AI is often seen as a tool for efficiency, but McKinsey took a different approach. Instead of adding AI as a feature or an afterthought, they rebuilt their entire business model around it. At the center of this transformation is Lilli, McKinsey’s generative AI platform, which is now the driving force behind how 45,000 professionals collaborate, access knowledge, and create value for clients. For executives wondering how AI can move from being a buzzword to becoming integral to business success, Lilli offers a valuable case study. McKinsey is using AI to comprehensively reshape their operations and build a system that delivers measurable, real-world results. AI as Core Infrastructure, Not a Supplement AI as Core Infrastructure, Not a Supplement McKinsey’s approach to AI wasn’t about experimenting with technology or using it for isolated tasks. Instead, they focused on building AI into the heart of their operations. In July 2023, McKinsey launched Lilli firm-wide. Today, 72% of their employees use it regularly, generating over 500,000 prompts each month. Lilli has become the foundation for how McKinsey works. The results speak for themselves. With Lilli, McKinsey has saved over 50,000 consultant hours every month. Time that used to be spent searching through documents is now dedicated to high-value tasks like strategy development and client engagement. This transformation shows that AI doesn’t need to be a bolt-on or a one-off project. If you want to see real business value, AI must be deeply integrated into your operations. How Lilli Transformed McKinsey’s Knowledge Operations How Lilli Transformed McKinsey’s Knowledge Operations Lilli is a fully integrated platform that powers McKinsey’s knowledge engine. By automating routine tasks, saving around 50,000 consultant hours. That time goes back into client work, from refining strategies to faster delivery. The platform sits inside daily workflows. Over 70% of consultants use it to tap into McKinsey’s proprietary knowledge base of more than 100,000 documents and frameworks. Each response is grounded in the firm’s own data, not public internet filler. Security was part of the build from day one. Lilli runs on a zero-trust architecture with role-based access and full audit trails. Teams work fast and stay compliant. Speed isn't the only outcome. Deliverables that took days now take hours. Proposal win rates are rising. Junior consultants shift from background research to narrative and insight. Senior leads focus on planning and mentorship. Lilli also improves knowledge-sharing. It helps teams find the right materials and connects them with the right internal experts. That reduces friction and supports faster decisions. Clients in sectors like life sciences and logistics are now deploying their own tailored versions of the system. The underlying architecture is flexible enough to travel. To support scale, McKinsey created an internal AI playbook. It covers deployment models, governance, and adoption practices. The result is a repeatable system, not just a successful tool. AI Is Not a Quick Fix AI Is Not a Quick Fix While McKinsey’s success with Lilli is impressive, it highlights an important point for businesses: AI is not a quick fix. Many companies treat AI as an add-on solution, hoping it will solve specific problems without addressing their broader operational needs. However, to reap the full benefits of AI, it must be integrated into the core of the business. This requires significant effort, upfront investment, and a shift in how the organization operates. McKinsey didn’t simply adopt AI as a tool. They rebuilt their entire approach to knowledge work. This level of transformation takes time, but the results are clear. Businesses that treat AI as a bolt-on will struggle to see sustained success. How to Build AI as the Core of Your Business How to Build AI as the Core of Your Business Executives often ask how McKinsey turns AI initiatives into measurable business outcomes. The key lies in treating AI as infrastructure that integrates deeply into day-to-day operations. Companies achieve real results when AI becomes central to daily workflows. It should not exist as an optional or isolated feature. To drive meaningful impact, prioritize your organization's proprietary data. Leveraging internal datasets, especially sensitive information like customer insights or operational metrics, creates tangible business value. Publicly available data may seem easier to use. But it rarely provides the competitive edge gained from insights rooted in your own business context. Finally, view AI as a way to augment existing talent within your teams. Automating repetitive tasks allows junior staff to contribute more effectively. It frees senior leaders to focus on strategic decisions. Design your systems for flexibility and scalability. AI adoption is a continuous, iterative process. AI as the New Standard AI as the New Standard McKinsey’s success with Lilli is a testament to the potential of AI to transform business operations. As AI becomes more embedded in day-to-day operations, it will no longer be a luxury or a trend. It will be the standard. For executives, the question is how to integrate it into the core of your business. AI must be more than an add-on tool. For real impact, AI has to be the backbone that drives business outcomes. McKinsey has proven that when AI is fully integrated, it delivers significant value. The businesses that succeed in the AI-driven future will be those that rebuild their infrastructure around it. Now is the time to build. Don’t wait for AI to be perfect, start making it a core part of your business today.

How McKinsey Rebuilt Its Business Around AI—And Why It’s Working

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