90% of management consultants now use Gen AI every day
Nine-in-ten consultants are using Gen AI across research, email, drafting, and even full report creation. The payoff is clear: over one-in-ten say they save more than five hours a day, and many are redirecting that time into analysis, client strategy, and delivery. Source: LexisNexis.
For managers, this shift isn't theory. It changes how work gets done, how you price, and how you staff. The firms that pair AI with strong training and guardrails are already pulling ahead.
Why consultants are outpacing the market
Adoption isn't the ceiling-it's the starting line. Across industries, 83% of leaders say Gen AI is meeting or exceeding expectations. In consulting, that climbs to 91%. Source: LexisNexis.
Impact is showing up in the numbers. 40% of consultants report a significant productivity lift. 85% expect AI to improve overall performance going forward.
Where AI is paying off today
Usage isn't fringe-it's in the core workflow. 77% use AI for research. 71% for summarization. Similar shares draft and analyze documents, then refine with human review. Source: LexisNexis.
What's next? Consultants expect AI to strip out time sinks like data entry (21.4%), creative content drafting (18.8%), and report generation (12.5%). That frees up hours for insight and client-facing work.
The training edge most firms don't have
This acceleration isn't happening by accident. Over 40% of consultants have advanced Gen AI training-nearly triple the wider economy. 70% of firms train at least quarterly. Only 8% offer no training, compared to a 28% average elsewhere. Source: LexisNexis.
If you lead a team, make structured training non-negotiable. Repeat it. Make it practical. If you need a shortcut, explore curated options by job function at Complete AI Training.
Time saved-and where it goes
AI is already buying back real hours. 14% of consultants save over five hours daily. 56% save three to four hours. 28% save at least one hour. Source: LexisNexis.
The key is where you reinvest that time: deeper client discovery, sharper storylines, better stakeholder alignment, and faster iteration on recommendations.
Pricing needs to catch up
The billable hour was built for manual throughput. AI changes the calculus. If the same outcome takes fewer hours, time-based pricing punishes your own efficiency.
Move toward pricing tied to outcomes and defined deliverables. Consider subscriptions for ongoing analysis, or phase-based fees with clear milestones. Track value created-speed to insight, reduction in cycle time, impact on KPIs-and make that your case for fees.
Quality, privacy, and compliance: set the guardrails
AI output can be confident and wrong. BBC research found significant issues in 51% of tested news summaries. Don't publish raw output. Always layer human review, citation checks, and a source-of-truth standard.
- Adopt an AI policy: what data is allowed, approved tools, and red lines for client and employee data.
- Run a human-in-the-loop review for anything client-facing. Require sources and claim checks.
- Stand up an AI registry: who's using what, where data flows, and the evaluation method for each use case.
- Use a recognized framework for risk and controls, such as the NIST AI Risk Management Framework.
A simple 30-60-90 plan for managers
- 30 days: Pick three high-ROI use cases (research summaries, first-draft slides, data extraction). Set quality bars. Pilot with a small team.
- 60 days: Formalize your AI policy and data boundaries. Create reusable prompts and templates. Launch role-based training. Start a lightweight review workflow.
- 90 days: Shift pricing on select offers to value or deliverable-based models. Publish internal case studies with time saved and client outcomes. Expand the registry and scorecards for accuracy and impact.
What "good" looks like
Large firms are signaling their direction. One global strategy firm publicly shared that it now counts "AI agents" alongside employees, and even received a plaque from a leading model provider for prompt volume. The headline isn't the plaque-it's that firms are systematizing AI, not dabbling.
That's the bar. Make AI part of the operating system: skills, workflows, pricing, and governance. The firms-and teams-who do this now will feel compounding gains by year-end.
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