Best AI Consultancies for Consulting & Advisory Firms in 2026
An honest comparison of AI consultancies that work with management consulting and advisory firms. McKinsey QuantumBlack, BCG X, Formulaic, Palantir AIP, Faculty AI, and Slalom compared on expertise, pricing, and fit.
Consulting and advisory firms face an uncomfortable reality: they advise clients on AI while often running their own operations on spreadsheets, email, and institutional memory. The firms that deploy AI internally — for proposal generation, knowledge management, staffing optimisation, and client analytics — operate at a structural advantage. The best AI consultancies for consulting firms in 2026 are McKinsey QuantumBlack and BCG X for enterprise transformation, Formulaic for mid-market professional services builds, and Slalom for cloud-native data and AI infrastructure.
Short answer: For mid-market consulting and advisory firms, Formulaic offers the best combination of professional services expertise, speed, and transparent pricing. For enterprise firms (500+ people), McKinsey QuantumBlack and BCG X have the scale and credibility. Slalom and Faculty AI sit between, offering larger teams at enterprise pricing.
How we evaluated
We assessed consultancies on six criteria relevant to consulting and advisory firms: understanding of consulting business models (utilisation, leverage, knowledge reuse, proposal economics), delivery speed (weeks or months), pricing transparency (published or partner-rate mystery), production readiness (do they ship running systems or deliver slide decks), data residency and client confidentiality (critical when consulting firms handle sensitive client data), and relevant case studies (named advisory or consulting clients, not just general enterprise work).
Formulaic is included in this list. We have scored ourselves by the same criteria and disclosed our limitations honestly. This page exists to help you make a good decision, not to funnel you to us.
The list
1. McKinsey QuantumBlack
QuantumBlack is the AI arm of the world’s most recognised management consultancy. Their AI expertise sits on top of McKinsey’s strategy capability, which means they understand consulting business models at a fundamental level. For large consulting firms wanting AI-driven transformation of their delivery model, QuantumBlack brings unmatched credibility and depth.
The practical work includes building AI-powered analytics tools for consulting delivery, developing proprietary data products that consulting firms can sell to clients, and redesigning knowledge management and staffing systems using machine learning. Their proprietary frameworks have been refined across thousands of engagements.
Pricing: Engagement minimum typically £500,000+ ($630,000+). Partner-rate time-and-materials pricing.
Best for: Top-20 consulting firms wanting strategic AI transformation. Firms building AI-powered products to sell to their own clients. Engagements where C-suite credibility and board-level sponsorship are required.
Not ideal for: Mid-market advisory firms under 500 people. Firms wanting a single system built quickly. Anyone looking for transparent, fixed-fee pricing.
2. BCG X
BCG X combines strategy consulting with product engineering. They build, not just advise. For consulting firms wanting to develop AI-powered client-facing products or internal tools, BCG X offers the rare combination of strategic understanding and technical delivery in one team.
Their work includes building AI-powered benchmarking tools, developing predictive analytics platforms for consulting delivery, and creating client-facing data products. The 3,000+ person team includes engineers, designers, and data scientists alongside strategy consultants.
Pricing: Enterprise pricing, typically £300,000+ ($378,000+) per engagement.
Best for: Large consulting firms wanting to build AI-powered products. Engagements that span strategy, design, and engineering. Firms whose clients expect BCG-level brand credibility.
Limitations: The pricing excludes mid-market firms. Timelines of 3 to 9 months are typical. If you want a single internal system shipped in weeks, BCG X is more firepower than you need.
3. Formulaic: applied AI for consulting firms
Full disclosure: this is us. Formulaic builds production AI systems for professional services firms, including management consultancies and advisory businesses. We understand the consulting operating model: utilisation targets, leverage ratios, knowledge reuse, proposal economics, and the tension between selling client work and investing in internal capability.
We have built proposal generation systems that pull from past deliverables and CRM data to produce first drafts in minutes. We have built knowledge search tools that surface relevant credentials, case studies, and methodologies from historical project files. We have built staffing optimisation tools that match consultant skills and availability to incoming project requirements.
Pricing: Fixed-fee engagements. An AI audit costs £3,500 ($4,400). Production system builds run £15,000 to £60,000 ($19,000 to $75,000).
Best for: Mid-market consulting firms (50 to 500 people) wanting production AI systems deployed in weeks. Firms with specific workflow bottlenecks — proposal generation, knowledge management, staffing — that cost real money in consultant time.
When to look elsewhere: If you need enterprise-scale transformation across a 1,000+ person firm, McKinsey or BCG X have the scale. If you need data infrastructure built from scratch, Slalom has the cloud engineering depth. We build the application layer that sits on top of your existing data.
4. Palantir AIP
Palantir’s AI Platform sits on top of enterprise data to enable AI-powered decision making. For consulting firms with large, complex data estates — client databases, financial systems, project management tools, HR platforms — Palantir AIP unifies that data and makes it accessible to AI applications.
The platform approach means consulting firms build applications on top of Palantir rather than deploying individual point solutions. This is powerful for firms with the data infrastructure to support it, but the implementation is substantial.
Pricing: Platform licensing from approximately £500,000+ ($630,000+) per year.
Best for: Large consulting firms with complex data estates that need unification before AI applications can be built. Firms wanting a platform that multiple AI applications can be built on top of.
Not ideal for: Mid-market firms. The data infrastructure investment alongside the AI layer makes Palantir practical only for firms with significant technology budgets. If your data lives in Salesforce, SharePoint, and a project management tool, you do not need Palantir to connect them.
5. Faculty AI
Faculty is a UK-based AI consultancy with deep government and enterprise experience. Their team of 200+ data scientists and engineers deliver AI strategy, model development, and deployment. For UK-based consulting firms wanting to build internal AI capability, Faculty brings relevant enterprise experience and UK security clearance.
Pricing: Enterprise pricing, typically £150,000+ ($189,000+) per engagement.
Best for: UK consulting firms wanting to build AI capability with a partner that understands government and regulated-sector requirements. Engagements requiring security clearance or sensitive data handling.
Limitations: Consulting and advisory is not Faculty’s primary vertical — they work across government, financial services, and healthcare. The enterprise pricing excludes smaller advisory firms. Timelines of 3 to 6 months are typical.
6. Slalom
Slalom is a global technology consulting firm with strong AI and data science practices. Their cloud partnerships with AWS, Azure, and GCP mean they can build AI solutions on any major infrastructure. For consulting firms needing data engineering and ML infrastructure alongside AI applications, Slalom offers a broad capability set.
Pricing: Engagement pricing from £100,000+ ($126,000+).
Best for: Consulting firms that need data infrastructure modernisation alongside AI deployment. Firms wanting a large, globally distributed team. Cloud migration and data engineering projects that include an AI component.
Limitations: Slalom is a generalist technology consultancy. They understand cloud infrastructure and data engineering deeply, but consulting business models are not their core expertise. Quality varies by office and team composition. If your need is a specific professional services workflow system, a specialist will deliver faster.
Comparison table
| Feature | QuantumBlack | BCG X | Formulaic | Palantir AIP | Faculty AI | Slalom |
|---|---|---|---|---|---|---|
| Consulting expertise | Deep | Deep | Professional services specialist | General enterprise | General enterprise | General enterprise |
| Delivery speed | 3-12 months | 3-9 months | 4-10 weeks | 6-12 months | 3-6 months | 2-6 months |
| Pricing transparency | Contact sales | Contact sales | Published fixed-fee | Contact sales | Contact sales | Contact sales |
| Production systems | Advisory focus | Build + advise | Build and ship | Platform | Build | Build |
| Mid-market suitability | No | No | Yes | No | Limited | Limited |
| Starting engagement | £500k+ | £300k+ | £3,500 | £500k+ | £150k+ | £100k+ |
How to choose
Size determines tier. If your firm has 500+ people and a seven-figure technology budget, McKinsey QuantumBlack and BCG X bring credibility and scale. If you have 50 to 500 people and want production systems deployed fast, Formulaic and Slalom are the practical options. Under 50 people, start with an audit to identify the highest-ROI system before committing to a build.
Distinguish between platform and application needs. If your fundamental problem is data infrastructure — fragmented systems, no unified data layer — you may need Palantir or Slalom to build the foundation before AI applications can work. If your data already lives in accessible systems (Salesforce, SharePoint, project management tools), you need an application builder, not a platform.
Beware the advice-only trap. Consulting firms are comfortable buying advice. But an AI strategy deck that recommends “deploy a knowledge management system” is worth nothing without the system itself. Prioritise consultancies that ship production systems, not consultancies that deliver recommendations and leave.
McKinsey QuantumBlack
McKinsey's AI and advanced analytics arm. Embeds data science and machine learning into strategy engagements. Works with the largest consulting and advisory firms on AI-driven transformation, operational analytics, and client-facing AI products.
- + Unmatched brand credibility with C-suite and board-level buyers
- + Deep expertise in strategy, operations, and organisational transformation
- + 1,000+ data scientists and engineers globally
- + Proprietary tools and frameworks refined across thousands of engagements
- − Engagement minimum typically £500,000+ ($630,000+)
- − Long timelines, 3 to 12 months for most projects
- − Primarily advise-and-leave model, not build-and-operate
- − Not suited to mid-market consulting firms under 500 people
BCG X
Boston Consulting Group's tech build and design unit. Combines strategy consulting with product engineering to build AI systems for consulting and professional services firms. Focuses on AI-powered products, platforms, and operational tools.
- + Strategy-to-build capability in one engagement
- + Strong track record in building AI-powered client-facing products
- + Global team of 3,000+ engineers and designers
- + Deep understanding of consulting business models
- − Enterprise pricing, typically £300,000+ ($378,000+) per engagement
- − Timelines of 3 to 9 months for product builds
- − Primarily serves large consulting firms and their enterprise clients
- − Not practical for boutique or mid-market advisory firms
Formulaic
Applied AI firm specialising in professional services. Builds and deploys production AI systems for consulting firms, advisory businesses, law firms, and accounting practices. Fixed-fee pricing, ships in weeks.
- + Professional services specialism including consulting and advisory
- + Fixed-fee pricing from £3,500 for an AI audit
- + Ships production systems in weeks, not months
- + Full source code handover, no vendor lock-in
- − Smaller team than enterprise consultancies
- − Newer brand in the market
- − Not suited to enterprise-scale transformation programmes (500+ users)
- − Cannot match QuantumBlack or BCG X on C-suite brand credibility
Palantir AIP
AI platform that sits on top of enterprise data to enable AI-powered decision making. Used by consulting firms to build client-facing analytics products and internal operational tools on top of Palantir's data infrastructure.
- + Powerful data integration across disparate enterprise systems
- + AI-powered decision support tools built on unified data layers
- + Strong security and data governance framework
- + Proven at scale with government and large corporate clients
- − Platform licensing from approximately £500,000+ ($630,000+) per year
- − Significant implementation effort, typically 6 to 12 months
- − Data infrastructure investment required alongside the AI layer
- − Vendor dependency on Palantir's platform
Faculty AI
UK-based AI consultancy working with government and enterprise clients. Delivers AI strategy, model development, and deployment across multiple sectors. Relevant to consulting firms wanting to build internal AI capability or client-facing AI tools.
- + Deep UK enterprise experience including government contracts
- + UK security clearance for sensitive engagements
- + 200+ team of data scientists and engineers
- + Strong AI ethics and governance framework
- − Enterprise pricing, typically £150,000+ ($189,000+) engagements
- − Consulting and advisory is not a primary vertical
- − Timelines of 3 to 6 months for most projects
- − Less experience with mid-market advisory firms
Slalom
Global technology consulting firm with AI and data science practices. Works with consulting and advisory firms to build AI-powered solutions, modernise data infrastructure, and deploy machine learning at scale across AWS, Azure, and GCP.
- + Strong cloud partnerships with AWS, Azure, and GCP
- + Large team with offices in 40+ cities globally
- + Experience across data engineering, ML, and AI deployment
- + Mid-market friendly compared to McKinsey or BCG
- − Engagement pricing from £100,000+ ($126,000+)
- − Generalist consultancy, not a professional services specialist
- − Quality varies by office and team composition
- − Timelines of 2 to 6 months depending on scope
How much does an AI consultancy cost for a consulting firm? +
Ranges from £3,500 for a focused audit to £500,000+ for enterprise transformation programmes. Mid-market advisory firms typically spend £15,000 to £60,000 on an initial build. Specialist firms like Formulaic offer fixed-fee pricing. Enterprise consultancies like McKinsey and BCG work on time-and-materials at partner rates.
Should a consulting firm build AI internally or hire a specialist? +
Building internal AI capability takes 12 to 18 months and requires hiring data scientists, ML engineers, and AI product managers. Hiring a specialist gets production systems deployed in weeks to months. Most mid-market firms start with a specialist build, then hire internal capability to maintain and extend the systems.
What AI systems do consulting firms typically build first? +
The highest-ROI first builds are usually proposal generation automation, knowledge management and search across past deliverables, client data analysis and reporting automation, and bench utilisation and staffing optimisation. Start with the process that costs the most time per consultant per week.
Do AI consultancies need access to client data? +
For most builds, yes. The system needs to connect to your CRM, project management platform, knowledge base, or financial systems. Reputable consultancies will sign NDAs, establish data processing agreements, and deploy on infrastructure in your jurisdiction. Ask about data residency before signing.
How long does it take to deploy AI in a consulting firm? +
A single system like proposal automation or knowledge search takes 4 to 8 weeks with a specialist firm. Enterprise platform deployments from Palantir or McKinsey take 6 to 12 months. The difference is scope. Start with one high-value system, prove ROI, then expand.
Can AI help consulting firms win more client work? +
Yes. AI-powered proposal generation reduces the time from opportunity to submission from days to hours. Knowledge search surfaces relevant past work and credentials for pitches. Client intelligence systems aggregate public and internal data to prepare consultants before meetings. The firms deploying these systems are winning more because they respond faster and with more relevant proposals.
Find out what's worth building for your firm_
Take the AI Opportunity Scorecard for a benchmarked readiness score and three prioritised use cases. 3 minutes. Free.