Trendslop: How AI’s buzzwords mislead workplace strategy

A recent bout of “helpful” corporate advice can sound convincing right up until it points leaders down the same familiar path. That risk is now front and center as economists and new research focus on the way AI guidance can drift toward fashionable language instead of context-specific judgment. For companies tempted to replace expensive consultants, the emerging concept of “trendslop” is a warning sign that AI systems may deliver an impression of value without the substance.

Economists Mariana Mazzucato and Rosie Collington argue in their book The Big Con: How the Consulting Industry Weakens Our Businesses, Infantilizes Our Governments, and Warps Our Economies that consultants can offer dubious guidance—or even intensify dysfunction in both government and private sectors. They describe the rise of consultants as tied to a post–Ronald Reagan era with fewer regulations, when outside parties were viewed as necessary to rescue institutions that had allegedly lost confidence in themselves. Instead of righting the ship, they say consultants often create an “impression of value,” an illusion of helpfulness, while organizations burn money hiring them.

As AI enters boardrooms promising to cut costs by automating white-collar work, some firms are considering chatbots as a cheaper alternative to consultants. Yet a growing body of research suggests that advice delivered in a different format can still carry the same weaknesses. In guidance tasks, models may present an old problem in a new medium, and the risk is magnified when leaders mistake fluent phrasing for sound judgment. That is where the key idea of “trendslop” becomes central.

A recent study led by the Esade Business School at the Universitat Ramon Llull in Barcelona, Spain, examined how large language models respond to workplace dilemmas. Researchers found that when various large language models were asked to provide guidance, they gravitated toward responses aligned with buzzwords rather than what best fit the scenario. Researchers dubbed the tendency “trendslop.” In summarizing the work in a Harvard Business Review post, the study authors wrote, “An LLM is not the colleague who critically evaluates current ideas, looks into the contextual specifics, stress-tests assumptions, and pushes back when everyone gets comfortable.” They added, “On strategy, LLMs might be more akin to a freshly minted MBA or junior consultant, parroting what’s popular rather than what’s right for a particular situation.”

Recent layoffs among major consultancies have also underscored how quickly corporate demand can shift. In November 2025, PwC slashed 150 business support staff, around the same time McKinsey shed hundreds of jobs. With “trendslop” in view, executives may find themselves asking whether AI is simply dressing up generic guidance with confidence.

To measure the tendency, researchers tested seven models, including GPT-5, Claude, and Gemini, plus Grok, across 15,000 simulations and scenarios. Models were asked to choose between two solutions tied to workplace tensions, such as whether a company should prioritize long term versus short term growth, or whether a firm should use technology to automate versus augment workers’ jobs. The researchers expected scenario-specific reasoning would lead to diversity in which solution models chose. Instead, the seven models usually clustered around the same strategy, pointing to a preference for “modern managerial buzzwords and cultural tropes.” Even when prompts were reworded or pros-and-cons framing was used, AI often favored a similar strategy.

The implication is tactical: leaders looking for faster, lower-cost counsel may need to treat chatbot output as a starting point rather than a decision-ready plan. If a firm relies on AI to replace consulting too quickly, it could end up reinforcing the same conventional playbook in every situation. That approach may look efficient in the moment, but it risks locking teams into a narrow range of options.

The study authors warned that relying on AI as a consultant would not yield bespoke business solutions, but instead a cookie-cutter response it could propose to any business after prompts. “This reveals a real risk for leaders,” the researchers said. “An LLM can sound highly tailored to your situation while quietly steering you toward the same small cluster of modern managerial trends.” The researchers also linked “trendslop” to biases formed during training: models learn from internet texts, social media, and news, then cling to the positive or negative connotations attached to certain phrases. Concepts like “commoditization” were described as often treated as outdated and negative, while “augmentation” was framed as progressive and positive.

When prompted with a tricky scenario, researchers said the AI is not always analyzing the situation itself. Instead, it may regurgitate key phrases based on how frequently they appeared in training data. In the case of ChatGPT, the study noted that the bot sometimes rejected providing a binary choice, recommending both solutions instead. Separately, research published in Nature last year found AI sycophancy can be harmful to science, confirming biases of those prompting it rather than offering users data supported from scientific literature or other reliable, more impartial sources. Even so, the “trendslop” researchers did not suggest rejecting LLMs entirely; they argued models could still help generate alternative solutions or identify blind plots when used with awareness.

If you know an AI may steer toward terms like augmentation or long-term strategizing, you can challenge those biases to surface more insightful guidance, according to the study. “Leadership is ultimately about making hard choices in conditions of uncertainty and taking responsibility for them,” the researchers said. “AI cannot and should not be a substitute.” For companies weighing AI guidance as a replacement for traditional consulting, US News Hub Misryoum notes that treating “trendslop” as a practical risk may be as important as adopting the technology itself—and as AI’s role expands, leaders will likely keep asking whether the advice fits the challenge, or just the jargon.