BUILDINGFILM

AI Transformation Without Layoffs: How Wix Did It in Under a Year

Invest in mindset alongside tooling: how Wix scaled AI-native transformation across 5,500 employees in less than a year.

May 7, 2026 32m

Asaf Yonay

Expert Insights

Asaf Yonay, GM of AI-Native Transformation & AI Platforms at Wix, makes the case that the hardest part of AI transformation at scale isn't the technology; it's the people. While most enterprise SaaS companies frame AI adoption as an efficiency play that justifies headcount reductions, Wix took the opposite bet: keep all 5,500 employees, and rewire how every one of them works.

He argues that mindset transformation, not tool selection, is what determines whether an AI initiative succeeds or stays a pilot. The hardest part isn't choosing the right LLM or IDE, but getting thousands of people to let go of workflows they've spent years perfecting. Wix achieved this by combining centralized enablement (an AI Core team of ~50-60 people), explicit non-optional commitment to AI adoption, and a culture that treats failure as part of the process.

Here are the key insights into his perspective:

AI adoption at enterprise scale needs to be non-optional, but paired with extensive structural support, making the alternative (falling behind) explicit, while providing the training, tooling, and infrastructure required to bridge the gap.
A centralized enablement team is more effective than scattered team experiments, because it lets every product group move fast without re-solving the same problems on training, tooling, and infrastructure.
AI transformation works best when adoption is AI-friendly, not AI-binary, making AI the easy path through specific workflows rather than mandating it across every process.
Leadership should explicitly tell teams they're going to fail repeatedly, and frame this as part of the process rather than a sign of poor execution.
The hardest and most valuable part of AI transformation is the mindset shift across thousands of people, not the technology selection, and Asaf considers this "the real win" of Wix's approach.

I know of a lot of companies that would say: we know that we can be AI-driven, and we don't need 50% of the headcount. And Wix has done the opposite. We're saying everyone has a valid chance to do that. And in order to be in that place, you need to do those small leaps. You can't say tomorrow morning everything is changing, if you're not here, then you're gone. Those small iterative steps - you're actually keeping your talent. And the metric that I'm judging myself by is velocity. If I can create velocity, that's great. It's up to the company to decide how they use it. And I think we have such a big backlog of things that I can see how we can be so much more productive using that velocity.

Monterail Team Analysis

Here are some actionable insights for software development teams pursuing AI-native transformation at scale:

Make AI adoption non-optional, paired with real support: Wix didn't issue a mandate without infrastructure. They standardized on a unified IDE (Cursor), built dedicated training programs, and assigned a centralized team to handle the operational complexity. The "left behind" framing works only when the organization has actually built the path forward.
Build a centralized enablement team before scattering initiatives: Wix calls theirs "AI Core" (~50-60 people). It owns training, tooling decisions, and shared infrastructure, letting every product team move fast without re-solving the same problems on prompt engineering, evaluations, or governance.
Treat failure as part of the process, and say so explicitly: When people first try AI tools, they get disappointed. The hype is "I can do everything with AI"; the reality is steep learning curves. Leaders who frame failure as expected - not as poor execution - accelerate adoption.
Optimize for velocity, not output: When AI tooling moves this fast, the company that decides quickest (even imperfectly) outperforms the one that analyzes longest. Stale decisions cost more than wrong ones in an environment where the technology shifts every quarter.
Make AI the easy path, not the mandatory one: Mandating LLM use across every workflow creates resistance and breaks legitimate processes that don't benefit from AI. Small wins compound. AI-friendly beats AI-binary.
Plan for AI tool redundancy from day one: Wix learned that teams who over-rely on a single LLM/IDE stop working when that service has downtime. Keep 2-3 viable alternatives in your tooling stack so a single provider's outage doesn't halt the company.