decision-making skills.
The Human Touch
Some inherently human capabilities cannot be replaced by AI - at least not yet. Product management success relies heavily on effective leadership, interpersonal skills, and empathy. These skills are crucial for understanding human emotions, interacting with the product team, and building meaningful relationships with customers and stakeholders. We, humans, are always interpreting non-verbal cues and analyzing the words left unsaid. While AI can provide general information and guidelines, genuine empathy and emotional connections can only be achieved through human interaction..
In a nutshell
LLMs have opened up new opportunities for product management, empowering us to learn faster, analyze data more efficiently, and make more informed decisions. This capability can help us create successful products that deliver customer value. By combining the capabilities of LLMs with our vital skills as product managers, we can navigate complexity more effectively and provide outstanding results. That includes the ability to devise better strategies, make faster and better improvements, and analyze complex data with greater accuracy and speed. Ultimately, this enables us to make data-driven decisions that lead to better product outcomes and more substantial business results.
So let's keep asking questions and be curious about our untiring new sparring partner and friend.
Annika Koli Pouria Kay Anna Katariina Kindahl Paavo Punkari