The Role of AI in College Football Recruiting; What It Can and Can’t Do

A former Division I coach offers a firsthand look at how artificial intelligence is being used to organize recruiting and why it will never replace real evaluation.

MTSU head football Coach Rick Stockstill looks at his phone, in the football conference room, in front of a wall where new MTSU signees have been added as their paperwork arrives to the office, on Wednesday, Feb. 3, 2016, National Signing Day. 636691704512119581-71-MTSU-Coach-Rick-Stockstill.JPG / HELEN COMER/DNJ

Recruiting has never been short on information. It has always been short on time. I say that from firsthand experience as a former Division I college coach who has sat in recruiting rooms, built boards, and been responsible for making evaluation decisions under real pressure.

Every year, college staffs are asked to sort through thousands of prospects across multiple regions, platforms, and events, all while working within limited evaluation windows, small staffs, and nonstop timelines. Film pours in daily, camps overlap, rankings fluctuate and offers move quickly. In the middle of that chaos, good players still get missed. That reality is what brings artificial intelligence into the recruiting conversation, not as a replacement for evaluators, but as a tool to help organize a process that has become increasingly inefficient.

The Real Problem in Recruiting

The public perception of recruiting is simple. If you are good enough, you will be found. Anyone who has spent time inside a recruiting room knows that is not reality. Recruiting is a volume and prioritization problem. Staffs are managing boards, relationships, visits, portals, evaluations, and internal conversations simultaneously, often across multiple classes. Exposure frequently becomes a shortcut for ability, not because coaches believe it should, but because time forces hard decisions. This is not a lack of talent in the system. It is a workflow issue that continues to shape outcomes.

Where AI Actually Fits

AI’s value in recruiting is not prediction. It is organization. At its best, AI helps evaluators reach clarity faster by removing inefficiencies in the process. In film evaluation, AI can assist by sorting clips by situation, tagging repeated behaviors, and allowing coaches to study athletes within context rather than relying solely on highlight tapes. The evaluation still belongs to the human eye, but the path to that evaluation becomes more efficient.

From an exposure standpoint, AI can help compare production, measurables, and movement profiles across regions, offering staffs a broader view of athletes who may not exist in the same recruiting ecosystems. On the operational side, AI can streamline board management, communication tracking, visit histories, and regional pipelines, quietly freeing up hours that can be reinvested into evaluation and relationship building.

How AI Is Already Being Used, The 247Sports Composite

One of the clearest examples of AI already playing a role in recruiting is the Composite ranking system used by 247Sports. Rather than relying on a single evaluator or outlet, the Composite aggregates data from multiple recruiting services and weighting models to produce a more balanced view of a prospect’s standing nationally and by position.

In practice, this functions as an AI assisted synthesis that reduces individual bias, smooths out outliers, and organizes vast amounts of ranking data into a single reference point that coaches, media members, and fans can quickly understand. While the Composite does not replace live evaluation or internal recruiting boards, it reflects how data driven aggregation can bring structure to an otherwise fragmented recruiting landscape. Its value is not in predicting a player’s future, but in providing a shared baseline that helps contextualize prospects within the broader ecosystem.

What AI Can’t Do

There are limits that must be clearly stated, and I say this as an evaluator who has spent years studying athletes beyond the surface level. AI cannot evaluate competitiveness, read body language, understand how a player responds to adversity, or assess locker room presence and leadership. Those are things you learn through live evaluation, repeated exposure, and real conversations, not data points.

AI also cannot build trust with families or project how an athlete will grow within a program’s culture. Those responsibilities belong to coaches and evaluators who understand context and development. The danger is not AI replacing recruiters. The danger is mistaking data for judgment. Recruiting has always been about projection, fit, and development, and that is where human experience still carries the greatest weight.

Why This Matters for Families

For families navigating the recruiting process, AI has the potential to bring clarity if it is used responsibly. It can help identify realistic comparables instead of selling false hope, shift conversations toward fit rather than logos, highlight alternative pathways that align with development timelines, and reduce unnecessary spending on camps or exposure opportunities that do not match an athlete’s profile. When used properly, AI can help move recruiting discussions from hype driven narratives to informed and honest decision making.

The Ethical Responsibility

With any powerful tool comes responsibility. AI systems reflect the data they are built on, which means bias, incomplete information, and context free comparisons remain real risks. Over reliance on metrics without understanding individual circumstances can do harm if left unchecked. That is why AI must remain a support system rather than a final authority. Athletes are not datasets, development is rarely linear, and context will always matter in recruiting decisions.

The Future of Recruiting

The future of recruiting will not belong to the loudest platforms or the flashiest rankings, and that is something I believe because I have seen how decisions are actually made. It will belong to programs and evaluators who can see clearly, move efficiently, and still value the human side of development. AI will not replace recruiters, but evaluators who understand how to use AI to reduce noise, create clarity, and reclaim time will be better positioned in a system that demands precision more than ever. From my experience, the edge has never been technology alone. It has always been how wisely it is applied by the people making the final call.