# AI Chiefs Claim Zero Enterprises Have Truly Reinvented Core Operations Organizational politics and workflow inertia hinder meaningful AI transformation in large global companies. - **Source:** [Fortune](https://fortune.com) - **Published:** 2026-10-15 - **Topic:** [Leadership](https://brifing.si/c/leadership) - **Original article:** - **On Brifing:** https://brifing.si/s/363f7286-6869-42ba-aedf-b95806981f21 ## Core Transformation Remains Elusive Accenture CTO Marc Warner argues that almost zero large organizations have truly reinvented their core operations using artificial intelligence. Most firms currently limit AI deployment to peripheral tasks like transcription or marketing. True industrial reinvention requires targeting central business processes, which remains a high-risk endeavor that few leaders have successfully navigated. ## The Workflow Redesign Requirement Mastercard executive Greg Ulrich emphasizes that layering AI onto existing workflows yields minimal returns compared to full redesigns. Simply automating one step in an eighty-step process often creates bottlenecks elsewhere. Mastercard is currently restructuring its entire product development life cycle to enable smaller, faster teams rather than just deploying new software tools. ## Politics Over Technology Projects Warner now characterizes AI transformations as political projects rather than purely technical ones. While the actual builds involve engineering, the implementation requires managing internal organizational dynamics. Executives like AXA’s Matthieu Caillat note that the primary challenge is bringing people along, as internal resistance often outweighs the technical capabilities of the models. ## Accountability in AI Deployment When AI agents fail, responsibility is distributed across business owners, technologists, and security officers. Warner suggests companies should avoid a blame-heavy culture during the early stages of adoption. Instead, leaders should encourage experimentation, provided that critical incidents like security breaches remain under strict oversight by the chief information security officer. ## Short Shelf Life of Tools The rapid pace of AI development renders many internal tools obsolete within a single year. Mastercard is already rebuilding consulting tools created just twelve months ago because they are no longer useful. This volatility forces companies to abandon traditional long-term planning cycles in favor of more iterative, high-speed development and deployment strategies. ## Strategic Focus at AXA AXA shifted from an initial strategy of testing four hundred AI use cases to a more focused approach. The insurer now targets five hundred to seven hundred million euros in annual recurring pretax value by 2029. They are currently leveraging four billion unstructured documents to drive these specific, high-impact business process improvements. ## Control and Infrastructure Guardrails Mistral AI’s Marjorie Janiewicz highlights the importance of companies maintaining control over their own technology stacks. By utilizing open-weight models that run on internal infrastructure, firms can establish their own security guardrails. This autonomy is essential for organizations that prioritize data sovereignty and long-term stability over relying on external, black-box AI providers. ## Future Outlook and Constraints Accenture predicts the current pace of AI innovation will continue unabated until at least 2030. However, potential energy constraints in Western markets may emerge as a significant bottleneck by the early 2030s. Companies must balance aggressive AI integration with these looming infrastructure realities to ensure their long-term digital transformation strategies remain viable. ## Sources covering this story - https://fortune.com/2026/10/15/close-to-zero-ai-transformation-politics-projects/ — --- _Summary written by Brifing from the original reporting. Copyright in the original article belongs to its publisher; read the full piece at the link above._