Most Companies Fail to Redesign Operations Around AI

Organizations are pouring unprecedented capital into artificial intelligence but failing to capture its full potential because they're bolting new technology onto old ways of working.

Despite more than $250 billion invested globally in AI during 2025, only one in four companies reports achieving transformative impact from their efforts, according to new research from the World Economic Forum. The gap between investment and results stems from a fundamental misstep: most organizations layer AI onto existing processes instead of rebuilding operations around intelligence from the ground up.

The AI-first blueprint

The World Economic Forum, working with consulting firm Kearney, has published a framework for what it calls "AI-first enterprises" — organizations that fundamentally rethink how they operate with intelligence at the core. The research draws on insights from more than 50 leading organizations to identify five essential building blocks.

These components include intelligence engines that power decision-making, adaptive technology stacks that evolve with needs, complete operations redesign rather than incremental changes, effective human-AI teaming models, and strategies for creating entirely new forms of value rather than just optimizing existing processes.

The blueprint features case studies from Indeed, Gamma, and Cognizant, demonstrating how these principles translate into practice. These examples show organizations embedding intelligence at scale to drive faster innovation cycles, measurably higher productivity, and business models that weren't previously possible.

Why it matters

The 75% failure rate on AI transformation reveals a critical strategic error that's costing businesses billions. Companies that treat AI as a feature addition rather than an operational foundation are competing with one hand tied behind their backs. As AI capabilities accelerate, the gap between organizations that redesign around intelligence and those that don't will become a defining competitive divide. Leaders need frameworks for systemic transformation, not just technology adoption.

From incremental to fundamental change

The research emphasizes that achieving transformative impact requires moving beyond automation of individual tasks. AI-first organizations redesign entire workflows, decision architectures, and value creation models. This means questioning assumptions about how work gets done, who makes decisions, and what products or services the business should offer.

The framework's focus on human-AI teaming acknowledges that successful transformation isn't about replacing people but about creating new collaboration models where human judgment and machine intelligence complement each other effectively.

The findings were first reported by the World Economic Forum in their publication "The AI-First Operating System: A Blueprint for Operating and Business Model Innovation," produced in collaboration with Kearney.