Consulting Firms 90-day fee/work pause

AI Research Analyst for Consulting Firms

Takes over routine work of: Junior Research Analyst

Hand Your Research Analyst Work to an AI Worker

01 Setup + retainer Fixed-price setup plus a monthly retainer
02 90 days Fee/work pause on agreed SOW metrics
03 20 min Assessment estimates the figures for your roles
The problem

Why Consulting Firms Are Switching to AI

These aren't edge cases. They're the daily reality that's bleeding your margins.

01

Inefficient Research Consumes 15-25% of Engagement Hours

Junior research analysts spend 15-25% of each engagement hunting for benchmarks, competitor data, and industry statistics across fragmented Confluence, SharePoint, and email repositories.

02

Proposal Research Drains 40-80 Hours Per Major RFP

Responding to major RFPs requires extensive market research, competitor analysis, and case study compilation.

03

Fragmented Knowledge Management Creates Duplicate Work

Consulting deliverables are scattered across Confluence, SharePoint, and email threads. Junior analysts spend 2-4 hours weekly searching for previous project materials, templates, and client intelligence.

04

Unbilled Hours from Poor Time Capture

When junior analysts focus on research rather than time entry, firms lose billable hours.

Task analysis

What AI Handles vs. What Stays Human

AI takes the repetitive load. Your team focuses on judgment calls and relationships.

Market sizing and TAM analysis

AI tools crawl public databases, industry reports, and financial filings to generate market size estimates in minutes rather than days

~8-12 hours per project (illustrative)

Competitor benchmarking research

Automated scraping of competitor websites, press releases, and financial reports compiles comprehensive competitive intelligence matrices

~6-10 hours per engagement (illustrative)

Industry trend analysis

AI synthesizes news articles, analyst reports, and academic papers to produce trend summaries with source attribution

~5-8 hours per deliverable (illustrative)

Case study extraction from past projects

Semantic search across SharePoint and Confluence surfaces relevant case studies and metrics without manual folder hunting

~4-6 hours per rfp response (illustrative)

Data visualization and chart generation

AI converts raw data tables into presentation-ready charts, graphs, and infographics automatically

~3-5 hours per report (illustrative)

Bibliography and source compilation

Automatic generation of cited sources, footnotes, and research bibliographies in firm-standard formats

~2-3 hours per deliverable (illustrative)

Client interview note synthesis

AI transcribes and summarizes stakeholder interviews, extracting key insights and action items automatically

~2-4 hours per interview (illustrative)
Workflow comparison

Before & After AI

The same process. Night-and-day difference.

Before — manual
01
Analyst receives research assignment from engagement manager
15 minutes·Email chains, unclear requirements, back-and-forth clarification
02
Search Confluence and SharePoint for past deliverables
2-4 hours·Inconsistent naming conventions, version confusion, access permissions issues
03
Browse external sources for industry data
4-8 hours·Paywall barriers, outdated reports, manual data compilation
04
Compile findings into draft format
3-5 hours·Formatting inconsistencies, missing citations, manual chart creation
05
Manager reviews and requests revisions
2-4 hours·Total: 11-21 hours per research deliverable
After — handed to AI
01
Analyst inputs research request into AI assistant
5 minutes·Clear prompts, structured outputs from the start
02
AI searches all internal knowledge sources simultaneously
5-10 minutes·Semantic matching finds relevant content instantly, including conceptual matches
03
AI compiles external benchmarks and generates draft analysis
30-60 minutes·Automated data collection, chart generation, source citation
04
Analyst reviews AI output and adds strategic context
1-2 hours·Human expertise focused on value-adding refinement, not grunt work
05
Manager conducts final quality check
30-60 minutes·Research deliverable assembled for analyst review
Implementation

How We Deploy

From signed contract to live AI workforce. No long IT projects. No dragging it out.

1
Phase 1

Assessment and Tool Selection

Evaluate current research workflows, map data sources (Confluence, SharePoint, external databases), and select AI platform integration. Configure secure access permissions and NDA compliance settings.

2
Phase 2

Data Integration and Knowledge Base Setup

Connect AI tools to existing document repositories. Train semantic search on firm-specific terminology, past project templates, and proprietary methodologies. Establish data governance protocols.

3
Phase 3

Pilot Program with Select Projects

Deploy AI research assistance on 2-3 pilot client engagements. Test market sizing, competitor analysis, and benchmarking outputs. Gather consultant feedback and refine prompts.

Phase 4

Full Rollout and Optimization

Train all consulting staff on AI research tools. Document standard operating procedures. Establish KPIs for research efficiency and quality. Transition pilot learnings to firm-wide practice.

FAQ

Common Questions

Real objections from Consulting Firms owners considering AI AI Research Analyst.

01Will AI-generated research meet our client's quality standards?

AI handles the data gathering and initial synthesis while senior consultants provide strategic context and quality validation. This hybrid approach typically produces higher quality work faster because analysts focus their expertise on insight rather than information gathering.

02How does this work with our NDA and confidentiality requirements?

Enterprise AI platforms used by consulting firms include SOC 2 compliance, data encryption, and client data isolation. Research outputs can be configured to exclude proprietary firm data when working on sensitive engagements.

03What happens to our junior analysts who currently do this research?

Rather than eliminating positions, firms typically redeploy analysts to higher-value client-facing work. This improves both consultant development and utilization rates—turning a cost center into a profit center.

04How is an AI research analyst priced?

Leverwork prices each deployment as a fixed-price setup plus a monthly retainer, scoped on a 20-minute call. The 90-day fee/work pause applies to the metrics agreed in your SOW. Your 20-minute assessment estimates the figures for your roles.

05Can AI handle the specialized industry knowledge our firm requires?

AI models can be trained on your firm's proprietary methodologies, past project data, and industry-specific terminology. The more you use it, the more it learns your firm's unique knowledge base and terminology.

Still have questions? We'll answer them directly.

Talk to an expert

Same industryOther roles we support in Consulting Firms

Other industriesThis Role in Other Industries

Put AI to work. Keep your people leading.

A full-time AP / bookkeeping seat costs about $68K–$74K a year in wages and benefits (our estimate from BLS 2025/2026 data). Your assessment estimates the numbers for your business. 90-day fee/work pause on agreed SOW metrics

A 20-minute call. We'll show you which seats AI can take over — and where humans stay essential.

Book the 20 minutes