CORPORATE AMERICA BEHIND THE WALLS OF EA NS GHTS I I
AI agents and automation tools like Power Automate, ChatGPT , and other machine- learning models [MLLs] are increasingly taking on repetitive, process-driven tasks—things that have traditionally been part of business administration to organize and deploy. But while AI can execute, it lacks the ability to think strategically, interpret nuance, or anticipate needs. These are and will continue to be core strengths of executive assistants. As AI takes over repetitive work streams, EAs have an opportunity to step into a new role as navigators and strategic enablers. Here’s the hard truth: AI is only as good as the input it receives. Unlike a human EA who can “read between the lines,” AI requires structured, precise instructions to generate meaningful outputs. This is where a major gap exists in organizations today. Leaders are constantly lifting and shifting so their communication may not be fully articulated in a manner that is concise—this is where EAs fill in the missing instruction to attain the expected output.
AI won’t fill the gaps in executive intent—it will only amplify inefficiencies if the input is unclear.
Context matters—AI doesn’t inherently understand nuance; it relies on well-structured prompts and logic.
Translation? EAs who hone their communication skills and learn how to give AI the right instructions will become the bridge between executives and AI systems.
Engineers and data scientists are busy building AI systems, fine-tuning MLLs, and refining algorithms. While the focus is on building AI, few are considering how it will integrate into daily business operations.
Who is ensuring that AI will be implemented in real-world business contexts? Who is teaching executives how to use AI efficiently and effectively? Who is managing the human layer of AI-driven workflows?
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