Consulting firms are undergoing structural change, rather than being made obsolete, thanks to artificial intelligence. The HBR article by Duncan, Anderson, and Saviano argues that AI is transforming consulting in ways that require new roles, flatter teams, and sharper judgment.
1. From Pyramid to Obelisk
Traditional consulting is often structured like a pyramid: many junior staff doing research, analysis, modeling; fewer middle managers; still fewer senior leaders. AI is shifting that shape toward what the authors call an obelisk: a model with fewer layers and more cross-cutting skills. Roles are changing: less “busywork” for juniors, more work focused on interpreting AI outputs, defining problems, and ensuring quality.
2. New Core Roles
To succeed, consulting firms are developing or increasing three kinds of roles:
- AI facilitators / tool specialists — people who are fluent with AI tools, pipelines, and how to integrate AI into workflows.
- Engagement architects — those who lead client projects, define what problems will or won’t be solved by AI, interpret results, translate outputs into strategy.
- Client leaders — senior, relationship-building roles, helping clients navigate change, trust, ethics, and what AI can or can’t do.
3. Automation of Junior Tasks
Many tasks that used to require junior consultants — routine research, modeling, summarization — are increasingly done by AI. This means smaller juniors’ teams, more efficiency, but also a need for juniors to learn new skillsets (e.g. oversight, validating AI output, interpreting what gets produced).
4. Need for Judgment, Oversight & Ethics
AI is powerful but imperfect. When tasks are within the capability frontier of current AI tools, results can be faster, cheaper, even higher quality. But when tasks are outside that frontier, over-reliance on AI can lead to errors. Consulting firms (and their clients) need people who can detect, correct, contextualize AI output—ethical implications, governance, bias, etc.
5. Implications for Staffing, Workflow, Client Engagement
- Staffing shifts: fewer people needed for routine analytic work; greater demand for people who can design workflows, interpret results, do quality assurance, manage AI tooling.
- Workflow redesign: integrating AI into consulting engagements means redesigning how tasks are divided, who owns what, how feedback loops are built in.
- Client relationships & expectations: firms must help clients understand what AI can realistically deliver, set expectations, manage risk, build trust.
What This Means If You’re Looking for AI Help
If your company is considering hiring consultants/partners for AI-tool adoption, integration, or staffing changes, here are practical takeaways to keep in mind:
- Ask about roles, not just tools: Do they have AI facilitators, engagement architects, or people who understand how to translate AI outputs into strategy (not just technical deployment)?
- Validate capability frontiers: Be clear on what types of problems the AI can solve well vs. where human judgment/expertise remains essential.
- Emphasize oversight & quality control: Ensure there are processes to check AI output, detect errors, guard against bias or misinterpretation.
- Enable change management: Tools and models won’t succeed by themselves. Training staff, redesigning workflows, ensuring buy-in, and managing expectations are critical.
- Partner with ethics & risk experts: Given the risks around privacy, bias, transparency, firms that embed ethical and governance considerations are going to be more sustainable and trustworthy.
The HBR article shows that AI isn’t replacing consulting firms — it’s forcing them to evolve. The firms that thrive will be those that rebuild their structures, redefine roles, integrate AI into their workflows intelligently, and maintain strong human judgment & accountability.
You can read the full article here:
AI Is Changing the Structure of Consulting Firms
Harvard Business Review (Sept 10, 2025) — link
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