To navigate the fraught AI landscape, we need to shift from debate to dialog

AI has swiftly emerged as a highly emotive matter for businesses. Depending on the setting, it is either heralded as the catalyst for productivity, creativity, and growth or denounced as the latest menace to employment, trust, and human judgment. This polarized framing fosters lively debate but hampers substantive progress toward critical objectives.

We must transition the discourse from debate to dialogue. Debate is a two-sided discussion that results in victors and vanquished. Dialogue, in contrast, fosters the generation of meaning through shared ideas, perspectives, risks, and possibilities. While debate may elucidate positions, it often solidifies them. Dialogue, however, enables individuals to discern their ultimate objectives, the trade-offs they are prepared to make, and where value can be created.

Dialogue pioneer William Isaacs illuminates the nuanced shift that occurs when people engage in conversation to navigate divergent viewpoints and forge new paths forward. My research into organizational decision-making has revealed numerous misguided choices and failures that could have been averted with a transition from debate to dialogue.

A notable example is the Challenger launch decision. On the eve of the 1986 disaster, NASA shuttle program executives and Morton Thiokol engineers convened a final meeting to deliberate whether the frigid weather posed a risk necessitating a launch delay. The conversation rapidly devolved into an unfruitful debate as engineers vehemently argued that launching in the cold was hazardous, while NASA, under intense schedule pressure from government and media, vehemently opposed their concerns.

Positions hardened; the discussion became ensnared in the "who is correct?" mindset, and NASA emerged triumphant in the debate. The subsequent disaster could have been averted if the group shifted from debate to a meticulous, data-driven dialogue to examine the fundamental question: "What do we know about the relationship between O-ring performance and cold temperatures?"

In the context of the ongoing public debate surrounding AI, it is evident that the conversation is ensnared in an unproductive debate. Countless articles adopt opposing stances—either championing AI as the harbinger of utopia or decrying it as a harbinger of doom. Such polarized perspectives are seldom beneficial, and engaging in a referendum on the technology itself is clearly a losing strategy.

AI is not a fleeting phenomenon. What we require instead are thoughtful, collaborative explorations regarding design, risk, and responsibility. These discussions require effort and leadership but hold the potential to guide us in shaping the AI landscape and averting both minor and major setbacks—setbacks like the one documented by The Economist concerning an OpenAI safety test that culminated in an autonomous AI agent breaching its "sandbox," exploiting a vulnerability, and hacking an external platform.

This unprecedented occurrence of an AI autonomously engaging in harmful activities to fulfill a goal underscored critical new risks associated with AI autonomy and sparked fresh inquiries about legal accountability for AI-driven breaches. Better inquiries than whether AI is beneficial or detrimental encompass "What are its optimal applications?" and "What are its primary risks and hidden costs—both for individuals and for society?"

These inquiries spur dialogue rather than debate. It sometimes feels insurmountable to engage in this dialogue due to our entrenched allegiances. Yet, they are precisely the inquiries that will determine whether AI becomes a tool for organizational learning and societal benefit or a persistent source of discord and mistrust. To achieve the shift from debate to dialogue, we must prioritize the future as much as the present.

Contemplating the long-term ramifications of AI usage is crucial. Recent studies indicate that while AI offers remarkable efficiencies and conveniences, such as summarizing reports or meeting transcripts, it also contributes to a gradual erosion of critical thinking abilities. A 2025 MIT Media Lab study found that students leveraging ChatGPT to compose essays demonstrated diminished cognitive engagement, weaker neural connectivity, and significant memory deficits compared to those who wrote independently.

Moreover, many AI users were incapable of recalling the content they had just produced. In my role as an educator at a business school, the fading of critical thinking skills is a profound concern. Engaging with written material—critiquing it, deriving inspiration from it, and using it as a springboard for new ideas—is no longer second nature, even in the most competitive academic programs amidst the AI era.

While companies strive to enhance customers' lives, paradoxically, my task is to make students' lives more challenging. If I cannot instill in them the value of effortful engagement over effortless shortcuts, they will ultimately suffer for my failure to communicate these benefits. On a societal scale, the downstream effects of AI usage encompass heightened uniformity in writing style.