EY Shifts Focus to AI-Native Operating Models
Artificial Intelligence
AI-Native
Operating Models
Digital Transformation
Ernst & Young
CES 2026
Workflow Automation
8
Strategic Reset
Media Hype
6/10
Real Impact
8/10
What is the Viqus Verdict?
We evaluate each news story based on its real impact versus its media hype to offer a clear and objective perspective.
AI Analysis:
While there's considerable buzz around AI's potential, EY's framework represents a grounded, strategic approach – a realistic assessment of the complexity and transformative nature of true AI integration, earning a high impact score with moderate hype due to the ongoing, generalized excitement around the technology.
Article Summary
Ernst & Young Global LLP is observing a significant shift in how organizations are approaching artificial intelligence, moving away from 'bolt-on' experiments towards fully AI-native operating models. Companies are recognizing that simply adding AI to legacy processes rarely delivers substantial transformation. EY’s counsel centers on a radical redesign of workflows, prioritizing outcomes and data, rather than optimizing individual tasks. This approach, championed by Dan Diasio and Hyong Kim, emphasizes a fundamental rethinking of how work gets done, moving from hundreds of isolated use cases to a cohesive, AI-driven system. The critical element is abandoning the instinct to retrofit intelligence – a mistake that many organizations made when initially exploring AI. This ‘AI-native’ mindset demands stepping outside established comfort zones and embracing role evolution, rather than simply automating existing jobs. The conversation is increasingly about people and roles, aligning human expertise with the capabilities of AI. This requires a cultural shift, reframing AI’s impact – not as a job replacement, but as an opportunity for augmented human capability. This is driven by the need to avoid getting stuck in legacy assumptions and creating inefficient, siloed processes that ultimately hinder the true potential of AI.Key Points
- Companies are moving beyond ‘bolt-on’ AI experiments towards AI-native operating models.
- The key is to fundamentally redesign workflows from the outset, prioritizing outcomes and data, rather than optimizing individual tasks.
- A cultural shift is required – moving away from outdated assumptions and embracing role evolution rather than simply automating existing jobs.