Fiverr Cuts 25% of Staff in AI-First Pivot as CEO Calls for Startup Mode Reset

Fiverr cuts 25% of staff as it pivots to an AI-first operating model

Fiverr will lay off around 250 employees-about 25% of its workforce-as it restructures around an AI-first strategy. Founder and CEO Micha Kaufman told staff the company is "going back to startup mode" to become leaner, faster, and flatter with technology built around artificial intelligence.

Kaufman said AI is already embedded in products like Neo, Fiverr Go, and Dynamic Matching, and across coding, marketing, and customer care. The company now believes it can operate the existing business with fewer people while reinvesting in AI talent, infrastructure, and enterprise go-to-market.

Strategy: smaller org, bigger bets

• Flatten management layers and simplify infrastructure to speed up shipping cycles.
• Reallocate budget to AI capabilities, data pipelines, and platform modernization.
• Accelerate enterprise and long-term projects where AI demand and budgets are expanding.
• Maintain service continuity for freelancers; departing employees receive severance, extended healthcare, and career transition support.

Financial context executives should note

Fiverr's latest quarter shows the model shifting from broad marketplace volume to higher-value clients and managed work.

• Revenue: $108.6M, up 14.8% year over year.
• Services segment (incl. Fiverr Pro's Managed Services): up 83.8%.
• Marketplace segment: down 2% to $74.7M.
• Active buyers: down ~11% to 3.4M; average spend per buyer: up ~10% to $318.
• Adjusted EBITDA: $21.4M (vs. $17.8M a year earlier); Free cash flow: $25M, up 21%.
• Guidance: 2025 revenue $425-$438M; Adjusted EBITDA $84-$90M.

Translation for leadership: fewer, larger customers are driving growth, especially in AI-related services and managed enterprise projects. That concentration raises execution expectations on service quality, account expansion, and retention.

Fiverr Investor Relations

Why this move makes sense

• AI has cut manual work across internal functions and core products, improving speed and cost structure.
• Enterprise buyers want outcomes, not transactions-managed services and AI-enabled solutions fit that demand.
• Flattening the org reduces cycle time, a key advantage as AI product cycles compress.

Operational risks to manage

• Morale and productivity dip post-layoffs; over-rotate to AI without clear customer value can stall growth.
• Model reliability, data quality, and vendor reliance need strong MLOps and governance.
• Concentration risk rises as buyer count falls and average spend climbs.

For external perspective on AI's economic impact and productivity potential, see this analysis: McKinsey: The economic potential of generative AI.

Executive checklist: make AI-first real

• Run a 90-day AI audit: identify 5-10 workflows to rebuild with AI (customer support, marketing ops, code review, sales enablement). Quantify time and cost savings upfront.
• Restructure for speed: small cross-functional product squads (PM, engineering, design, data) with direct access to data and model tooling. Cut approval layers.
• Rebalance budgets: shift spend from headcount-heavy ops to data engineering, model hosting/inference, evaluation tooling, and security.
• Set operating metrics: time-to-ship, model-enabled coverage per workflow, unit economics by cohort, and enterprise expansion rate.
• People plan: offer fair severance and reskilling; hire for AI product management, data engineering, and applied ML. Protect critical domain knowledge.
• Customer strategy: package AI outcomes (e.g., managed services, co-pilots, workflow automation) with clear SLAs and ROI. Prioritize expansion within top accounts.

What to watch next

• Speed of product releases tied to Neo, Fiverr Go, and Dynamic Matching improvements.
• Enterprise share of revenue and attach rate of managed services.
• Buyer mix: can Fiverr grow average spend while stabilizing or improving active buyers.
• Gross margin trends as AI infrastructure spend scales.

If your team needs structured upskilling by function, see: AI upskilling by job function.

Bottom line

Fiverr is trading scale for focus-fewer layers, faster shipping, and a business oriented around AI-enabled services. For executives, the takeaway is clear: redesign the org and P&L around AI use cases that customers pay for, and measure the change with hard operating metrics.