AI in Action Beyond Experimentation to Transform Industry 2025

AI is poised to reshape critical aspects of work – what is done, who does it, when it’s done and how it’s performed. GenAI, in particular, is expected to increasingly redefine work across industries, drive labour productivity, improve decision-making and augment human capabilities.  To prepare for this transformation, organizations need to prioritize workforce development to enable employees to navigate technological changes and lead AI-driven value creation.  Engagement with the community and research by the World Economic Forum’s Center of New Economy highlights some key actions related to the workforce, including: –Building AI capabilities: Organizations are increasingly aligning their structures with AI goals, led by organizational moves such as appointing chief AI officers or forming AI strategy teams. AI is becoming integral to business functions, with dedicated AI-driven roles in operations, marketing and risk.   –Agile, data-centric cultures: Promoting cross- functional teams and cultivating a data-driven, adaptive culture can accelerate AI adoption. Designated employees (“change champions”) can also play a crucial role in embedding AI into an organization’s operating model that embraces experimentation. –Human-AI interaction: As AI handles routine tasks, jobs requiring AI management, data analysis and creativity will grow, alongside the need for emotional intelligence to facilitate smooth human-AI collaboration.42 As AI takes over routine tasks, human roles are expected to shift towards higher-impact activities, increasing human-computer interaction. To prepare for these changes, companies must reskill employees and ensure AI is designed to work harmoniously with humans, taking into account human needs and considerations.   –Continuous learning and change management: Surveys show that many workers are concerned their organization’s AI implementation will cost them their jobs or lead to stress, burnout or overload.43 To address these concerns, organizational support to help employees build trust in AI-driven processes and integrate the technology successfully into their work is essential. Chevron’s pivot to renewable energy required new employee skills and expertise. To help address its lengthy recruitment cycles, Chevron turned to an AI talent acquisition platform, which saved the energy firm about $10 million by efficiently assessing organizational skills gaps. The platform also accelerated Chevron’s hiring process by 30%.44CASE STUDY 11 Talent transformation A hospital services company adopted AI to improve discharge planning. To achieve this, its machine learning model analyses over 72 variables to predict discharge readiness within 24 hours, providing actionable insights through a cloud-based interface. Deployed across 12 hospitals, the tool has increased daily discharge rates by 4.6% in six months, streamlining patient transitions and easing bottlenecks.CASE STUDY 12 Human-AI collaboration Organizations need to prioritize workforce development to enable employees to navigate technological changes and lead AI-driven value creation.Company-level enabler 2: Talent and organization AI Governance Alliance: Transformation of Industries in the Age of AI 17