Next week, I’ll be in Atlanta for the ERE Recruiting Innovation Summit, where the focus will be on meaningful conversations between the talent acquisition professionals who are leading our profession. The ERE team has put a lot into creating an experience built around connection, practical ideas, and the future of the profession. In that spirit, this week we’re going to take a look at how the team at GALLO has rebuilt talent acquisition around AI and agile squads in a fast-changing business.

When people think of GALLO, they think of wine.

Almost nobody thinks of a vertically integrated manufacturing and distribution empire that spans glass manufacturing, silica mining, logistics, bottling, spirits, beer, and non-alcoholic beverages.

Ryan Cook, Head of Talent Acquisition at GALLO, leads the team that hires for all of it.

Two years ago, Cook said, GALLO reassessed its talent acquisition operations “knowing that AI was going to have a significant impact,” and concluded that a more agile model would be needed.

From Traditional Teams to Agile Squads

GALLO’s talent function supports roughly 2,500 hires per year with a team of about 35 recruiters, scaling up during seasonal peaks.

Those hires span wineries, glass manufacturing, sales, logistics, and corporate staff. With so many necessary skill sets, hiring demand can be unpredictable. When GALLO entered the beer category in 2024, for example, sales asked TA to hire dozens of people in 90 days in a category where the recruiting team had no prior experience.

That kind of demand creates bottlenecks, handoffs, and chaos, so GALLO needed a more agile approach.

The team eliminated the idea that recruiters “belong” to business units and rebuilt recruiting around agile squads that realign daily based on what the business needs most.

Every squad includes a senior TA partner who acts as the business point of contact. But within the squad, there are no handoffs.

As Cook describes it: “Everyone has to know how to do everything.”

If an offer falls through, the squad pivots to sourcing. If an offer letter needs to go out, even senior recruiters do it themselves rather than creating a ticket for someone else.

This model removed much of the friction that exists in most TA organizations, but it also created a new problem. To allow everyone to be jacks of all trades, the processes themselves needed to be simplified.

Using AI to Streamline the Offer Process

Offer letters were one of GALLO’s biggest operational bottlenecks.

With different unions, business units, relocation packages, and compliance rules, the company had over 50 different offer letter templates. On top of that, there are often state rules, and even county-level requirements. With so many possible scenarios, recruiters found it challenging to remember every nuance.

To address this, the GALLO TA team built a single “alpha file” containing every clause that could ever appear in an offer, along with a rules engine that determines which clauses apply in which situations. Together, this created a single dynamic framework that now covers more than 1,482 unique hiring scenarios.

That framework is now embedded in an internal AI agent, built on an internal AI enabled compliance framework. Recruiters can ask the AI which clauses or documents are required for a given candidate, and the system checks every offer for compliance before it goes out.

For the first time, GALLO no longer has to audit offer letters after the fact. More importantly, any recruiter can easily generate an offer, which helps enable the squad model.

As Paradox (called Sophia at GALLO) took over scheduling and routine candidate questions, Cook shifted recruiting coordinator headcount into recruitment operations. That team now includes specialists focused specifically on hiring compliance, recruitment efficiency, candidate experience, and data analytics.

The Impact So Far

The new model is already producing results.

GALLO has improved its candidate experience, moving from #12 in 2024 to #6 this year in the Candidate Experience Awards, with an NPS of 47 versus the CandE average of 27. The team also saved 2,500 hours of recruiting work through efficiency initiatives.

Operationally, the impact shows up in speed and quality. In 2025, average days to offer acceptance dropped by 37 percent, and average days to official start fell by 21 percent. Over the same period, offer acceptance rates increased by 10 percent.

Productivity has improved as well. With roughly 2,500 annual hires across a team of 35, GALLO averages about 71 hires per TA staff member per year, putting the team well above typical in-house recruiting benchmarks.

AI is going to change the talent acquisition function whether companies are ready for it or not. What separates leaders from laggards is how they use AI to solve real operational pain points and then reorganize around what produces results. GALLO’s experience shows what that looks like in practice.

— David

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Conferences

ERE Recruiting Innovation Summit

Atlanta, GA
May 5-6, 2026

Real-world challenges will meet real-world solutions next week at the ERE Recruiting Innovation Summit. It’s not too late to join us in person in Atlanta or stream the entire Summit live from your home office.

Connect with today’s talent acquisition leaders, explore what works and what doesn’t, and get solid advice from peers who share many of your own experiences and challenges.

Experience the future of talent acquisition next month. We hope to see you there! (ERE Recruiting Innovation Summit)