Artificial intelligence has not arrived in consulting merely to support processes. It is reshaping from the ground up what it means to be a consultant. A sector that was once human-intensive, structured around analytical hierarchies and established methodologies, is now moving toward a hybrid model where data, automation, and algorithms are no longer auxiliary tools but central actors. In this shift, AI does not replace strategic thinking, but it redefines who creates value, how it is delivered, and what is expected from each profile.
A deeper disruption than it seems
Top consulting firms were among the first to adopt generative AI, both internally and in client services. McKinsey launched its platform “Lilli” in 2023 to respond to strategic queries, navigate databases, and generate recommendations in seconds. BCG has partnered with Anthropic and OpenAI to integrate AI in every phase of projects, from diagnostics to final presentation. Accenture has invested over 3 billion dollars to expand its AI division, training thousands of consultants in generative AI.
The integration is not cosmetic. Tools such as ChatGPT, Claude, or proprietary models now automate key tasks including document review, benchmark creation, conceptual frameworks, interview summaries, and preliminary dashboards. In typical projects, this reduces human hours spent on repetitive tasks and increases focus on solution design, client validation, and context adaptation.
Changes in the talent pyramid
The direct consequence is a transformation of the classic consulting pyramid. Junior profiles, traditionally responsible for research, presentations, and data support, see their role shrink. Firms now value those who can operate AI tools, interpret results, and translate them into actionable decisions. The ideal profile is no longer just skilled in Excel and PowerPoint, but fluent in prompts, models, and APIs.
Human talent remains essential, but its function changes. Consultants are no longer primarily data generators. They ask the right questions, validate findings, and connect insights to business realities. New roles emerge: data engineers, algorithm ethics specialists, product designers, and applied AI consultants. Consulting is no longer divided into strategy and operations, but into problems and systems.
Client expectations
The change originates with clients. Companies now demand not only strategic answers, but technological execution. They want to know how to use AI to cut costs, improve processes, accelerate sales, and make better decisions. Theory is no longer enough; clients want functional pilots, scalable tools, and models they can manage independently.
This forces consulting firms to break from the classic model. Proposals increasingly include product development, software licenses, AI integration in client systems, and co-design of internal solutions. Firms unable to operate at this technical level lose projects or are relegated to facilitation roles.
Risks, lessons, and internal tensions
The AI transition is not without friction. Many firms face questions: how to maintain business models if clients pay less for automated tasks? How to justify high fees when part of the work is done by a model in seconds? How to train young talent outside traditional learning cycles?
Not all AI outputs are valid. There are risks of errors, hallucinations, biases, and overreliance on outputs generated without context. Firms that survive will build a critical culture around AI, combining speed with rigor, automation with judgment, and efficiency with trust.
The new value of the consultant
In this new paradigm, a consultant’s value lies not in knowing more, but in thinking better, faster, and with more tools. Mastery of frameworks becomes mastery of systems. Storytelling is replaced by prototyping. Impactful slides give way to functional interfaces. Expert intuition combines with the ability to design flows, prompts, and A/B tests.
Firms that understand this are redefining their teams, deliverables, and success metrics. Many are developing their own products, automating delivery components, or integrating AI across every vertical. In this environment, consulting without technological mastery is simply one opinion among many.
Sources
- McKinsey & Company: Meet Lilli: Our generative AI tool
- Fast Company: We spent nearly a year building a GenAI tool. These are the 5 hard lessons we learned
- Boston Consulting Group: GenAI Increases Productivity & Expands Capabilities
- Harvard Business Review: When AI changes the consultant-client dynamic
- World Economic Forum: Future of Jobs Report 2023
