Future AI Driven Changes in NFL Front Offices

To give us a natural runway for introducing unique processes and ways of thinking, our lens will be a new ownership group. We’ll hit five primary areas along the way:

• Building the core (Leadership) 👈🏾👈🏼

• Developing Talent (Player and Personnel Development)

• Telling the story (Marketing)

• Getting fans into seats (Ticketing)

• Bringing the energy (In-game Experience)

“Building the core” boils down to how AI can enhance the ways ownership groups identify and retain championship-caliber talent where it matters most. The spine of this challenge is identifying primary leaders who understand and are capable of bringing the overarching vision to life. This process will forever (and should) be human-driven, but AI is quickly making the process far more dynamic.

Finding your Foundation

Relationships will never not play an outsized role in how front office roles are filled, but with the cost of doing business (and the potential for ROI) growing season over season, making hyper-informed decisions is more critical than ever. NFL teams—like most organizations—have access to more comprehensive data than ever before. To help with those decisions, what if you could interject tailored, situation-specific challenges into the interview process, allowing your team to see and analyze how candidates work through pivotal situations?

That’s where I think we’re headed with what we’ll call “critical moment scenarios.” The job interview process on the whole doesn’t really assess how candidates solve problems in atmospheres that resemble what would be their day-to-day. Time constraints also limit the complexity of the scenarios that can be talked through. Avoiding that during the traditional interview process is almost impossible, but the potential to build a platform that helps identify that blind spot is closer than you think.

An actual ball example: let’s say you’re interested in hiring a candidate from the Eagles’ front office because you value their emphasis on building their fronts via premium draft capital, but you’re concerned that their philosophy of locking up young impact players early doesn’t quite mesh with your intention to build an analytics-heavy “Moneyball” approach.  

Critical moment scenarios will allow you to present the candidate with an athlete contract situation that details key facets like current salary cap information (able to be adjusted so they can see the potential effects of their potential decisions), a “current” roster (tailored any way you want, of course), an archetype of their agent’s style and tendencies (if you’ve got a ton of guys in the Mulugheta/Athletes First camp, you can crank up the guaranteed money hard-line), and comps of players who could potentially be available (or get really Nicey and layer in potential rookies for that upcoming draft class, complete with their current PFF grades - or your own staff’s grades - then give yourself an actual draft slot). 

From there, the candidate will be able to work through the layers of the decision, like signing or letting the athlete walk; how the void can be filled if they ultimately decide re-signing the athlete isn’t the best path, as well as their perspective on the ripple effect of their cumulative decisions. 

Each step of the way, AI will help support your assessment by automatically tracking and analyzing the tools they used; what questions they asked your virtual pro personnel and scouting staff (built from insights from your own scouting and pro personnel staffs); and the reasoning they shared for why they made their decisions. 

This would give groups a different, more authentic level of depth in understanding how the people charged with building their roster think and problem solve. 

Keepin’ ‘em Happy

Retaining talent is as much about the situation the person is leaving as it is about where they could potentially go. This makes arming your talent with optimized tools that help them do their job better, do more of the stuff they love (and that drives value) a distinct advantage in keeping teams intact.

Efficiency is the needle mover here. Automation is the AI equivalent of blocking and tackling, and despite it lacking any level of sexy, the impact is priceless. Salary cap forecasting - faster, deeper, and more agile, all driven by simple-language text prompts. Employee and athlete satisfaction - gathered, analyzed and reported on in real-time (no more surprises when the NFLPA drops its annual team report cards). Vendor agreement negotiations and contract execution - handled entirely, requiring only an overseer’s virtual signature.

War rooms during the draft are where it will get really wicked. We love the post-draft content that shows the breakneck-speed of draft-day trade decisions. But what if AI recording and transcript features (already on a lot of your iPhones if you’re able to upgrade to any iOS that starts with 18) could provide real-time valuations of the trades you're offered, with that valuation based on your data and metrics? This would give some real advantage in assessing incoming trade requests and understanding how to maximize value on the trades you send out the door.

The nuance and power of these examples will continue to grow, and with the success of teams like the Browns (current struggles aside) in leveraging data in new and unique ways, certain organizations will begin to find creative, innovative ways to build championship leadership teams.