EY's Tanu Garg: Stop automating, redesign around outcomes
Get the Tech newsletter
Daily tech — startups, AI labs, chips, the launches that shape the next decade. Free.
- Tanu Garg, EY GDS Partner leading AI Service Delivery Transformation, told DevSparks Bengaluru 2026 that AI is 'not about making existing processes faster' but 'rewiring how enterprises deliver value.'
- EY outlined three critical areas for enterprise AI: process redesign around outcomes (via EY.ai Value Blueprints), scaling beyond pilots into production (the AI Engine Room), and workforce readiness with embedded governance.
- Garg identified context — industry knowledge, enterprise data, governance requirements and business context — as 'the next frontier,' arguing reliable outcomes depend on more than model performance.
- EY introduced its Value Realization framework, with Garg's maxim 'you monetize impact, not effort,' shifting metrics from hours and activities to speed to market, quality, process simplification and revenue growth.
- EY.ai for Risk, co-designed with EY's Gen Z workforce and built on Nvidia's platform, keeps complex business, risk and compliance decisions under human oversight while AI handles routine work.
- EY cited a US travel management firm where an AI-enabled car booking app shipped in 3.5 weeks with a six-person team, versus an estimated 12 professionals over four months under a traditional approach.
- Garg argued workforce roles across engineering, architecture, product management and risk are shifting from execution toward oversight, orchestration and decision-making as AI absorbs routine tasks.
Why it matters: Enterprise AI programs have spent two years chasing pilots and productivity gains; EY's framing reframes the bottleneck from technology adoption to operating-model redesign, governance and context — meaning the firms that win on AI will be those that restructure decision rights and metrics, not just deploy more tools.
Ask SkimNews
