The consulting industry, long known for its hierarchical structure and reliance on junior analysts to handle routine tasks, is undergoing a fundamental transformation. At the forefront of this change is McKinsey & Company, one of the world’s most prestigious consulting firms, which has developed and deployed an internal AI platform called Lilli that is revolutionizing how consultants work and challenging traditional notions of entry-level employment in professional services.
The Birth of Lilli: A Strategic Response to the AI Era
In 2023, McKinsey launched Lilli, an internal AI platform named after Lillian Dombrowski, the first woman hired by the firm in 1945. This naming choice reflects both the company’s recognition of its historical evolution and its commitment to honoring pioneering figures who broke barriers in the consulting world. The platform represents more than just a technological upgrade; it embodies McKinsey’s strategic response to the rapidly evolving landscape of artificial intelligence and its potential to reshape professional services.
According to Kate Smaje, McKinsey’s global leader of technology and AI, the development of Lilli was driven by the need to create a secure, proprietary AI solution that could handle confidential client data—something that external platforms like ChatGPT, while permitted for internal use, could not safely accommodate. This distinction is crucial in the consulting industry, where client confidentiality and data security are paramount concerns that can make or break business relationships and regulatory compliance.
The platform was trained on McKinsey’s entire intellectual property repository, encompassing over 100,000 documents and interviews accumulated across the firm’s nearly century-long history. This comprehensive training dataset gives Lilli unprecedented access to the firm’s collective knowledge, methodologies, and best practices, making it not just an AI tool but a repository of institutional wisdom that can be accessed instantly by consultants worldwide.
Widespread Adoption and Usage Patterns
The adoption rate of Lilli within McKinsey has been remarkable by any measure. Over 75% of the firm’s 43,000 employees now use the platform monthly, with the average user turning to Lilli 17 times per week. These statistics reveal not just widespread acceptance but active integration of AI into daily workflows across the organization. The frequency of use suggests that Lilli has become an indispensable tool rather than an occasional convenience.
This level of adoption represents a significant shift in how consulting work is conducted. Traditional consulting has always been knowledge-intensive, requiring extensive research, analysis, and synthesis of information from multiple sources. The fact that Lilli answers over half a million prompts every month indicates the scale at which AI is now handling these fundamental consulting tasks, fundamentally altering the nature of the work itself.
The platform’s usage patterns also reveal important insights about the evolution of professional work. Consultants are not using Lilli sporadically or for simple tasks; the 17-times-per-week average suggests deep integration into complex, ongoing projects. This frequency indicates that AI has moved beyond being a supplementary tool to becoming a core component of the consulting process.
Transforming Traditional Junior-Level Tasks
Perhaps the most significant impact of Lilli is its ability to handle tasks that have traditionally been the domain of junior employees. The platform can create comprehensive PowerPoint presentations through simple prompts, modify the tone and style of content to align with McKinsey’s standards, draft client proposals, identify internal subject matter experts, and conduct industry research.
These capabilities directly address many of the routine but essential tasks that have historically served as training grounds for new consultants.
The “Tone of Voice” feature represents a particularly sophisticated advancement in AI capabilities. Maintaining consistency in communication style and adhering to firm standards has always been a critical skill that junior consultants needed to develop over time. By automating this process, Lilli not only ensures consistency but also eliminates the learning curve traditionally associated with mastering the firm’s communication standards.
The ability to draft proposals while maintaining firm standards is another game-changing capability. Proposal writing has long been considered both an art and a science in consulting, requiring deep understanding of client needs, firm capabilities, and competitive positioning. The fact that AI can now handle this complex task suggests a fundamental shift in what constitutes uniquely human value in professional services.
Research capabilities represent perhaps the most transformative aspect of Lilli’s functionality. Junior consultants have traditionally spent significant portions of their time gathering, organizing, and synthesizing information from various sources. According to McKinsey’s own case studies, Lilli saves workers 30% of the time they would have spent on these information-gathering and synthesis activities. This time savings translates directly into increased efficiency and the ability to focus on higher-value activities.
The Broader Industry Context
McKinsey is not alone in embracing AI for consulting tasks. The entire consulting industry is experiencing a technological transformation that is reshaping traditional business models and service delivery approaches. Bain & Company has developed Sage, an AI chatbot powered by OpenAI, while Boston Consulting Group employs Deckster, an AI tool specifically designed to enhance PowerPoint presentations.
This industry-wide adoption of AI tools reflects a broader recognition that the consulting business model, built on leveraging junior talent for routine tasks while senior partners focus on strategy and client relationships, may need fundamental restructuring. The traditional pyramid structure of consulting firms, with many junior analysts supporting fewer senior consultants, is being challenged by AI’s ability to handle many of the tasks that justified this hierarchical approach.
The competitive implications are significant. Firms that successfully integrate AI into their service delivery models may gain substantial advantages in terms of efficiency, consistency, and cost structure. Conversely, firms that lag in AI adoption may find themselves at a competitive disadvantage, unable to match the speed and cost-effectiveness of AI-enhanced competitors.
Implications for Entry-Level Employment
The impact of AI on entry-level employment in consulting raises important questions about career development and the future of professional services careers. Traditionally, junior positions in consulting firms served multiple purposes: they provided cost-effective labor for routine tasks, offered training opportunities for future senior consultants, and created a pipeline of talent familiar with firm methodologies and culture.
Kate Smaje’s statement that McKinsey doesn’t necessarily plan to hire fewer junior analysts, but rather will have them focus on “things that are more valuable to our clients,” suggests an evolution rather than elimination of entry-level roles. However, this evolution may fundamentally change the nature of these positions and the skills required for success.
The challenge lies in determining what constitutes “more valuable” work for junior employees when AI can handle many traditional tasks. This shift may require junior consultants to develop different skill sets, focusing more on creative problem-solving, client interaction, and strategic thinking from the beginning of their careers rather than gradually building these skills through routine task completion.
Broader Economic and Social Implications
The transformation at McKinsey reflects broader trends in the economy where AI is increasingly capable of handling white-collar, knowledge-based work. A report from SignalFire, a venture capital firm tracking over 650 million LinkedIn employees, found that new graduates accounted for just 7% of new hires at big tech companies in 2024, down 25% from 2023, as AI takes over entry-level tasks.
This trend extends beyond consulting to other industries. IBM CEO Arvind Krishna reported that the company replaced hundreds of human resources staff with AI, then redirected resources to hire more programmers and salespeople. Salesforce has used AI to reduce personnel costs by $50 million this year, demonstrating the significant financial impact of AI adoption on workforce planning.
These examples illustrate a broader economic shift where AI is not just augmenting human capabilities but actively replacing human roles in specific functions. The implications for career development, education, and economic inequality are profound and require careful consideration by policymakers, educators, and business leaders.
The Security and Confidentiality Advantage
One of Lilli’s key differentiators is its ability to handle confidential client information securely. While McKinsey employees can use external AI platforms like ChatGPT for general tasks, only Lilli can safely process sensitive client data. This capability is crucial in consulting, where confidentiality agreements and data security requirements are fundamental to client relationships.
The development of secure, proprietary AI platforms may become a competitive necessity for professional services firms. Clients increasingly expect their advisors to leverage the latest technology while maintaining the highest standards of data security and confidentiality. Firms that can demonstrate both AI capabilities and robust security measures may gain significant competitive advantages.
This security focus also highlights the importance of internal AI development versus reliance on external platforms. While external AI tools offer rapid deployment and continuous updates, they may not provide the security, customization, and control that professional services firms require for their most sensitive work.
Measuring Success and Impact
McKinsey’s case study data provides concrete evidence of Lilli’s impact on productivity and efficiency. The platform handles over half a million prompts monthly and saves workers 30% of the time previously spent on information gathering and synthesis. These metrics demonstrate measurable returns on AI investment and provide a framework for evaluating AI success in professional services.
The 30% time savings is particularly significant because it represents time that can be redirected to higher-value activities such as strategic analysis, client interaction, and creative problem-solving. This reallocation of human effort toward uniquely human capabilities may represent the optimal integration of AI in professional services.
However, measuring AI success requires more than efficiency metrics. Quality, client satisfaction, and long-term competitive advantage are equally important measures that may be more difficult to quantify but are crucial for sustainable AI integration.
Challenges and Considerations
Despite its success, the implementation of Artificial Intelligence in consulting faces several challenges. Quality control remains a critical concern, as AI-generated content must meet the high standards expected in professional consulting. While Lilli can maintain McKinsey’s tone and style, ensuring accuracy, relevance, and strategic insight requires ongoing human oversight.
The risk of over-reliance on AI is another consideration. Consulting has always been a relationship-based business where human judgment, creativity, and interpersonal skills are crucial for success. Firms must balance AI efficiency with the human elements that clients value and that drive long-term business relationships.
Training and change management represent additional challenges. Successfully integrating AI into consulting workflows requires significant investment in training, process redesign, and cultural adaptation. Organizations must help employees understand how to work effectively with AI while maintaining their professional development and career progression.
The Future of Consulting
The success of Lilli and similar AI platforms suggests that the consulting industry is entering a new era where AI augmentation becomes standard practice. This transformation may lead to new service delivery models, different pricing structures, and evolved client expectations.
Future consulting firms may be distinguished not by their ability to deploy large teams of junior analysts but by their capability to combine AI efficiency with senior-level strategic insight and client relationship management. This shift could lead to flatter organizational structures, different career paths, and new definitions of professional value.
The integration of AI may also enable consulting firms to serve smaller clients who previously couldn’t afford comprehensive consulting services. By reducing the cost of routine tasks, AI could democratize access to professional consulting services and expand market opportunities.
Preparing for an AI-Augmented Future
For current and aspiring consultants, the rise of AI platforms like Lilli necessitates a reevaluation of career development strategies. Skills that complement rather than compete with AI—such as creative problem-solving, emotional intelligence, strategic thinking, and client relationship management—become increasingly valuable.
Educational institutions and professional development programs must also adapt to prepare future consultants for an AI-augmented workplace. This preparation should include both technical literacy to work effectively with AI tools and enhanced focus on uniquely human capabilities that remain essential for consulting success.
Conclusion
McKinsey’s deployment of Lilli represents more than a technological upgrade; it signals a fundamental transformation in how professional services are delivered and how careers in consulting may evolve. With over 75% of employees using the platform monthly and significant measurable impacts on productivity, Lilli demonstrates the practical viability of AI integration in knowledge-intensive professional services.
The success of Lilli and similar platforms across the consulting industry suggests that AI augmentation is not a future possibility but a present reality that is reshaping the competitive landscape. Firms that successfully navigate this transformation—balancing AI efficiency with human insight, maintaining quality while improving productivity, and evolving career development while preserving institutional knowledge—will likely emerge as leaders in the next generation of professional services.
As the consulting industry continues to evolve, the example set by McKinsey’s Lilli provides valuable insights into both the opportunities and challenges of AI integration. The key to success lies not in replacing human capabilities but in thoughtfully combining AI efficiency with uniquely human value creation, ensuring that technology serves to enhance rather than diminish the strategic impact of professional consulting services.
The transformation is already underway, and its implications extend far beyond the consulting industry to the broader future of knowledge work in an AI-augmented economy. How organizations and individuals adapt to this change will determine their success in an increasingly AI-integrated professional landscape.
