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AI cover letters sound generic for a structural reason. Language models tend toward the most typical phrasing for a request. Ask for "a cover letter for a marketing job" and you get an average of countless similar letters: enthusiastic openers, vague claims of passion, and interchangeable strengths. The fix is to supply specifics the model cannot guess. A dependable process has six steps. First, gather your inputs: the posting, your resume, two or three concrete accomplishments, and a genuine reason for wanting this employer. Second, ask the AI to map each key requirement to your evidence. Third, outline the letter: a specific opening, two evidence paragraphs, and a short close. Fourth, draft. Fifth, rewrite in your own voice. Sixth, check every fact. Keep the letter well under one page. Recruiters notice several patterns in AI-written letters. Stock openers and flattery that could apply to any company. Claims with no example behind them. A uniformly polished tone with no personality. And worst of all, errors: the wrong company or role name left over from another application, or invented details about the employer. Any of these tells the reader the letter was not written for them. Two misconceptions deserve correcting. First, AI-written letters are not reliably caught by detection software. Such tools are known to be inaccurate, so the real risk is not detection but a weak, generic letter. Second, whether a cover letter matters depends on the employer. Some ignore them, while others use them to decide between close candidates, especially for career changers. When a letter is requested, a specific one is worth the effort.