- July 22, 2025
- FOXITBLOG
The conversation around Artificial Intelligence in product development is often overly optimistic and enthusiastic. While AI’s capabilities continue to expand at a breathtaking pace, a critical distinction must be made: AI is a powerful tool, not a substitute for leadership or genuine human insight. The prevailing narrative, which sometimes paints AI as an increasingly human-like entity, risks leading companies down a perilous path of development that merely reacts to trends and misses opportunities for true innovation.
The AI Illusion: Beyond Human Mimicry
The perceived sentience of AI, where it seems to exhibit intention or rationality, can be deceptive. This phenomenon, according to Brian Root, a fractional chief product officer and product strategist, echoes this, stating, “It is interesting on the face of it. Why we’re even having that conversation, right? Why is AI even being thought of in the context of being a person within other conversations than this? It brings to mind for me a real brief anecdote from way back when I was in school. Travel with me back a solid 20 years, at least. I took a philosophy class from a college professor. Although one of the many things that we debated in that class was effectively not AI, we instead discussed if computers are alive.” The perceived autonomy, like a screensaver turning on by itself, can lead to the dangerous assumption that AI possesses deep insight beyond human capacity. However, this is largely imitation, a sophisticated reflection of predetermined algorithmic inputs. The goal for many AI developers, Root contends, is to make these tools “more lifelike, because that’s frankly what companies who are developing these tools want us to experience.”
When Automation Undermines Innovation
This fundamental misunderstanding of AI’s nature leads to a critical misstep in product leadership: the impulse to simply replace human roles with AI solutions. This immediate response among many product leaders overlooks the true essence of product strategy. Root states that good strategy and products are fundamentally “the result of seeing patterns and then breaking those patterns”. This act of disruption, of taking calculated risks, is precisely what AI, in its current form, struggles with. Large Language Models (LLMs) are designed to identify commonalities and provide answers based on prevalence within their training data. Strategic insight, on the other hand, involves discerning patterns that deviate from the norm, and then connecting disparate ideas in novel ways. This capacity for novel synthesis, for identifying exceptions and forging new connections, remains a uniquely human domain.
The Peril of Mindless Frameworks
An excessive reliance on AI in the development process often results in an emphasis on quantitative data at the expense of qualitative understanding. While data is crucial, a relentless pursuit of incremental gains based solely on measurable metrics can inadvertently devalue unquantifiable, yet vital, aspects like customer understanding. The temptation, as Root highlights, to automate the analysis of customer interactions by processing all calls through AI for efficiency may yield a brief summary, but it strips away the messy, nuanced process of genuinely listening to customers, observing their reactions, and inferring deeper needs from subtleties like vocal tone and pauses. This direct human engagement, Root asserts, is where true pain points and opportunities for innovation are often uncovered.
The uncritical application of frameworks, especially those generated by AI, presents another significant danger. Root cautions against “coming into a situation which you did not thoroughly understand and starting to apply frameworks that may have worked in other contexts without understanding what made them successful, and whether those same underlying criteria are true within the new space that you’re moving into.” AI, lacking true contextual understanding, can readily apply a multitude of basic or advanced frameworks, but it cannot discern whether the underlying criteria for success are present in a new environment. This can lead to the rapid scaling of a poor decision, transforming it into a tremendously damaging outcome very quickly. The inherent agreeableness of AI, where it consistently affirms user input, further exacerbates this risk, failing to provide the crucial critical feedback necessary for robust strategic development. As Root plainly puts it, “I think a lot of us, myself included, have worked at companies that already operated that way pre AI. It’s the place where you don’t tell the CEO their idea won’t work. You just do it, right? Those are not good companies.”
Reclaiming Strategy: The Human Imperative
Moving forward, the successful integration of AI in product development demands a deliberate and focused approach. Instead of broad directives to incorporate AI into every feature, Root advises companies should focus on leveraging AI for tasks with clear, well-defined outcomes. This allows for automation of processes that are traditionally time-consuming, freeing up product leaders to engage in the truly strategic work: “talking to customers more and doing the parts that are really hard to automate, the parts that have always gotten shunted to the side because ‘Gosh, I don’t have time for that.'” By embracing AI as a sophisticated tool for efficiency and augmentation, and by resolutely prioritizing human insight, creativity, and critical thinking, we can build thoughtful, user-centered products with intention and truly unlock the next era of groundbreaking innovation.
To delve deeper into this critical discussion, watch the latest podcast where Brian Root shares his invaluable perspectives.
New podcasts available every Friday.
