The industries projected to gain the most productivity from AI automation by 2035 are those where work is data-intensive, language-heavy, or built around complex but pattern-based tasks. Finance and banking consistently top the rankings, with generative AI estimated to add value equivalent to roughly 2.8 to 4.7 percent of annual banking revenues through enhanced risk modeling, fraud detection, and customer-service automation. [1][2]

Healthcare and life sciences are close behind. AI accelerates drug discovery, automates clinical documentation, and supports diagnostic workflows, with pharmaceutical and medical-products sectors estimated to see impacts of around 2.6 to 4.5 percent of revenues. [1][2] Technology and software-intensive industries benefit from AI-assisted code generation, automated testing, and IT-operations tools, and because these firms already have mature digital infrastructure they tend to capture gains earlier than others. [3][4]

Manufacturing gains through predictive maintenance, quality inspection, and supply-chain optimization, raising equipment uptime and output per worker. Retail and consumer packaged goods see meaningful but somewhat smaller gains — roughly 1.2 to 2.0 percent of revenues — through demand forecasting, dynamic pricing, and personalized customer interactions. [1][2] Telecommunications and professional services, including legal work, are also strong beneficiaries: network optimization and large-scale document review, contract analysis, and legal research are well suited to current AI capabilities. [3]

At the functional level, the largest cross-industry gains are concentrated in customer operations, marketing and sales, software engineering, and research and development. [3] Empirical data already shows that AI-exposed industries are experiencing around 10 percent higher productivity growth, and notably this is occurring alongside job and wage increases rather than pure displacement. [5]

The main caveat is that these gains are uneven. The ILO notes that measured benefits so far are concentrated in larger, more digitally advanced firms, meaning smaller enterprises and lower-income economies risk being left behind. [6]