Report Claims AI Might Have Cost Brad Treliving His Job in Toronto

Rumblings out of the Toronto Maple Leafs front office are raising eyebrows on Tuesday, as new reporting suggests MLSE president and CEO Keith Pelley took an unusually hands-on approach ahead of the March 6 trade deadline — one that may have contributed to the dismissal of general manager Brad Treliving.

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According to a column in The Athletic, Pelley made a rare appearance in the Leafs’ war room at their suburban practice facility, a move that signaled just how concerned ownership had become with the team’s direction. Specifically, there might have been a lack of trust as Treliving navigated the trade deadline.

Reports indicate that, unlike his typical hands-off approach with other MLSE franchises, Pelley was not merely observing. Multiple sources indicated he was actively engaged — questioning scouts, pushing for more “assets” in trade discussions, and offering his own ideas.

What stood out most, however, was the reported use of artificial intelligence in his pitches.

Pelley reportedly arrived with notes outlining potential trade returns, which some within the organization believed were generated using large language models and AI tools. While AI has become more prevalent across MLSE’s broader operations, when he showed up to tinker with the Leafs’ traditionally hockey-driven decision-making process, it caught staff off guard. The belief among staffers was that Pelley’s AI musings were coming directly from Humza Teherany, who has become one of Pelley’s most trusted advisors.

The Athletic scribes write:

“One organization source said Teherany had “his fingers in all of the (MLSE) teams.” That included the Raptors, who had embraced the support of MLSE’s Sports Performance Lab, which included everything from AI to analytics to biomechanics, and found success from it.

The Leafs staff, conversely, were found to be resistant to what the tools might offer, which explained why Pelley would later call for a more “data-centric” head of hockey operations.”

Pelley Denies the Report He Tried to Interfere

Pelley started his press conference a couple of weeks ago by denying any attempt to act like a GM or influence hockey decisions. While he didn’t address the use of AI to suggest trades before Treliving was relieved of his duties, The Athletic maintains that it’s one of the reasons Pelley has been so adamant that a GM who embraces a “data-centric ” approach be a priority.

Ultimately, whatever it is Pelley is looking to do with the Leafs, he didn’t believe Treliving was the guy to ride shotgun with. That poses an interesting question: will a new GM embrace Pelley’s ideas? Or will this President be steadfast in their stance that AI will not be an assistant in the process of making trades?

An AI-Generated Auston Matthews Trade

For fun, I popped a request into AI to see what it would give me if Pelley took over the process of trading Auston Matthews. I would assume the team is using more tools than just the platform I selected, but you get the idea. Here’s what it suggested that conversation between Treliving and Pelley might have looked like:

“Brad, I asked the model: ‘What is the absolute maximum controllable, high-upside return we could realistically extract for Matthews right now?’ Here’s what it spit out.”

Mock Trade (San Jose Sharks – because they have the deepest prospect pool in the league and a desperate need for a proven 50-goal center to accelerate around Celebrini)

Toronto Maple Leafs receive:

• Sam Dickinson (19, LHD) — The Sharks’ No. 2 overall prospect, elite skating, size, and offensive projection. Ready to step into a top-4 role immediately and has top-pair upside.
• Igor Chernyshov (20, LW/RW) — Big, skilled, high-motor winger already showing NHL scoring flashes. Perfect middle-six piece with top-six upside.
• 2026 1st-round pick (unprotected — Sharks are still a ways from contending)
• 2027 1st-round pick (unprotected)
• 2028 2nd-round pick

Toronto retains 25% of Matthews’ $13.25 M cap hit (only ~$3.3 M against the cap through 2027-28 — basically turns him into a very reasonable cap number for San Jose while giving the Leafs massive future flexibility).

San Jose Sharks receive: Auston Matthews (75% retained cap hit)

Why the AI loved this package:

• Two blue-chip prospects at premium positions (elite D + scoring winger)
• Two first-rounders in a weak-to-middling draft window for SJ → high probability of another impact player
• Immediate cap relief + long-term asset haul that lets Toronto retool on the fly without a full teardown
• Fits the “modern, data-centric” mandate Pelley keeps talking about — controllable talent + draft capital over one aging star

Next: Small Moves, Big Impact: How the Leafs RFAs Should Be Handled