The solution to the AI skills gap is both global and local (www.techradar.com)

The AI skills gap has become acute: roughly 500,000 AI engineering roles are open globally, 72% of decision-makers plan AI investments in 2025, and AI jumped to the number-one scarce technology skill in 2025. Industry analysts warn this won’t be solved quickly—Gartner estimates 80% of existing software engineers will need AI upskilling by 2027—while the World Economic Forum predicts AI will net 78 million new roles (170M created vs 92M displaced). That combination of rapid demand, fierce competition, and a still-maturing technology stack means companies can’t rely on pay alone to fill ML/AI pipelines; they must rethink how they source, train and retain talent. The practical response is both global and local. Remote-first hiring expands the talent pool—most tooling and languages are English-centric and more than 80% of developers work remotely at least part-time—enabling round-the-clock productivity and wage flexibility. But remote hiring must be paired with deliberate inclusion: cross-cultural onboarding, asynchronous collaboration norms, meeting practices that avoid excluding non-native speakers, and real-time translation tools to make conversations genuinely two-way. For the AI/ML community this implies investment in scalable upskilling (training on ML pipelines, MLOps, data governance), collaboration and translation tooling, and measurable retention strategies—culture and growth opportunities can become as critical as compensation in solving the shortage.