Where to Hire AI/ML Talent in 2026
- Five critical questions to ask before choosing your next technical talent market — grounded in real hiring data and expert TA insight
- Market-by-market trade-offs across talent density, compensation, speed, and hiring culture to match your business constraints
- Actionable frameworks for defining “good,” benchmarking EVP, and evaluating retention dynamics in new regions
70% of organisations now use AI in at least one function — yet AI talent makes up less than 0.3% of total employment
What's Inside
The 2026 AI Talent Landscape
Why demand is outpacing supply, how layoffs have flooded the market without solving the hiring problem, and why “senior” no longer guarantees the right experience.
5 Questions Before You Hire
A structured framework covering role definition, compensation reality, operating constraints, market dynamics, and long-term retention — so you choose markets based on outcomes, not geography.
Market Trade-Off Analysis
How to evaluate talent depth, seniority availability, compensation benchmarks, and hiring culture across global markets — with insights from Talentful's expert team.
Who Is This For
Heads of Talent Acquisition
Tasked with scaling AI and ML hiring beyond saturated hubs — and need a data-backed framework to evaluate new markets against your specific business constraints.
CTOs & Engineering Leaders
Building applied AI, LLM, or MLOps teams and need clarity on where the talent actually sits — and what trade-offs come with each market.
People & HR Leaders
Supporting rapid technical expansion with workforce planning that connects talent strategy, compensation reality, and long-term retention.
Stop asking “where next?” — start asking “what do we actually need?”
Download the guide and map your AI/ML hiring strategy to the markets that can deliver.