Abstract
The initial rush of generative AI adoption has peaked, but the era of substantial business value realization has barely begun. While 78% of enterprises now use generative AI, only 17% can attribute material EBIT growth to these investments. This disconnect signals a fundamental failure in enterprise design. Layering cognitive intelligence on top of fragmented, siloed operations does not increase speed; it accelerates friction at a higher cost . As enterprises confront rising operational complexity, disconnected intelligence, and slow decision cycles, the need for a unified approach becomes more urgent.
Our white paper outlines the shift to an Intelligent Operational Fabric, a unified model that breaks down barriers across procurement, HR, and IT to enable frictionless, autonomous scale. We demonstrate how our TurningEdge suite operationalizes this fabric by integrating embedded intelligence, Oracle Cloud capabilities, and workforce “superagency” to convert high AI adoption into measurable business impact. This white paper also explores the strategic shifts leaders must prioritize to build a truly AI-powered enterprise.
Key Insights
The impact of redesigning workflows is often localized rather than systemic. To achieve scale, organizations must move beyond ‘use cases’ to a holistic operational fabric.
Our vision for the autonomous enterprise is Intelligent Operational Fabric. It represents a shift from static tools to a dynamic operating model. This layer of embedded intelligence learns, adapts, and connects every operational domain.
Procurement is evolving from a transactional function to a strategic powerhouse. As noted in Harvard Business Review, the future lies in autonomous sourcing and risk mitigation. CPOs must now focus on building resilience against geopolitical shocks and ensuring ESG compliance.
The fear that AI will replace jobs is fading. The new focus is on empowerment. McKinsey describes this as "superagency." This is the ability for employees to command complex workflows and achieve outcomes that previously required large teams.
As AI scales, risk management becomes the CIO’s primary concern. The March 2025 McKinsey report indicates that large organizations are significantly more likely to actively mitigate AI risks, such as cybersecurity and accuracy.