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An unintended consequence of AI is clients using it to fill out agency onboarding forms. Instead of providing genuine insights, they submit generic, AI-generated text. This 'slop' makes it harder for agencies to get real answers, undermining the efficiency AI was meant to create.
The problem with bad AI-generated work ('slop') isn't just poor writing. It's that subtle inaccuracies or context loss can derail meetings and create long, energy-wasting debates. This cognitive overload makes it difficult for teams to sense-make and ultimately costs more in human time than it saves.
Using AI to generate content without adding human context simply transfers the intellectual effort to the recipient. This creates rework, confusion, and can damage professional relationships, explaining the low ROI seen in many AI initiatives.
The primary issue with low-effort AI-generated work is not its poor quality, but how it transfers the cognitive burden of correction and completion to the recipient. This 'masquerades' as finished work but creates interpersonal friction and hidden rework, fundamentally shifting the responsibility for the task's success.
A major hurdle in AI adoption is not the technology's capability but the user's inability to prompt effectively. When presented with a natural language interface, many users don't know how to ask for what they want, leading to poor results and abandonment, highlighting the need for prompt guidance.
While AI can structure RFP responses, its overuse leads to generic text that fails to convey a vendor's unique value proposition and cultural fit. This trend heightens the need for multi-stage evaluations with direct human interaction to discern if a potential partner is truly aligned and being transparent.
AI is increasingly used to produce low-quality outputs like emails and reports, termed "work slop." While quick to create, this content is often so vague or useless that it makes colleagues' jobs harder, increasing overall administrative burden and hindering real progress.
Research highlights "work slop": AI output that appears polished but lacks human context. This forces coworkers to spend significant time fixing it, effectively offloading cognitive labor and damaging perceptions of the sender's capability and trustworthiness.
AI scales output based on the user's existing knowledge. For professionals lacking deep domain expertise, AI will simply generate a larger volume of uninformed content, creating "AI slop." It exponentially multiplies ignorance rather than fixing it.
Professionals are using AI to write detailed reports, while their managers use AI to summarize them. This creates a feedback loop where AI generates content for other AIs to consume, with humans acting merely as conduits. This "AI slop" replaces deep thought with inefficient, automated communication.
The ease of generating AI summaries is creating low-quality 'slop.' This imposes a hidden productivity cost, as collaborators must waste time clarifying ambiguous or incorrect AI-generated points, derailing work and leading to lengthy, unnecessary corrections.