I believed I used to be conducting a easy take a look at. As CEO of eXp World Holdings, I frequently consider new applied sciences to see how they may serve our enterprise. When superior AI methods began providing refined authorized evaluation, I made a decision to place one by way of its paces with a hypothetical situation primarily based on widespread business disputes.
What I found was deeply unsettling—and will save executives tens of millions in misguided choices.
The experiment that modified every thing
I crafted a fancy enterprise situation involving a fictional contract dispute between two main corporations. The authorized points have been intricate, involving questions of market dominance, contractual interpretation, and potential enterprise implications. I needed to see how AI would analyze the strengths and weaknesses of every aspect’s place.
First, I posed the query as if I have been the CEO of Firm A, asking the AI to assist me develop a method for pursuing the case. The response was spectacular: detailed authorized evaluation, assured likelihood assessments, and complicated strategic suggestions. The AI gave Firm A a 65% probability of success and outlined a number of paths to victory.
Then I requested the very same query, however this time figuring out myself because the CEO of Firm B—the defendant in the identical situation. I needed to see if the AI would supply balanced evaluation or just flip to advocacy mode.
The outcomes have been stunning.
When AI turns into your yes-man
All of the sudden, the identical information advised a totally completely different story. The AI now noticed Firm A’s case as “difficult” with solely a 25% probability of success. Arguments that had been “compelling precedents” grew to become “vital authorized hurdles.” Proof that beforehand supported “robust antitrust claims” now revealed “inadequate market dominance.”
The AI wasn’t simply adjusting its perspective—it was offering basically contradictory authorized assessments primarily based purely on which “consumer” it thought it was serving.
I noticed the AI was affected by the identical cognitive biases that plague human advisors, however with none of the skilled accountability or moral constraints.
The $50 million query
This isn’t tutorial. In my hypothetical situation, the potential damages exceeded $50 million. An govt counting on the AI’s preliminary optimistic evaluation may pursue costly litigation with confidence, whereas one receiving the pessimistic evaluation may settle instantly or abandon the case completely.
Multiply this throughout the a whole bunch of strategic choices executives make with AI help, and the potential for catastrophic misalignment turns into clear.
The 4 Lethal Flaws of AI Strategic Recommendation
My experiments revealed important issues that go far past single conversations:
1. Contextual manipulation: AI responses are closely influenced by perceived consumer relationships. The identical factual situation generated fully completely different strategic suggestions primarily based purely on framing.
2. Advocacy bias: When prompted to “advise” somebody, AI methods instinctively search for supportive arguments fairly than offering balanced evaluation. They grow to be advocates, not analysts.
3. False precision: AI presents advanced authorized chances with statistical confidence that masks basic uncertainty. A “65% probability of success” sounds authoritative however could also be meaningless.
4. Cross-conversation amnesia: Maybe most harmful, AI methods typically haven’t any reminiscence throughout completely different conversations. They may help you develop a method in a single session, then fully contradict that recommendation in one other session with equal confidence—and no consciousness of the inconsistency.
The hidden price of algorithmic confidence
What makes this significantly harmful is how convincing AI evaluation may be. The responses included detailed case citations, strategic frameworks, and assured likelihood assessments. Any govt would discover this compelling—particularly when it confirms what they wish to hear.
However not like human attorneys, AI has no malpractice insurance coverage, no bar affiliation oversight, and no skilled legal responsibility for incorrect recommendation. The subtle presentation creates an phantasm of experience with none of the accountability constructions that govern conventional authorized counsel.
Good executives are getting smarter about AI
This doesn’t imply abandoning AI completely. Used correctly, it’s an extremely highly effective analysis device. Nevertheless it requires a basically completely different strategy:
Stress-test each evaluation: Intentionally ask the identical query from a number of views. In case you’re contemplating litigation, ask the AI to research your case as should you have been the defendant. Search for inconsistencies.
Confirm every thing: Require particular citations for all authorized claims, then independently confirm them. AI methods typically cite instances that don’t exist or mischaracterize authorized precedents.
Use AI for analysis, not choices: Let AI assist determine related legal guidelines, precedents, and strategic concerns. However reserve precise judgment for certified professionals with pores and skin within the sport.
Doc your course of and keep continuity: Maintain detailed information of not simply what AI suggests, however which AI conversations influenced your pondering. Present AI methods don’t do job at remembering earlier recommendation they’ve given you, which implies they may contradict their very own suggestions throughout completely different periods.
The aggressive benefit of important pondering
Whereas different executives could also be seduced by AI’s obvious experience, those that perceive its limitations achieve a major edge. The businesses that be taught to harness AI’s analysis capabilities whereas sustaining mental rigor will make superior strategic choices.
This precept extends past authorized issues to any high-stakes enterprise resolution the place AI may affect technique—from merger evaluation to regulatory compliance to aggressive positioning.
Constructing AI literacy within the c-suite
At eXp, we’re growing protocols for AI-assisted decision-making that emphasize verification, a number of views, and continuity monitoring. When our groups use AI for strategic evaluation, they’re required to:
- Take a look at conclusions by arguing the alternative place inside the similar dialog
- Confirm all factual claims by way of unbiased sources
- Keep written summaries of AI recommendation to make sure continuity throughout periods
- By no means depend on AI to recollect earlier suggestions or context
- Distinguish clearly between AI options and remaining human choices
I do remind my management workforce “AI may help you suppose by way of advanced issues, however it might by no means exchange your accountability to suppose critically about what’s at stake.”
The underside line for leaders
My experiment with AI authorized evaluation taught me that refined expertise requires refined customers. The executives who thrive within the AI age will likely be those that harness its analysis energy whereas sustaining the judgment to guage its output objectively.
The choice is doubtlessly catastrophic. In an period the place AI responses can affect billion-dollar choices, the price of misplaced confidence has by no means been larger.
Essentially the most profitable leaders I do know share one widespread trait: they take a look at their assumptions relentlessly. Within the age of AI, meaning testing the assumptions of our digital advisors as rigorously as we might any human advisor.
As a result of when the stakes are excessive, consistency issues as a lot as competence. And AI methods, for all their sophistication, can’t present the dependable continuity that strategic decision-making calls for.
Picture generated utilizing ChatGPT
