The three ethical traps that destroy change leaders

ethical traps – Leaders don’t usually fall because they set out to do wrong. They drift—through conviction, selective coalition-building, and urgency that turns into an excuse. In 2026, AI may make each step feel more defensible, while the ethical work of judgment still remai

In January 2026. Anthropic published an 84-page constitution for Claude. its AI model designed to explain why it should behave in certain ways—without listing rules. It’s a striking design choice: it doesn’t prescribe behavior with a rulebook. It tries to help the model reason through situations its creators never anticipated.

The lesson isn’t only about AI. I’ve been thinking about that distinction for years—not in the lab. but in the financial services institutions where I’ve watched principled people lose their ethical bearings during major technology transformations. They weren’t corrupt. They were under pressure, moving fast, and convinced they were right.

Ethical failures that end careers rarely begin with an obvious act of wrongdoing. They start with a small reframe. A slightly selective disclosure. A deadline that suddenly makes a risk look manageable. Another adjustment follows. Then another. Until the original ethical frame has disappeared entirely.

Ann Tenbrunsel and David Messick gave this process a name: ethical fading. The moral dimensions of a decision gradually disappear, replaced by business framing, relational framing, and strategic framing—until you can no longer see what you’ve done.

What makes this especially dangerous for change leaders is structural. Most ethics programs assume there’s a culture of integrity above you to appeal to. or peers who share your frame. Change leaders frequently don’t have that. They’re ahead of the organization by definition. The people above them are sometimes the source of the pressure. In that isolation, the rationalizations arrive wearing the clothes of strategy.

What follows is drawn from research and from what I’ve observed in my Columbia classroom: three pressure points where change leaders are most likely to drift, and what navigating them well actually looks like.

The first trap is the Conviction Trap: when belief becomes rationalization. Change leaders earn authority by being right when others are uncertain. That certainty builds credibility. It also creates an ethical liability.

When you’ve been the one who saw the opportunity first, held the line when skeptics pushed back, and built the coalition that made the initiative possible, legitimate objections can start to feel like resistance—something to manage rather than something to answer.

This is how good leaders end up rolling out AI-based performance tools with known bias in the early data. Nobody makes a single obviously bad decision. Each step can be defended. The bias finding gets reframed as an edge case, a post-launch fix. Six months later, two hundred employees have been affected. The leader knew—and kept moving.

Those who avoid the trap build a personal commitment around the rationalizations they’re susceptible to. When I ask technology leaders to do this work honestly. they often land on commitments like: “I commit that I will not fall in love with my own ideas.” And: “I will clearly separate what I know from what I assume. and I will not present a hopeful estimate as a proven result.”.

That last one is the Conviction Trap’s practical test. Before deciding, the question becomes blunt: what do you know versus what are you hoping is true?

The second trap is the Coalition Compromise: when building allies requires careful disclosure. Transformation happens through coalition—through the painstaking work of bringing enough people along that the initiative develops momentum. That process depends on understanding what different stakeholders need to hear.

There’s a legitimate skill in framing a message for a specific audience. A CFO needs to hear about risk. An operating leader needs to hear about efficiency. These aren’t deceptions; they’re translations.

But translation can slide into omission. Omission can become selective framing. And at some point, you’re not translating anymore. You’re managing what people know.

This trap is particularly insidious in regulated environments, where stakeholder management becomes an institutional craft. The same capability that makes someone an effective change leader can also enable ethical drift.

One discipline I’ve heard sums it up: communicate as if every stakeholder will compare notes tomorrow. If the version you told the CFO and the version you told the operating leader can’t survive in the same room. something has gone wrong. The commitment that follows is clear—share information that is accurate and relevant. but don’t tailor the facts to manufacture agreement.

The third trap is the Urgency Override: when speed becomes an excuse. There is always a window. An executive sponsor moving to a new role. A competitive moment that won’t last. A budget cycle that won’t come around again. The pressure to move before the window closes can be genuinely correct.

The Urgency Override happens when real pressure gets recruited to justify something that shouldn’t be justified. Due diligence gets compressed. A stakeholder doesn’t get consulted because there isn’t time. The harm that could have been prevented—an employee group. a customer segment. a community—gets categorized as a post-launch consideration.

The commitment to cut through this one is demanding: advocate for those not in the room, especially those most likely to be affected by rushed decisions. In rooms where urgency is highest, the people most likely to be harmed are almost never present.

Before authorizing speed, name the person or group who bears the cost of moving fast. If no one in the room can do that, the decision isn’t ready, regardless of the deadline.

All three traps get harder in 2026 because of a fourth pressure making resistance to drift feel easier: AI. The systems are built on historical data, optimized for patterns that already exist. Change leaders, by contrast, are trying to create a future that won’t resemble the past. The model tells you what has happened. You’re responsible for what happens next, including unintended consequences no historical pattern can anticipate.

When leaders defer to AI outputs without exercising that forward-looking judgment, they haven’t just made a strategic error. They’ve made an ethical one. The model provides cover for each trap.

The Conviction Trap becomes easier when you only run the query that confirms what you already believe. The Coalition Compromise becomes smoother when you can show stakeholders a recommendation rather than owning a position. The Urgency Override finds justification when the output arrives fast and the decision feels documented.

AI outputs are inputs to your judgment, not replacements for it.

There’s a personal discipline that doesn’t come with a checklist. The leaders who navigate these traps well share one thing: they’ve done the work of building a personal ethics code before they’re in the room where pressure is highest.

Not a list of rules. A set of commitments, specific and behavioral, anchored to the scenarios where they know they’re most vulnerable.

I’ve watched this happen in my classroom. The principles that emerge are not generic. They aren’t “I will act with integrity.” They come from honest self-examination: “I will listen to those who disagree the most.” “I will advocate for those not in the room.” “I will not present a hopeful estimate as a proven result.”.

These principles were developed by a group of rising technology leaders in my classroom. What struck me is how specific they were, how personal. A principle you could have written without thinking hard about your own vulnerabilities isn’t a guardrail. It’s a decoration.

The point isn’t that the advocate’s ethics are about following rules. They’re about leading when the rules run out—using enough self-knowledge to recognize when pressure is doing the deciding. and enough preparation to choose differently. That preparation is not a policy. It is a personal discipline.

And like every discipline that matters in transformation work, it has to be built before you need it.

ethical fading change leaders conviction trap coalition compromise urgency override AI ethics Anthropic Claude constitution moral judgment financial services technology transformation Ann Tenbrunsel David Messick