Google’s Gemini AI stunned draft observers by having the New York Jets select quarterback Ty Simpson at No. 16, a reach that ignores the team’s obvious defensive needs and creates a fascinating quarterback controversy.
Artificial intelligence has officially entered the NFL draft prediction arena, and its first full foray is already creating seismic waves. Google’s Gemini language model generated a complete first-round mock draft for 2026 that, while conventional at the top, delivered a series of confounding reaches that defied both expert consensus and basic team-building logic.
The most jaw-dropping selection came at pick No. 16, where the New York Jets—a franchise eternally searching for a franchise quarterback but now with Geno Smith reacquired in a recent trade—supposedly selected Alabama’s Ty Simpson. This move contradicts the Jets’ obvious, glaring need for defensive help after they used their No. 2 overall pick on edge rusher Arvell Reese.
The AI’s Methodology: Mimicry Over Mastery
Google Gemini’s approach appears fundamentally derivative. The AI aggregated existing human-generated mock drafts and expert analysis, producing a draft that followed consensus for the top 15 selections before encountering its first major logical flaw. This pattern suggests the model excels at synthesizing established narratives but struggles with nuanced team-specific evaluations that require understanding recent roster moves, cap situations, or coaching philosophies.
The AI’s failure to account for the Jets’ recent trade for Geno Smith—a move that strongly indicates the team’s intent to compete now with a veteran quarterback—highlights a critical limitation: current AI lacks the ability to integrate breaking transactional news with long-term draft strategy, a skill that separates elite human analysts.
Top 10: Consensus Reigns Supreme
The draft’s first decade remained largely predictable, reflecting the consensus big board rankings. The Las Vegas Raiders selected Indiana quarterback Fernando Mendoza at No. 1, a universally projected lock. The New York Jets then took Ohio State’s top-ranked player, edge defender Arvell Reese, a pick that aligned with their need for pass-rush help after trading Jermaine Johnson II.
From there, Gemini largely mirrored expert projections: the Arizona Cardinals took edge rusher David Bailey (who recorded 81 pressures in 2025), the Tennessee Titans and New York Giants landed the two combine stars—running back Jeremiyah Love and linebacker Sonny Styles—and the Cleveland Browns addressed their offensive line with Miami’s Francis Mauigoa.
The Jets’ Paradox: A Second Quarterback in the First Round
The first true shock arrived at pick 16, where the Jets—via their trade with the Indianapolis Colts—selected Ty Simpson. This creates an immediate and messy quarterback room: Simpson, a highly-regarded but raw talent, would compete with the reacquired Geno Smith and any potential free-agent signings. The selection ignores the Jets’ catastrophic defensive rankings from 2025 and their obvious need to add secondary or interior line help, positions that remained stocked with first-round talent.
Human experts have noted Simpson’s rising stock, but placing him in the middle of the first round—especially by a team with a quarterback already under contract—represents a reach that smacks of AI’s tendency to overweight recent narrative (Simpson’s combine performance) over roster context.
Late-First Round reaches: Brazzell and Beyond
The AI’s reaches continued. Most egregious was pick No. 24, where the Cleveland Browns selected Tennessee wide receiver Chris Brazzell II, who ranks 49th on the USA TODAY Sports big board. Even after a 4.37-second 40-yard dash, Brazzell has been largely omitted from expert first-round projections, with superior receivers like Texas A&M’s KC Concepcion and Indiana’s Omar Cooper Jr. still available.
Other questionables included the San Francisco 49ers taking OT Caleb Lomu at 27—a developmental prospect that fits their timeline—and the Houston Texans selecting CB Avieon Terrell at 28 despite a loaded secondary. The most glaring error arrived at pick 29, where the Kansas City Chiefs (from the Rams) selected edge rusher Nic Scourton, a player already drafted in the second round by the Carolina Panthers in 2025, revealing a fundamental flaw in the AI’s dataset.
The Fan Perspective: A Draft of Missed Opportunities
For Jets fans, the Simpson pick triggers existential dread. After years of quarterback purgatory, the team finally appears to have a short-term solution in Smith and a long-term project in Simpson from the prior draft. Adding another first-round quarterback signals organizational confusion, not clarity. The defensive roster remains patched together, and the Simpson pick means the Jets will enter 2026 with the same ah-oh line and secondary that failed them in 2025.
Meanwhile, Browns fans must wonder why their front office—in this AI simulation—passed on three better receivers to take Brazzell. The pick suggests a misreading of positional value, prioritizing raw speed over refined route-running and hands.
What This Means for Draft Season
Gemini’s mock draft serves as a crucial cautionary tale: AI can efficiently aggregate existing information but cannot yet replicate the holistic team-building assessment of a seasoned general manager. The model’s most valuable function may be identifying consensus players (like Mendoza and Reese), while its reaches highlight the human elements—coaching schemes, locker-room dynamics, contract situations—that remain beyond algorithmic comprehension.
As the real draft approaches, teams will undoubtedly study this AI output, not as a blueprint but as a mirror reflecting the most common narratives. The Jets’ hypothetical Simpson selection will be debated for months, a hypothetical that forces us to ask: In the modern NFL, is taking a quarterback in the first round ever a mistake, or only a mistake if the team isn’t committed to starting him immediately?
The only certainty is this: when the real 2026 NFL Draft begins, the Jets—and every other team—will face decisions no algorithm can fully anticipate.
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