Will AI kill off consulting?
Drawing parallels between Software Development and Management Consulting for GenAI applications
Got around to writing after a long time, this time a long form piece. Also nudged into it after đ on reading a lot of "AI is killing consulting and here's a startup whose model will replace McKinsey..." articles and tweets đ
Over the past year, I've observed AI applications across several companies and thought deeply about this while designing a master's level course on the topic*. This article consolidates those observations along with my experience spanning both the consulting and software development worlds. I explore how consultants should approach AI, the "70% problem" and why I don't think it goes to 100%, practical patterns I've seen work effectively, implications for junior vs. senior consultants, and what the future might hold for the profession as AI continues to evolve.
My core argument: GenAI won't replace consultants, but it will dramatically reshape how consultants work and which skills become most valuable. I think reports of consulting's death are highly exaggerated. đ
Feedback welcome, especially from those in professional services experimenting with AI integration!
*designing a course was so much fun, and such a great forcing function for myself to read and learn and think more!
Ok, here goes! (copy of whatâs posted on LinkedIn)
Introduction: The Headlines and AI Inflection Point
Generative AI (GenAI) is reshaping industries at breakneck speed, and management consulting is no exception. Since the debut of ChatGPT in 2022, AI tools have evolved from novelty to necessity, promising to automate research, draft reports, and even generate strategic recommendations. Headlines scream about AI replacing junior analysts or commoditizing strategy work, but these narratives often miss the mark. One might even say that reports of "The death of consulting" are highly exaggerated :)
For decades, consulting has thrived on human intuition, deep industry knowledge, and the ability to navigate ambiguity. There is no doubt that GenAI is shaking up this equilibrium. So what does this mean for the MBB consultant in 2025?
Let's dive in.
1. How Consultants Should Use AI: âSprintersâ vs. âStrategistsâ
Two distinct patterns will define AI adoption in consulting:
The Sprinters: Rapid Delivery at Scale
Sprinters leverage tools like ChatGPT, Claude, or proprietary AI platforms to:
Automate repetitive tasks: Drafting meeting summaries, populating slide decks, or benchmarking competitors.
Accelerate research: Scraping market data, synthesizing industry trends, or generating SWOT analyses.
Simulate scenarios: Modeling financial outcomes under varying conditions (e.g., pricing changes, M&A impacts).
Example: A junior analyst at a mid-tier firm might use AI to condense a 300-page regulatory document into a 5-page brief in 20 minutes. The output could be structurally sound but lack nuance, requiring senior oversight to align with client priorities.
The Strategists: Depth Over Speed
Strategists will treat AI as a thought partner for complex problems:
Challenge assumptions: Stress-testing hypotheses by asking, âWhat if our core premise is wrong?â
Identify blind spots: Surfacing overlooked risks in supply chain resilience or geopolitical shifts.
Enhance creativity: Brainstorming unconventional solutions (e.g., âHow might a retail client adopt circular economy principles?â).
Example: A partner at a boutique firm could use AI to generate 15 variants of a market-entry strategy, then refine the top three with team input. The final proposal can then blend AIâs breadth with human judgment on cultural fit.
The divide: Sprinters prioritize efficiency for well-defined tasks; Strategists focus on augmenting creativity and rigor. A warning - not knowing which mode one is in will create frictionâfor instance, juniors rushing analyses might deliver superficial insights, while seniors dismissing AI might miss opportunities to scale their thinking.
2. The 70% Problem: AIâs Promise and Peril
Early AI experiments in consulting reveal a consistent pattern: AI propels you 70% of the way there â then the real work begins.
Case Study: The Illusion of Completeness
A team is using AI to draft a post-merger integration plan. The AI produces timelines, synergy targets, and cultural alignment steps â all structurally sound. But it misses critical nuances:
A key stakeholderâs resistance to layoffs (revealed only in offline conversations).
Regulatory hurdles unique to the targetâs Southeast Asian operations.
Overly optimistic savings estimates from shared services.
The team could spend more time fixing these gaps than what was saved by AI. Seasoned consultants recognize the truth: "The AI has given us a generic starting point. Our job is to transform it into the client's playbook."
Why the Last 30% Matters
The final 30% is where consultingâs value lives:
Contextualization: Tailoring frameworks to a clientâs culture, politics, and constraints.
Judgment calls: Balancing quantitative models with qualitative risks (e.g., leadership dynamics).
Ethical guardrails: Ensuring compliance and avoiding AI hallucinations (e.g., invented data).
This phase remains firmly human â at least for now.
Is the 30% is going to 5% and 0%?
For some tasks, yes, and it already has. But think of consulting holistically, and there is a lot still left to do. Not the least of which is that humans crave human connection, and most complex business problems don't have a single "correct", "perfect" solution. AI will continue to do more work that is verifiable, creating space for humans to do even more deep thinking and nuanced work, always extending what 100% means. Those who miss this, miss the opportunity.
3. What Could Work: Practical Patterns for AI-Augmented Consulting
Based on conversations with MBB practitioners, three patterns emerge:
Pattern 1: âAI First Draft, Human Final Cutâ
Let AI generate initial drafts of reports, models, or slides.
Senior consultants review, contextualize, and pressure-test outputs.
Why it works: Frees juniors from grunt work; focuses seniors on high-value edits.
Pattern 2: âBidirectional Promptingâ
Treat AI as a dialogue partner, not a search engine. Example:
- Consultant: âWhat are risks of entering the Brazilian fintech market?â
- AI: Lists regulatory, currency, and competition risks.
- Consultant: âNow assume the clientâs CMO opposes this move. Reassess.â
Why it works: Mimics Socratic dialogue, uncovering deeper insights.
Pattern 3: âTrust but Verifyâ
Use AI for speed, but validate all critical outputs:
- Cross-check data sources.
- Flag conflicts of interest (e.g., AI recommending a vendor itâs trained on).
- Stress-test conclusions against industry veterans.
4. Implications for Consultants: The Knowledge Paradox
Paradox: AI empowers experienced consultants more than juniors.
Seniors will thrive by using AI to:
Rapidly prototype strategies they already understand.
Automate repetitive tasks (e.g., benchmarking).
Focus on client relationships and strategic oversight.
Juniors could struggle if they:
Accept AI outputs uncritically (e.g., overlooking biased data).
Miss subtle cues in stakeholder interviews.
Fail to ask âwhyâ behind AI-generated recommendations.
This creates a bifurcated talent landscape. Firms that train juniors to interrogate AI â not just use it â could build future-ready teams.
5. The Rise of Agentic Consulting (BUZZWORD ALERT!)
In 2025, AI will likely evolve from tool to collaborator. Early signs could include:
Autonomous research agents: Scouring earnings calls, patents, and news to flag trends.
Simulation engines: Modeling multi-year strategy outcomes with dynamic variables.
Real-time coaching: AI whispering advice during client negotiations (e.g., âPush back on budget cutsâhereâs whyâ).
The catch: Agents might require guardrails. For example, AI-generated strategies could lack empathy for employee impacts. The winning formula? Human-led, AI-assisted â not the reverse. At least not yet.
And let's be honest â two AIs negotiating with each other will likely communicate more efficiently than when humans are involved. (But where's the fun in that?)
6. The Return of Consultative Craft
As AI handles the âwhat,â consultants must master the how and why:
Storytelling: Turning data into compelling narratives.
Empathy: Reading unspoken client concerns.
Ethics: Navigating AIâs biases (e.g., gender in hiring algorithms).
Example: A team might use AI to optimize a retailerâs inventory but overrule its cost-cutting advice to preserve supplier relationships â a decision rooted in decades of trust-building.
The irony: AI commoditizes the mechanical, making the human elements even more valuable.
7. Future Outlook: Demand for the AI-Savvy Consultant
The Enduring Need for Expertise
GenAI will lower barriers to entry, flooding the market with DIY âstrategistsâ and "ConsultantGPT"s. But complex, high-stakes problems (e.g., turnaround strategies, geopolitical risk) will still demand seasoned experts who can:
Synthesize AI outputs with tacit knowledge.
Navigate boardroom politics.
Take accountability for recommendations.
Ethical Frontiers
Transparency: Disclosing AI use to clients (e.g., âThis model was AI-assistedâ).
Bias mitigation: Auditing tools for cultural or industry blind spots.
IP risks: Ensuring client data isnât used to train public AI models.
The Talent Shift
Juniors: Might evolve from data gatherers to âAI editorsâ and critical thinkers.
Seniors: Could spend less time reviewing slides, more on mentoring and client diplomacy.
Firms: Might differentiate by building proprietary AI tools tailored to niche verticals (e.g., healthcare compliance).
Conclusion: AI as the Ultimate Apprentice
CLICHE ALERT!
GenAI wonât replace consultants â but consultants who use GenAI will replace those who donât. The tools are here to stay, yet their greatest value lies not in replacing human judgment but in amplifying it.
Ultimately, clients don't hire algorithms; they hire insight, judgment, and accountability. The consultants who thrive will be those who leverage AI to amplify these quintessentially human qualities. By embracing AI as an accelerant rather than a replacement, the next generation of consultants will deliver something even more valuable than before: wisdom at scale.
And, now for the customary cat-pic : This cat is NOT out of the bag :P
