In an unusual move for professional sports, former Manchester United youth player Demetri Mitchell has revealed he used the artificial intelligence platform ChatGPT to negotiate his contract with League One club Leyton Orient. The 28-year-old footballer managed his own transfer, using the AI tool to formulate negotiation points and secure his terms.
Key Takeaways
- Demetri Mitchell, a professional footballer, used ChatGPT to handle his contract negotiations for a move to Leyton Orient.
- He chose to forgo a traditional agent, allowing him to collect the agent's commission as a signing-on fee.
- The AI provided negotiation language based on inputs like previous salary, London's cost of living, and family relocation.
- Mitchell described the AI as his "best agent to date" and offered a detailed critique of the agent system in lower-league football.
An Unconventional Transfer Negotiation
Professional athlete transfers are typically complex processes managed by experienced agents who handle contract details, salary discussions, and signing bonuses. Demetri Mitchell, however, opted for a modern, technology-driven approach for his move from Exeter City to Leyton Orient this summer.
After receiving an initial offer from the London-based club, Mitchell turned to ChatGPT for assistance. He detailed his experience on the "From My Left" podcast, explaining how he leveraged the AI to his advantage.
"They [Leyton Orient] sent me an offer, and I started using ChatGPT, asking it how to negotiate a deal, and what to say in it," Mitchell stated.
He provided the AI with specific personal and financial details to build a strong case for his desired terms. These inputs included his salary from the previous season, the higher cost of living associated with moving to London, and the fact that his partner and child would be relocating with him. Mitchell also noted he felt he was worth more but wanted to present his case professionally.
The Rationale Behind Forgoing an Agent
Mitchell's decision to bypass a human agent was primarily a financial one. In professional football, agents typically receive a percentage of a player's contract value as a commission. By representing himself, Mitchell was able to have that fee redirected to himself as a signing-on bonus.
He calculated that the potential financial gain from a human agent would have been minimal and likely negated by their commission. This is especially true in the lower leagues, where transfer values and salaries are not as high as in top-tier football.
Financial Calculation
Mitchell explained his thinking: "An agent might have got me a couple hundred pound more... and then the percent that I would have to pay them, the difference, is going to be eaten up anyway." This highlights the slim margins that can make self-representation an attractive option for some players.
This move represents a significant departure from industry norms, where players are heavily reliant on agents for career management and contract negotiations. Mitchell's success using a widely available AI tool could prompt other athletes in similar financial brackets to consider alternative negotiation strategies.
A Critique of the Football Agent System
Beyond his personal experience, Mitchell offered a broader commentary on the state of player representation, particularly for those outside of elite leagues. He categorized agents into three distinct types, providing a critical perspective on the options available to many players.
Mitchell's Three Types of Agents
- The Salaried Employee: An agent who works for a large agency and receives a fixed salary, potentially lacking personal investment in every client.
- The Prospect Hunter: An agent from a major agency focused on signing promising young talent. Mitchell suggests they may lose interest once a player is no longer considered a top prospect.
- The Independent Operator: An agent running their own business who Mitchell described as potentially "money-hungry" and focused on securing any move quickly.
"When you're in the lower leagues, it's difficult to get a good agent, because that's all you've got to work with," he commented. His statement underscores a perceived gap in high-quality, dedicated representation for the majority of professional footballers who do not command multi-million-pound contracts.
His use of AI can be seen as a direct response to this perceived market failure, seeking a reliable, data-driven alternative to what he views as a flawed system.
Player Profile and Career Trajectory
Demetri Mitchell's career began in the prestigious youth academy of Manchester United, where he progressed to make one senior league appearance for the club. His journey is representative of many professional players, involving spells at various clubs across different leagues.
His career path includes time at Scottish clubs Hearts and Hibernian, as well as English clubs Blackpool and Exeter City. This varied experience has given him a comprehensive view of football's professional structure beyond the top flight.
On the international stage, Mitchell has represented England at multiple youth levels, from the Under-16 to the Under-20 teams. He was also named in the preliminary 60-man squad for the Jamaican national team ahead of the 2025 Gold Cup, highlighting his continued recognition.
Since joining Leyton Orient, he has made eight appearances for the club. His innovative approach to securing his contract demonstrates a forward-thinking mindset that is increasingly relevant in a sport being transformed by technology and data analytics.