Outcome-first AI: redesigning enterprise service delivery at scale
By Gayatri Guha When EY GDS Partner Tanu Garg took the stage at DevSparks Bengaluru 2026, she challenged one of the most common assumptions about enterprise AI: that its primary role is automation. “Artificial Intelligence (AI) is not about making existing processes faster. It is about rewirin
EY GDS Partner Tanu Garg delivered a keynote at DevSparks Bengaluru 2026, challenging the common assumption that AI's primary role in enterprise service delivery is automation. Garg argued that AI is about redesigning how enterprises deliver value, redefining processes, decision-making and value creation. Historically, service delivery was based around human capacity and linear workflows, but the integration of AI is changing how work moves across teams.
Garg highlighted three key areas for enterprise AI transformation: process redesign, scaling AI, and workforce readiness. Process redesign should focus on outcomes rather than activities, with organizations examining end-to-end workflows to identify bottlenecks and rethink outcome production. Scale involves moving successful AI initiatives from pilots into production through reusable assets and governance mechanisms.
Workforce readiness and responsible adoption are also crucial, with trust, explainability and accountability being embedded from the beginning. Garg stressed that measuring AI's impact, not just the effort, is changing how organizations evaluate performance and prioritize investments. AI is also transforming workforce roles, with teams shifting towards oversight, orchestration and decision-making.
The session emphasized a broader shift in enterprise AI conversations, with organizations now focusing on embedding AI into how work is designed, decisions are made and value is delivered.
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