Recruiting Is Being Optimized for Speed. It Should Be Designed for Outcomes.

Talent acquisition keeps getting handed tools built for speed and efficiency.

I understand why it is happening. Talent acquisition is a cost center, and the age of AI is all about supercharging knowledge workers so that smaller teams can do more with less. The pressure to shrink teams and automate processes is relentless.

Faster scheduling. Faster interviewing. Faster screening.

But the theme that I heard running throughout the ERE Recruiting Innovation Summit was that faster workflows alone do not produce better hires. There was a recognition that if TA is going to be judged on hiring outcomes, then we need to design the conditions that make those better outcomes possible.

Four ideas stood out.

The decision starts before the req opens

Several speakers pushed back on the assumption that "quality" is something that happens once candidates are already in the funnel.

"Quality of hire, from my perspective, is not solely a recruiter problem. It's an architecture problem," said Erin Walker of Teach For America.

Walker’s team was not trying to solve quality of hire by simply adding more candidates to the top of the funnel. She said the top of the funnel “has never really been an issue.” The harder work was identifying readiness and fit earlier, before those gaps were discovered too late in the process.

Damon Grothe of MacAllister Machinery made a similar point about interviewing. What we need isn't a better list of interview questions, it's a better foundation underlying the call itself: "I don't think it's that companies have an interviewing problem as much as it's a decision consistency problem."

AI should sharpen judgment, not replace it

There was plenty of practical talk about AI and its role in the hiring process at RIS.

AI is genuinely good at scale, prioritization, pattern recognition, and clearing administrative sludge. But the more invisible the process becomes, the less likely anyone is to question what comes out of it.

"Accountability rests with our recruiters. No algorithm can fully account for all of the decisions and nuances and edge cases it was never trained to see," Salesforce's Ed Delgado said.

Delgado was even sharper on accountability later in his session: "An AI tool is a prioritization tool. It's not a sole decision maker."

The choice isn't a binary "automate" or "don't." It’s deciding where AI assists, where it recommends, and where a human owns the call.

Candidates are deciding too

Candidates aren't just being evaluated. They're evaluating the company, the manager, the work, the recruiting experience, and whether the pitch they're hearing has anything to do with reality.

“When candidates are looking at organizations, they are trying to determine what’s real and what is just corporate polish,” Jay Olson of Medtronic said. “They are experiencing your people, the conversations that are taking place. That's what's actually leaving the imprint.”

Trust, but verify

In their session, Hannah Rodriguez and Rory Herriman of Zip described a hiring environment where fake candidates, AI-assisted interviews, and weak validation are no longer just recruiting annoyances. They affect the business’s ability to trust the hiring process itself.

As Herriman, Zip’s CTO, put it: “Talent acquisition is squarely now a fraud challenge and a cyber risk.”

Their answer wasn’t to bolt on more screening steps. Zip’s approach can be described as a system of controls: clearer role definitions, shared success metrics, checklists, escalation paths, hiring-team certification, and a process for stacking signals before making a call. The goal, Rodriguez said, was “a process that makes it harder to fake capability and easier to expose it.”

Special offer for ERE Weekly readers

These are exactly the kinds of deep practitioner conversations we want to continue having.

The next ERE Recruiting Innovation Summit takes place on November 10–11 in San Diego, with practitioner-led sessions, small-group speaker AMAs, and the kind of peer-to-peer conversations where TA leaders can compare what’s working, what isn’t, and what they’re still trying to figure out.

And for ERE Weekly readers, we’re offering a special price for San Diego: the first 25 readers to register can attend the Summit in person for only $899. That is the lowest rate we’ll offer from now until the Summit.

— David

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More Recruiting Insights

Amazon workers are under pressure to up their AI usage—so they’re making up extraneous tasks. Some Amazon employees felt pressure to “use more AI” without receiving clear guidance on what “good” usage looks like, so they started creating unnecessary agents just to burn tokens. I’m sure that many in TA can relate to the pressure from the top to get with the AI program. (Fast Company)

American Jobs with AI Exposure Really Are Starting to Disappear, Data Show. Gizmodo reports that BLS data shows employment in several AI-exposed occupations, especially customer service, sales, and administrative roles, is starting to decline even as overall employment grows. These rolls shrank by 0.2% in the last year, while overall employment rose by 0.8% in the same period. (Gizmodo)

Tech Layoff Wave Has Already Hit 100,000 Jobs This Year. Tech and startup layoffs have been the tip of the spear of AI-related layoffs, although it is debatable how much is just overcorrecting for over-hiring. These layoffs accelerated sharply in 2026, with more than 100,000 jobs already cut worldwide by early May and Q1 alone reaching about 81,700 layoffs. (Statista)

The AI economy is rewriting the American Dream — and blue-collar workers are poised to win. AI is cooling demand for many white-collar and entry-level jobs while creating a parallel boom in skilled trades tied to data centers, energy, construction, and infrastructure. All this is coming as the number of college graduates is expected to continue to rise for the foreseeable future. (CNBC)

Colorado’s fierce two-year fight over AI regulation ends with watered-down law. Colorado lawmakers passed a compromise bill that waters down and delays the state’s first-in-the-nation AI law, replacing detailed disclosure requirements with notice when AI is used in consequential decisions like hiring, housing, and lending. For a more pointed look at how this will impact hiring and TA, check out this video from Martyn Redstone of Warden AI. (Colorado Sun)

Conferences

ERE Recruiting Innovation Summit

San Diego, CA
November 10-11, 2026

Talent acquisition is moving fast. The best leaders are not just chasing trends. They are comparing notes, testing new approaches, and learning from practitioners who are already deep in the work.

This November, the ERE Recruiting Innovation Summit comes to San Diego for two days of practical insight, honest discussion, and peer-to-peer learning. You’ll hear real examples from recruiting teams tackling today’s biggest questions, from AI and automation to candidate trust, quality of hire, hiring manager alignment, employer brand, and recruiting at scale.

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