«Common sense is the least common of the senses.» Attributed to Voltaire, this phrase emerged from the Enlightenment, the movement that consecrated reason and observable evidence as pillars of human thought. Three centuries later, its relevance is a sad reminder of how far we remain from that liberating ideal, especially in corporate boardrooms.
Far from a philosophical debate, this phrase encapsulates an operational reality: common sense, logic and the understanding of evidence are, frequently, the first casualties in decision-making. Some weeks ago, this maxim materialized in raw form in a century-old transnational company fighting for its survival. In a critical meeting, the cold analysis of one department — focused on cutting labor benefits to generate vital savings — clashed with the unreflective response of others: «let's cut one, but compensate with another.» There was no bad faith, only a systemic inability to grasp the main premise. The dialogue of the deaf ended, as it usually does, in the politically correct capitulation of the «let's agree to disagree»: an elegantly framed failure that the company will pay dearly for in the medium term.
This is not an anecdotal problem but symptomatic of a larger dynamic. «Common sense» applied to business — that amalgam of logic, experience, empathy and conciliation — is irremediably clouded by bias, corporate politics and entrenched mental frameworks. Faced with this human inability to transcend ego and bias, a radical question emerges: could Artificial Intelligence, far from being a cold tool, stand as the «algorithmic Socrates» that restores to the corporation the common sense it has lost?
Resistance to this idea commonly disguises itself as the «intelligent fear of being replaced by machines.» But this is not a matter of intelligence; it is one of ego, bias and the inability to separate personal identity from the objective evaluation of ideas. The true fear is not of the machine, but of the mirror that confronts us with our own obsolescence and the Darwinian necessity to evolve.
What is the root of people's inability to «detach» from their position lacking common sense and be unable to grasp the logic of situations? Upon analyzing the case, it becomes evident that the root of the problem is not a single factor, but a perfect storm of cognitive biases and human limitations that feed on one another.
First, there operates a deep attachment to the status quo — the «we've always done it this way» — that prioritizes the comfort of the known over the cold data of reality. This conservatism is potentiated by a «vested rights» mentality, where a benefit is perceived as an inalienable right, clashing head-on with the cold logic of corporate survival.
This dynamic is aggravated by a fundamental cognitive inability to grasp the real substance of the matter, since a professional title and many years of experience are not synonymous with critical thinking or deep professional commitment. Many operate on «autopilot,» applying learned recipes without the systemic analytical capacity needed to connect the dots.
Yet underlying all of the above is an even more fundamental limitation: the absence of transformational leadership. The true leader is not one who defends their position to the hilt, but the architect of sustainable human capital. What we often find instead is an executive who acts as a «bishop» on the corporate chessboard: their mobility and status confer the privilege of evading the consequences of their poor decisions, externalizing the cost to the organization and its subordinates.
Faced with this diagnosis, the solution emerges: AI as a reality facilitator. Its fundamental value is not automation, but the capacity to perform cold, systemic, scenario-based analysis, guiding decision-making, evaluating and monitoring results, freeing entirely from the emotional short-termism and identity biases of individuals.
Imagine the meeting with an integrated AI tool:
1. The Finance Department presents its proposal to cut benefits «X» for savings «Y».
2. Human Resources rejects it under the premise of «we need to compensate with another benefit.»
3. Instead of a dead end, the AI is consulted.
4. The AI projects data-based scenarios: Scenario A (Status Quo): «Probability of a 15% staff cut in 18 months: 85%.» Scenario B (Cut): «Probability of cut: 25%. Gains 18 months of financial breathing room.» Scenario C (Compensation): «Net savings: zero. Probability of cut: 82%.»
Faced with the perfect tsunami of biases, egos and corporate strategic myopia, Artificial Intelligence should not aspire to be an oracle that dictates solutions from a glass tower. Its true power lies in being able to operate as the ultimate facilitator of human reason. It stands as what we might call an «algorithmic Socrates»: an entity that does not offer answers, but formulates the incisive questions that uncover contradictions and force an honest confrontation with reality.
AI should be neither passive nor active, but contextual and strategic. Its intervention should feel less like an order and more like the revelation of an inevitable logic. AI does not state the answer; it formulates the right questions at the exact moment to guide humans to arrive at the logical conclusion themselves.
The AI intervenes with a dialectical move:
«To assist deliberation, I need the team to define:
Question 1: Is the primary objective of this measure to achieve net savings or to maintain the current level of employee satisfaction?
Question 2: If the objective is both, what is the relative priority? Savings (70%) and satisfaction (30%)? 50/50?
Question 3: Is the HR department willing to formally accept a high probability (80%) of future staff cuts in exchange for maintaining job satisfaction today?»
The devastating power of this method lies not in the data, but in the logic it unleashes. By forcing the verbalization of priorities, AI exposes the irrationality of attempting to have both options when they are mutually exclusive. It gives no orders; it exposes contradictions.
The AI system, however Socratic or perfect, inevitably runs into the blinding power of human ego. There are individuals for whom not even the most overwhelming evidence is sufficient. Their lack of cognitive humility will lead them to take refuge in convenient explanations. And this is where the system must have more teeth than the ego, equipped with an incorruptible accountability protocol.
The objective cannot be to convince the irredeemably biased. The strategy must evolve toward changing the incentives and processes surrounding the individual, so that ignoring AI carries such a high personal and professional cost that the rational option is, precisely, to act rationally. This is where the Algorithmic Objection Protocol deploys its utility.
1. The AI acts as «Socrates» and poses its questions.
2. The leader insists on their irrational position.
3. The AI declares: «Understood. I have recorded the decision not to act on the recommendation based on scenario analysis. To proceed, the dissenter is required to complete the Own Judgment Objection Form.»
In this model, AI does not overcome irrationality with logic; it exposes it through corporate bureaucracy. It transforms a discussion of ideas into a formal process with consequences. The way to compel honest confrontation is to institutionalize that rejecting evidence carries an explicit and personal burden of responsibility.
If the human evaluator is the weak link, the solution must be radical: AI must evaluate humans. Not from a position of moral superiority, but as an impartial and tireless auditor. Accountability must be automated and integrated into performance management systems.
The answer to this paradox must be structural: the evaluation of the evaluator must also be audited. A leader's performance metric must include, in an explicit and quantifiable way, how well they evaluate and manage the judgment of their subordinates.
AI consolidates itself as not only a central nervous system of accountability but as an impartial auditor that operates in cascade: an immutable record of every objection and outcome; automatic auditing that contrasts decision with result generating an objective «Gap Report»; and automated consequences tied to incentives and radical transparency before senior management.
Throughout this essay, we have dissected the «agree to disagree syndrome» not as a communicative failure, but as the symptom of a deeper corporate disease: the inability of our human nature, potentiated by the corporate environment, to submit to the discipline of common sense.
The paradox I raised at the outset — «how do we code something we ourselves do not completely possess?» — reaches its climax here. Resistance to this evolution will not be technical, but visceral. Those with the power to change things will fight, under the banner of «intuitive leadership» or «human essence,» to protect the ultimate privilege: the impunity of their own judgment.
The «AI Enlightenment» we glimpse is not a rejection of the human, but its culmination. It is the possibility of responding, centuries later, to Voltaire's call and his defense of reason against irrationality. Ultimately, AI does not come to replace humans, but to challenge the part of the human that resists evolving.
«Will we be willing to allow AI to improve us, even if that improvement demands sacrificing the privileges of our ego?» — Jesús Bernal Allende