Cómo negociar un salario mediante un juego de roles con IA

A useful role-play has three parts: a realistic setup, several rounds of practice, and a debrief. For the setup, tell the AI who it is playing (for example, a hiring manager at a 200-person logistics company), what has already happened (the offer, the role, the timeline), and how it should behave: stay in character, raise common objections such as 'this is the top of our range' or 'we need an answer by Friday', and do not agree too easily. Then run the conversation several times with different personas, such as friendly, rushed, or tough, because real managers vary. In each round, practice the core moves: thank them and show enthusiasm, give a specific number or narrow range, back it with evidence (market data, competing offers, skills the role needs), and then stop talking. Practice non-salary levers too: signing bonus, equity, start date, remote days, title, professional development budget, or a written promise of a review in six months. The biggest misconception is that the AI knows what you should be paid. A general chatbot's salary figures come from training data that may be years old, mix countries and cities, and can be invented outright. Use real sources instead: government wage statistics such as the US Bureau of Labor Statistics occupational wage data, pay ranges in job postings (several US states, including Colorado, California, New York and Washington, require many employers to list them), industry salary surveys, professional associations, and sites like Glassdoor, Payscale or Levels.fyi, while remembering that crowd-sourced figures are self-reported. Bring those numbers into the prompt. A second misconception is that rehearsal fully prepares you. An AI cannot reproduce the pressure of a live call, so practice out loud, ideally in voice mode. Finally, remove names, employee IDs and confidential offer details before pasting documents into any chatbot.