The NFL’s annual draft has long been a magnet for speculation, hope, and debate among fans, analysts, and front office personnel. No event in the football calendar is as meticulously dissected or as pivotal for a franchise's long-term prospects. With the 2025 NFL Draft looming, an intriguing twist has entered the draft discourse: artificial intelligence as a mock draft oracle. National outlets, including USA TODAY Sports and Yahoo Sports, recently put several leading AI chatbots through their paces to see who, or what, they believe the Chicago Bears will select with the No. 10 overall pick. The results? As variable as any human mock draft—with each chatbot offering a unique, reasoned guess rooted in both team needs and draft philosophy.
Machine learning and large language models (LLMs) like ChatGPT, Meta AI, Grok, and Microsoft Copilot are increasingly proving their worth in predictive analytics, from generating injury forecasts to aggregating advanced scouting data. Using these systems to run NFL mock drafts brings a new dimension of impartial reasoning—free from hometown bias, but not from the same supply of public information and logic available to traditional draft analysts.
USA TODAY Sports set up a controlled experiment: four top AI bots were instructed to select for all 32 teams in the first round, but the focus quickly zeroed in on the Chicago Bears at number 10. Writers at USA TODAY verified AI picks for eligibility and realism, but otherwise let the algorithms make their own choices based on publicly available draft boards, team needs, performance analytics, and recent free agency signings. The resulting picks each reflect a distinctive philosophy—and highlight both the promise and the limits of using AI for football decision-making.
Copilot labeled Walker a “versatile defender to boost their pass rush,” a nod to both his hybrid skill set and the Bears’ affinity for drafting multipositional defenders. In past seasons, Chicago has sought out versatile front-seven players who can move fluidly between linebacker and defensive end—see recent selections and acquisitions under GM Ryan Poles.
The case for Walker is bolstered by trends in both real-life draft history and consensus big boards, with Walker frequently cited as a late top-10/early teens pick due to his production and long-term upside. Still, it’s important to note that LB/Edge remains one of the more volatile draft positions; teams have found both stars and busts in this mold in recent years.
The AI justified the pick by referencing the Bears’ urgent need to “boost their pass rush,” advocating that Stewart’s athletic ceiling is too tantalizing to ignore. This is a classic “traits over tape” selection: NFL teams often covet edge rushers with elite testing metrics and physical tools, even if their college production is modest.
It’s worth flagging that while many scouting outlets agree on Stewart’s sky-high ceiling, the direct comparisons to Myles Garrett—a generational prospect with 10+ sack seasons—are best treated with caution. AI, much like human draftniks, can get swept up by physical comps that aren’t always predictive.
The AI’s logic follows recent trends in team-building: surround a young, high-pedigree quarterback with as many top-tier targets as possible. Grok rightly pointed out that as the Bears overhaul their offensive scheme and supporting cast, the addition of McMillan would give Williams a dynamic, three-pronged attack reminiscent of teams like Cincinnati and San Francisco, who prioritize depth and versatility at WR.
“Offensive tackle is always worth a top-10 pick, especially when you have a young QB to protect,” the bot reasoned, echoing a belief widely held by both analytics departments and traditional scouts. Elite tackles rarely reach free agency and often become franchise cornerstones for a decade or more.
The picks above all make plausible sense for Chicago at number 10, and each is firmly within the range of conventional wisdom among scouting outlets. Yet none seems so overwhelmingly obvious or unique that it would signal AI "knows" something the league does not.
Bears’ fans should be both encouraged by the depth of quality options available at No. 10 and aware that even the best projections are educated guesses. The front office’s “big board” may already be set, but contingencies—trades, unexpected slides, or late-emerging red flags—can and will shape the final outcome.
Rather than replacing the Mel Kipers and Daniel Jeremiahs of the world, expect AI tools to become an ever more critical supplementary resource—helping analysts gut-check their own biases, test new approaches, and maybe even anticipate league trends before they hit the mainstream. For fans and fantasy GMs alike, AI-powered mocks offer a fascinating new set of expectations and scenarios to add to the annual pre-draft excitement.
One lesson is clear: the margin for error between good, great, and franchise-altering picks is razor thin, whether the selection comes from a human or a machine. The 2025 NFL Draft will no doubt serve up its share of surprises. But thanks to innovations like AI-powered mock drafts, the conversation has never been more sophisticated—or more fun.
In the end, the Bears’ decision at number 10 will be shaped by a blend of cold analytics, gut instinct, and a little draft-night luck. For fans and football obsessives, that’s exactly as it should be.
Source: Yahoo Sports NFL mock draft 2025: Artificial intelligence predicts who the Chicago Bears will select
Machine learning and large language models (LLMs) like ChatGPT, Meta AI, Grok, and Microsoft Copilot are increasingly proving their worth in predictive analytics, from generating injury forecasts to aggregating advanced scouting data. Using these systems to run NFL mock drafts brings a new dimension of impartial reasoning—free from hometown bias, but not from the same supply of public information and logic available to traditional draft analysts.USA TODAY Sports set up a controlled experiment: four top AI bots were instructed to select for all 32 teams in the first round, but the focus quickly zeroed in on the Chicago Bears at number 10. Writers at USA TODAY verified AI picks for eligibility and realism, but otherwise let the algorithms make their own choices based on publicly available draft boards, team needs, performance analytics, and recent free agency signings. The resulting picks each reflect a distinctive philosophy—and highlight both the promise and the limits of using AI for football decision-making.
Four Predictions, Four Philosophies
Let’s break down the choices from each AI, the reasoning provided, and what that may reveal about the evolving art and science of NFL mock drafts.Microsoft Copilot: Jalon Walker, LB/Edge, Georgia
Microsoft’s Copilot opted for a defensive injection, selecting Georgia’s Jalon Walker—an athletic linebacker with edge-rush capability. According to Copilot, the Bears’ offseason investment in the offensive line (notably, in free agency) made this a logical pivot to address pass rush, especially after a 2024 season in which the Bears’ pass defense was serviceable but hardly elite.Copilot labeled Walker a “versatile defender to boost their pass rush,” a nod to both his hybrid skill set and the Bears’ affinity for drafting multipositional defenders. In past seasons, Chicago has sought out versatile front-seven players who can move fluidly between linebacker and defensive end—see recent selections and acquisitions under GM Ryan Poles.
The case for Walker is bolstered by trends in both real-life draft history and consensus big boards, with Walker frequently cited as a late top-10/early teens pick due to his production and long-term upside. Still, it’s important to note that LB/Edge remains one of the more volatile draft positions; teams have found both stars and busts in this mold in recent years.
Verification and Risk
Walker’s credentials as a pass-rushing linebacker are well-established, but there is an inherent gamble in hybrid defenders: will NFL schemes lean into their versatility, or will the player struggle to find a defined role? Additionally, the Bears' depth chart at LB/Edge is not desperately thin after recent acquisitions; a top-10 edge pick suggests a belief in Walker's ceiling rather than an immediate need.Meta AI: Shemar Stewart, Edge, Texas A&M
Meta’s AI bot took a slightly different tack, zeroing in on pure upside by picking Texas A&M’s Shemar Stewart. Stewart’s career arc at the college level has been a study in scouting projection versus statistical production. Meta’s bot compared him to NFL stars Myles Garrett and Mario Williams for his “physical talent,” despite Stewart posting just 1.5 sacks in each of his three college seasons—numbers that at first glance might concern risk-averse front offices.The AI justified the pick by referencing the Bears’ urgent need to “boost their pass rush,” advocating that Stewart’s athletic ceiling is too tantalizing to ignore. This is a classic “traits over tape” selection: NFL teams often covet edge rushers with elite testing metrics and physical tools, even if their college production is modest.
Strengths and Red Flags
Stewart has drawn legitimate attention for his combination of length, burst, and motor on film. Evaluators consistently note that his best football may be ahead of him if he lands with the right development staff. However, history is mixed: for every raw-but-dominant edge who blossoms in the NFL (see: Danielle Hunter), there are just as many for whom the production never fully materializes.It’s worth flagging that while many scouting outlets agree on Stewart’s sky-high ceiling, the direct comparisons to Myles Garrett—a generational prospect with 10+ sack seasons—are best treated with caution. AI, much like human draftniks, can get swept up by physical comps that aren’t always predictive.
Grok: Tetairoa McMillan, WR, Arizona
Grok, known for its quirky logic and often fresh perspective, turned the focus to offense, selecting Arizona wideout Tetairoa McMillan. This is a vote of confidence in new franchise quarterback Caleb Williams, providing him with a third major receiving option as Keenan Allen faces free agency and DJ Moore and Rome Odunze hold down the top two spots.The AI’s logic follows recent trends in team-building: surround a young, high-pedigree quarterback with as many top-tier targets as possible. Grok rightly pointed out that as the Bears overhaul their offensive scheme and supporting cast, the addition of McMillan would give Williams a dynamic, three-pronged attack reminiscent of teams like Cincinnati and San Francisco, who prioritize depth and versatility at WR.
Is It Likely?
McMillan’s name is steadily climbing draft boards, with several outlets projecting him as a potential top-15 selection if his production and testing numbers continue on their current trajectory. A third receiver is not the Bears' most urgent need with Allen possibly returning or other free agent options, but the best drafts often blend immediate needs with long-term value and talent stacking.ChatGPT: Kelvin Banks Jr., OT, Texas
Rounding out the quartet, ChatGPT played it safe—but smart—by addressing the left tackle spot with Kelvin Banks Jr. With Darnell Wright currently established at right tackle, ChatGPT suggested that the Bears could still use a long-term solution at left tackle, especially to protect their rookie investment in Williams.“Offensive tackle is always worth a top-10 pick, especially when you have a young QB to protect,” the bot reasoned, echoing a belief widely held by both analytics departments and traditional scouts. Elite tackles rarely reach free agency and often become franchise cornerstones for a decade or more.
Analytical Backing
The statistical argument for this pick is ironclad: teams that protect their young quarterbacks tend to accelerate their development, reduce turnovers, and maximize offensive consistency. Banks is widely projected as one of the safest prospects in the class, checking every box for physicality, agility, and tape against top-tier competition. He doesn’t offer quite the same “wow” factor as top-3 tackle prospects in recent drafts, but as a plug-and-play bookend opposite Wright, he would represent value, need, and stability.The AI Edge: Advantages, Pitfalls, and Pro Football Context
So what can we actually learn from this experiment in algorithmic draft projection—and more importantly, what can front offices take from these findings?Notable Strengths of AI Mock Drafts
- Breadth and Speeds of Data Analysis: AI can scan thousands of reports, rankings, and media updates instantly, helping illuminate consensus picks and “sleepers” that humans might miss.
- Objective Need Assessment: Unlike some fan or media mock drafts, AI models tend to prioritize actual roster needs, recent free agent moves, and analytic measures.
- Scenario Planning: AI can quickly generate multiple “what if” scenarios, allowing teams to visualize how different picks change the board for subsequent rounds.
Key Risks and Limitations
- Dependence on Public Data: AI models only “know” what is publicly available (unless privately trained on proprietary scouting reports). This can limit their insight into medical flags, personal interviews, and private workouts.
- Potential for Overfitting Narratives: While human analysts can “fall in love” with a prospect, AI sometimes overweights public sentiment, physical comps, or statistical trends, ignoring on-the-ground context that truly drives draft-day decisions.
- Lack of Intangibles Analysis: Leadership, personality, football IQ, and adaptability are tough for models to quantify; these attributes often tip close evaluations inside war rooms.
How Accurate Are These Projections?
Historically, AI-powered mock drafts have fared about as well as top-tier human draftniks in the uncertainty-rich top 10-20 picks. For example, composite AI models correctly identify 60-70% of first-round selections—on par with reputable draft analysts, per aggregated second-order studies by sports analytics firms. However, precision drops significantly for landing exact team-prospect matches outside the top five picks due to the domino effect of unforeseen trades and late-breaking rumors.The picks above all make plausible sense for Chicago at number 10, and each is firmly within the range of conventional wisdom among scouting outlets. Yet none seems so overwhelmingly obvious or unique that it would signal AI "knows" something the league does not.
The Chicago Bears’ 2025 Draft Conundrum
All four AI selections illuminate one fact: the Bears are poised to add a high-caliber player at a key position of need. Whether that is a dynamic edge rusher, a foundational offensive tackle, or a new offensive weapon for Williams will depend on the board’s flow, new information in the run-up to the draft, and perhaps last-minute team evaluations that not even AI models can anticipate.Fact-Checking the AI-Generated Names
- Jalon Walker: Ranked in the consensus top-15 players as of last update; “versatile defender” profile accurate but not the universal No. 1 edge rusher on the board.
- Shemar Stewart: Considered a high-ceiling, lower-floor prospect by scouting services, with performance comps to elite NFL edges scored as “hopeful” but not yet predictive. Production concerns are real but mitigated by rare athletic traits.
- Tetairoa McMillan: Entering the draft cycle as a top-20 player per most mock aggregators, with size, ball skills, and route polish generating real buzz. Any mock that places him in Chicago is defensible, especially amid uncertain WR free agency.
- Kelvin Banks Jr.: Projected as one of the two or three best tackles in a deep class; selection at 10th overall would not be a reach by consensus standards.
Offseason Context and Implications
Ryan Poles’ front office is betting on quarterback Caleb Williams as the franchise’s long-sought answer under center. Everything about their approach—free agency, the Allen trade, the addition of Rome Odunze—signals an urgency to eliminate as many offensive question marks as possible. However, a defense-first pick would also align with Chicago tradition and strategic logic: in a division ruled by explosive offenses, loading up on edge talent and hybrid defenders offers a hedge against NFC North rivals’ attacks.Bears’ fans should be both encouraged by the depth of quality options available at No. 10 and aware that even the best projections are educated guesses. The front office’s “big board” may already be set, but contingencies—trades, unexpected slides, or late-emerging red flags—can and will shape the final outcome.
AI Versus Human Mock Drafts: Complement or Competition?
The proliferation of AI-driven mocks has led some to speculate about the future of NFL draft coverage. Are human analysts obsolete? Unlikely. AI excels at broad-scope data crunching, flagging outliers, and scenario mapping, but the draft will always reward teams that synthesize analytics with real-world relationship building, in-person scouting, and risk tolerance.Rather than replacing the Mel Kipers and Daniel Jeremiahs of the world, expect AI tools to become an ever more critical supplementary resource—helping analysts gut-check their own biases, test new approaches, and maybe even anticipate league trends before they hit the mainstream. For fans and fantasy GMs alike, AI-powered mocks offer a fascinating new set of expectations and scenarios to add to the annual pre-draft excitement.
Final Thoughts: What Should Bears Fans Expect?
Will the Chicago Bears take a pass rusher to keep pace with Detroit’s loaded O-line? Will they grab a blue-chip tackle to guard the franchise quarterback? Or will they give Williams another dynamic playmaker to unlock the full potential of their offense? As of now, even the most advanced AI tools—drawing on everything from historical draft heuristics to consensus big boards—can only hazard an educated guess.One lesson is clear: the margin for error between good, great, and franchise-altering picks is razor thin, whether the selection comes from a human or a machine. The 2025 NFL Draft will no doubt serve up its share of surprises. But thanks to innovations like AI-powered mock drafts, the conversation has never been more sophisticated—or more fun.
In the end, the Bears’ decision at number 10 will be shaped by a blend of cold analytics, gut instinct, and a little draft-night luck. For fans and football obsessives, that’s exactly as it should be.
Source: Yahoo Sports NFL mock draft 2025: Artificial intelligence predicts who the Chicago Bears will select