As artificial intelligence models become more sophisticated, distinguishing between human and AI-generated text is crucial for businesses. Experts suggest developing personal reading skills rather than relying solely on detection tools, as AI writing often exhibits specific vocabulary and structural patterns.
Businesses need to be able to discern AI-generated content to maintain the integrity of their hiring processes, protect their brand reputation, and ensure the accuracy of reports and communications.
The increasing prevalence of AI-generated text necessitates the development of human skills to identify it, according to experts. Ashish Dsa, CTO and co-founder of Arbor, an AI voice agent company, notes that spending hours reading AI-generated text has shifted his focus from content to identifying statistical fingerprints. This ability is crucial for various business functions, from reviewing resumes to approving marketing copy and reports.
Research from the Association for Computational Linguistics in 2025 found that individuals who extensively used language models performed better than commercial AI detectors in distinguishing AI-written articles. These human detectors were able to identify AI writing even when it had been rewritten to conceal its origin. The study highlighted that relying solely on detector tools can be problematic, as they may incorrectly flag writing from non-native English speakers or other legitimate sources, leading to significant costs.
Specific linguistic tells include vocabulary choices such as 'delve,' 'underscores,' and 'showcasing,' which have seen increased usage in AI-generated content. Dsa contrasts human language like 'I dug into the numbers' with AI's tendency towards phrases like 'I delved into the multifaceted tapestry of the numbers.' Beyond vocabulary, structural habits are also indicative of AI authorship. These include negated structures (e.g., 'It is not a product. It is a movement.'), the tendency to present concepts in threes, clauses that reiterate rather than add new information, and unnecessary concluding phrases like 'in conclusion.'
In a professional context, such as LinkedIn posts, AI writing often exhibits intensity without specific details, unlike a real CEO who might openly discuss missed targets. Product reviews generated by AI can sound like specification sheets, whereas human reviews offer more personal and specific experiences. Cover letters may also reveal AI authorship through generic praise for a company's innovation without specific knowledge of its operations.