Every CEO knows the same uncomfortable truth: hiring decides whether the rest of the strategy works. Yet recruiting still gets discussed with a fraction of the rigor that product or growth get, and the gap is widening as AI rewrites the day-to-day of the craft.
That gap is what Metaview's 10x Recruiting community exists to close. The most recent London event put four talent leaders on stage to walk through how they're rebuilding hiring for the AI era: Siadhal Magos (Co-founder and CEO, Metaview), Ash Rama (VP of Talent, hyperexponential), Lucy Szypula (Head of Talent, hyperexponential), Justin Bishop (Global Head of Recruiting, Miro), and Jamie Edwards (VP Talent and Organization Development, Deliveroo).
The conversation reframed what carries forward into 2026. The leaders who'll set the bar are the ones treating AI as the fabric of how recruiting operates: rebuilding workflows from scratch, multiplying their own impact, and trading time to hire for quality of hire as the metric that actually matters. Here are the five shifts they're betting on.
AI is now core to the craft
The panel agreed on the framing within the first ten minutes: AI fluency is now part of what it means to be a serious recruiter, not a side hobby for the technically curious. Lucy Szypula put it cleanly: "AI is now a must have. For everyone who cares about their profession and takes it seriously, AI is absolutely the expansion of our craft. It's helping us achieve outcomes we couldn't imagine before."
At hyperexponential, that conviction shows up in the artifacts. Lucy's team has built AI-enabled coaching programs for hiring managers and automated workflows that lift interview quality while cutting manual effort. The appetite, she said, is only growing. None of that is rhetorical. It's the operating reality of a talent team that decided AI was load-bearing and built accordingly.
Siadhal Magos framed the next three to five years as a single design problem: how humans and AI work together to build teams. The recruiters who treat AI as both a productivity engine and a creative collaborator are the ones who'll move quality up, not just speed.
AI is now a must have. For everyone who cares about their profession and takes it seriously, AI is absolutely the expansion of our craft.”
The best recruiters rebuild, not retrofit
The most cited mistake on the night was layering AI on top of a process that was already broken. Jamie Edwards described the Deliveroo philosophy: "We're now at a point where there's a lot we can take as a given (the tasks and activities that can be automated). The next step is using AI to uncover what we didn't know we didn't know, and to redesign how we operate."
Ash Rama drew the now-familiar three-tier map. "There are people who use AI to replace Google. People who sprinkle it on top of what they already do. And then there's the third group: the ones who stop and rebuild with AI. That last group is the most interesting, because when AI is in the fabric of what you're doing, it can transform how you operate."
Hyperexponential's team has moved through both stages. They started by layering AI into what they already did, reviewing interviews and improving feedback. Now Lucy's frame for every workflow is sharper: what's the least a human should do here, and what can we reimagine completely? That's the question separating the teams that compound from the teams that automate the same plateau they were already on.
- Intake calls captured in scattered notes, decay within 48 hours
- Scorecards filled out post-interview from memory
- Hiring manager coaching limited to whoever the recruiter happens to sit next to
- Time to hire treated as the headline metric
- Every intake call captured verbatim, structured into requirements automatically
- Scorecards generated live from interview signal, edited not authored
- Coaching loops powered by interview analysis, surfaced for every hiring manager
- Quality of hire anchored in company-specific DNA rubrics
Recruiters who scale themselves win
At Miro, Justin Bishop treats AI less as a procurement decision and more as a culture decision. "We give recruiters the freedom to play around with AI. If you want to create something, try it. And if it works, we'll scale it out. It's created a culture of empowerment." The team builds its own automations and shares the ones that stick.
That changes the recruiter job description on the margin. It's no longer about managing a process. It's about using technology to extend reach, sharpen decisions, and multiply output without multiplying headcount. Siadhal put the broader trend bluntly: the most effective recruiters aren't just the ones doing great work, they're the ones building systems that help them do more great work, faster.
The recruiters who'll thrive in the AI era are the ones who learn to scale themselves. Not by working longer hours, but by codifying their judgment into workflows that compound while they sleep. Read how recruiters are using Claude in production for one concrete pattern.
Taste is the new superpower
As more of the recruiting workflow gets automated, the differentiator collapses to two things: judgment and taste. Jamie's framing: "We're empowering our team to build their own tools. But that means they need taste, and an acumen for what great digital experiences look and feel like."
Deliveroo now interviews for it. The team looks for examples of how candidate recruiters have innovated, how they've improved candidate experiences, and how they've found new ways to reach talent. The hiring bar for talent teams is no longer just process discipline. It's design sensibility too.
We're empowering our team to build their own tools. But that means they need taste, and an acumen for what great digital experiences look and feel like.”
AI delivers the efficiency. The recruiter delivers the experience. The future of recruiting will reward the people who can hold both at once: smart and seamless, automated and deeply human. That's the brief.
Quality of hire is the new goal
For two decades, time to hire sat at the top of the recruiting dashboard. The panel called the end of its reign. Justin: "If you hire quickly, you can reduce quality. If you focus only on quality, you can lose speed. But I think the KPI around time to hire will start to disintegrate."
What replaces it is quality of hire: how many high-quality employees a team is bringing in, and what those hires actually do for the business once they're in seat. Justin's team is operationalizing it by identifying "Miro DNA" and rebuilding the entire hiring process around the signals that predict it.
Lucy described AI's role in the shift. It's not replacing the human element. It's giving teams sharper insight into what great looks like: analyzing interviews, spotting skills gaps, coaching hiring managers (the good-interviewer / bad-interviewer divide stops being a vibe and starts being a measurable thing), and feeding all of that back into the rubric. AI delivers new hires faster and at greater scale. The best recruiters use that speed to spend more time on quality, not less.
Where AI gives recruiting teams use
Surface candidates who match the intake-call signal, not just the keyword list. The pipeline gets narrower at the top and stronger at the bottom.
Rank inbound applicants against the ICP the hiring manager actually described, not the JD that got posted three weeks ago.
Capture every interview verbatim, generate a structured scorecard live, and feed the signal back into hiring manager coaching.
Tie hires to business outcomes through a quality-of-hire rubric the whole leadership team trusts and reads weekly.
The cost of staying with the old playbook is more concrete than most teams admit. According to Metaview's 2026 AI and Hiring Alignment Report, surveying 505 recruiting leaders and hiring managers across North America and EMEA, slow, retrofit-style hiring ops bleed candidates and burn trust at every stage. The numbers below are what the panel is rebuilding around.
The pattern is consistent across the panel. Teams that rebuild from the intake call forward, with AI in the fabric instead of bolted on, move quality and speed in the same direction. Teams that retrofit move neither.
The operating shift
The London evening reaffirmed the obvious thing that's easy to forget when the conversation gets too technology-heavy: recruiting has always been about people, and always will be. The panel agreed that the most exciting opportunities go to the teams willing to experiment, rebuild, and redefine what great looks like. Three moves to take into 2026:
One: rebuild before you retrofit. Pick the workflow that's costing the most and ask Lucy's question. What's the least a human should do here? Rebuild from that answer instead of layering AI on top of the existing pattern.
Two: scale yourself, not just your team. Codify the judgment that lives in your head into systems your team can use. Justin's empowerment culture only works because every recruiter is allowed to build, test, and ship.
Three: trade time-to-hire vanity for quality-of-hire honesty. Identify your "DNA" (the signals that actually predict success at your company) and rebuild the entire hiring process around them. Use AI to read the signal, not to chase the clock.
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Frequently asked questions
What does it mean to "rebuild with AI" instead of retrofit?
Retrofitting means adding an AI step to a workflow that was designed without it (summarizing interview notes, drafting outreach copy, ranking applicants). Rebuilding means asking what the workflow would look like if AI were assumed from the first design call. The Deliveroo and hyperexponential teams both made the leap by starting from the intake call and redesigning everything downstream, instead of inserting tools into the gaps of the old process.
How do you measure quality of hire if time-to-hire is no longer the headline metric?
Justin Bishop's approach at Miro is to identify the company-specific signals that predict high performance ("Miro DNA") and build the entire hiring process around them. Common inputs: 90-day retention, hiring-manager satisfaction at 30 and 90 days, ramp time to first impact, and whether the hire moves the business outcome the role was created for. The point is to define quality before you optimize for it.
Why is "taste" suddenly a recruiter skill?
When recruiters can build their own tools, the constraint shifts from "can we do this" to "is what we built any good." That requires aesthetic and editorial judgment. Deliveroo now hires for it directly: candidate experience design, attention to candidate-facing copy, and the ability to spot when an automation crosses from helpful into creepy.
How does AI fit into hiring-manager coaching?
Hyperexponential built AI-enabled coaching programs that analyze interview recordings, surface specific moments where the hiring manager could have probed harder or stayed calibrated longer, and turn those into personalized coaching prompts. Done well, it lifts interview quality across the whole hiring-manager bench, not just the ones who happen to get formal training.
Where should a recruiting team start if they want to rebuild instead of retrofit?
Pick one workflow with high pain and clear feedback. Intake-to-scorecard is the most common starting point because the signal loop is fast and the use is obvious. Capture the intake call verbatim, generate the requirements automatically, run interviews against that spec, and feed the resulting scorecards into a quality-of-hire rubric. Get one loop working end to end before you touch the next.
