AI Consulting for B2B Marketers

The multi-billion-pound market reshaping consulting economics

In the UK, the consulting market contracted 3.4% to £14.9 billion in 2024—its first decline since the pandemic—before stabilising. The Management Consultancies Association's 2025 member survey projects 6.4% growth in 2025 and 8.7% in 2026, with two-thirds of UK consulting firms expecting growth specifically in AI consulting services.

Global AI spending is accelerating dramatically. Gartner forecasts £1.5 trillion in total AI spending in 2025, exceeding £2 trillion in 2026. Venture capital has followed suit: AI startup funding reached £203 billion in 2025, up 75% from 2024, with AI consuming more than half of all global VC investment for the first time.

For B2B marketing leaders, these figures signal a fundamental shift. When Whitehat SEO analyses AI consultancy requirements for our clients, we're seeing the same pressure points: the need for faster insights, better attribution, and AI-augmented decision-making.

Every major consulting firm now operates proprietary AI platforms

The arms race in proprietary AI tools has produced a remarkably complete landscape. Every major consulting firm has built or deployed bespoke AI systems, with adoption rates reaching striking heights.

McKinsey's Lilli is arguably the most mature internal platform. Built on retrieval-augmented generation over 100,000+ internal documents, Lilli handles 500,000+ prompts per month and has answered over 19 million queries. Adoption stands at 94% of McKinsey's roughly 45,000-person workforce. The firm reports 30% time savings in information gathering and a 20% improvement in content quality.

BCG built GENE, a GPT-4o-based chatbot fine-tuned with BCG's knowledge, alongside Deckster for presentation refinement. BCG employees have built 6,000+ AI agents and 18,000+ custom GPTs. AI consulting now represents 20% of BCG's £13.5 billion revenue—approximately £2.7 billion—a revenue stream that barely existed two years ago.

Among the Big Four, approaches diverge significantly. Deloitte blocked ChatGPT internally for security reasons, instead building PairD for internal tasks and Zora AI, a fleet of agentic AI agents developed with NVIDIA. EY invested £1.4 billion in its EY.ai platform, deploying 1,000 AI agents with plans to scale to 100,000 by 2028. KPMG committed £4.2 billion in AI-backed technology investments through its Workbench platform. PwC deployed Agent OS with 25,000 intelligent agents across client operations.

Accenture has made the largest single commitment: £3 billion over three years in its Data & AI practice, scaling to over 77,000 AI professionals and booking £3.6 billion in generative AI consulting engagements.

The implication for marketing technology? These same patterns are emerging in marketing platforms. At Whitehat, our HubSpot onboarding services now include Breeze AI configuration as standard, ensuring clients capture maximum value from AI-powered marketing automation from day one.

The landmark evidence on AI productivity—and its limits

The gold-standard study remains the September 2023 BCG-Harvard experiment, involving 758 BCG consultants and researchers from Harvard Business School, MIT Sloan, and Wharton. The findings were remarkable: consultants using GPT-4 completed 12.2% more tasks, 25.1% faster, at 40%+ higher quality.

Junior consultants saw a 43% performance improvement versus 17% for seniors—AI acted as a powerful "skill leveller." However, for tasks outside AI's capabilities, consultants using AI were 19% less likely to produce correct solutions, revealing a dangerous over-reliance pattern the researchers termed "the jagged frontier."

These findings carry an important caveat exposed in October 2025, when Deloitte was asked to issue a partial refund for a £290,000 report prepared for the Australian government that contained AI-generated hallucinations. A Deloitte survey found that 66% of workers use AI outputs without verifying accuracy, and 56% have made work mistakes because of AI.

For marketing teams, this mirrors our experience at Whitehat. AI accelerates content creation and analysis dramatically—but human oversight remains essential. Our answer engine optimisation (AEO) services combine AI efficiency with expert review, ensuring accuracy whilst capturing the speed benefits.

From pyramid to obelisk: how AI is restructuring professional services

A landmark Harvard Business Review article in September 2025 described consulting's structural shift from the traditional pyramid model—a broad base of junior analysts supporting a narrow top of partners—to a leaner "obelisk" with fewer layers, smaller teams, and more leverage at every level. AI is automating the data-gathering, research, and analysis tasks that comprised the pyramid's foundation.

The data on entry-level hiring cuts tells the story starkly:

• PwC cut US entry-level hiring by 32%
• KPMG slashed entry-level hiring by 29%
• Deloitte reduced UK entry-level jobs by 18%
• EY cut UK entry-level jobs by 11%
• Indeed data shows 44% fewer UK accounting graduate openings compared to 2023

Yet the picture is more nuanced than simple displacement. McKinsey, despite cutting roughly 5,000 roles since 2023, is planning a 12% staff increase in 2026 focused on AI and digital roles. Accenture simultaneously laid off 11,000 employees and hired 77,000+ AI professionals. The pattern is clear: firms are not shrinking—they're reshaping, replacing traditional junior capacity with AI-augmented specialists.

The skills premium is significant. PwC's Global AI Jobs Barometer shows workers with AI skills command a 56% wage premium, up from 25% the prior year. For marketers, this underscores why investing in AI literacy now—whether through HubSpot's Breeze AI capabilities or broader upskilling—delivers career and commercial returns.

Regulation is tightening—but unevenly

The regulatory landscape presents a split picture between the EU's prescriptive approach and the UK's lighter touch.

The EU AI Act is the world's most comprehensive AI legislation. Prohibited AI practices and AI literacy obligations took effect in February 2025. General-purpose AI model obligations became active in August 2025. Full application for high-risk AI systems arrives in August 2026, with fines reaching €35 million or 7% of global turnover.

The UK has no comprehensive AI law and likely won't before late 2026 at the earliest. Instead, it relies on a principles-based framework built around five pillars: safety, transparency, fairness, accountability, and contestability. The FCA's approach is notably pragmatic: 75% of UK financial services firms already use AI, and the regulator has stated it will not introduce AI-specific rules, instead applying existing Consumer Duty requirements.

For marketing compliance, the practical landscape involves data governance frameworks aligned with ISO/IEC 42001:2023, enterprise-grade AI deployment to avoid data leakage, and human-in-the-loop quality assurance—76% of enterprises now include this. Our marketing services incorporate these governance principles by default.

Agentic AI and the next phase of transformation

The conversation is already moving beyond chatbots and copilots. Agentic AI—systems that independently reason, plan, and execute multi-step workflows without constant human oversight—represents the next frontier. Gartner predicts 40% of enterprise applications will embed AI agents by end of 2026, up from less than 5% in 2025.

McKinsey's research indicates 62% of organisations are experimenting with agentic AI, with 23% beginning to scale agents in at least one business function. Deloitte projects that 25% of companies using generative AI will launch agentic AI pilots in 2025, growing to 50% by 2027.

Consulting's pricing model is under corresponding pressure. The gap between delivery cost and client charges is widening. McKinsey's QuantumBlack has pioneered hybrid pricing—fixed base fees plus tiered AI resource packages plus success fees tied to measurable outcomes. The shift from time-based to value-based billing is accelerating.

New service categories are emerging rapidly. AI governance and ethics advisory is the fastest-growing segment, driven by the EU AI Act and Gartner's forecast of £5 billion in compliance investment by 2027. This mirrors what we see in marketing: clients increasingly need guidance on responsible AI use in customer communications, from content marketing to automated lead nurturing.

What this means for B2B marketers

The consulting industry's transformation offers a preview of what's coming for marketing functions. Three insights stand out for practitioners navigating this landscape:

First, the winners aren't those with the most AI tools—they're those solving the adoption gap. BCG's finding that 74% of companies struggle to scale AI value suggests the real opportunity lies in implementation, not experimentation. For marketing teams, this means moving beyond pilots to systematic AI integration across content, analytics, and campaign execution.

Second, the pricing transparency reckoning is coming. As clients grow more sophisticated about AI's efficiency impact, the current margin arbitrage will become untenable. Marketing agencies that proactively share productivity gains will build lasting trust. At Whitehat, we've always operated on transparent pricing through our published pricing page—this principle becomes more important as AI changes the economics of delivery.

Third, for individual marketers, the career imperative is clear. The 56% wage premium for AI skills and simultaneous entry-level hiring cuts signal that mid-career professionals who combine domain expertise with AI fluency will be the most valuable players. This isn't about becoming a data scientist—it's about understanding how to leverage AI for better SEO, more effective HubSpot automation, and sharper campaign attribution.

The bottom line

The consulting industry in 2026 stands at an inflection point where experimentation gives way to operational reality. AI adoption is near-universal among major firms, productivity gains are real but accompanied by serious quality risks, and the economic model—from staffing structures to pricing—is under fundamental pressure.

For B2B marketers and the businesses they serve, this transformation is both warning and opportunity. The firms that thrive won't be those with the flashiest AI demonstrations, but those that systematically integrate AI into repeatable, measurable processes—whilst maintaining the human judgment that catches errors and builds client relationships.

Frequently asked questions

References

1. Dell'Acqua, F. et al. (2023) "Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality." Harvard Business School Working Paper No. 24-013
2. Gartner (2026) "Gartner Says Worldwide AI Spending Will Total $2.5 Trillion in 2026." Gartner Newsroom
3. Duncan, D., Anderson, T. & Saviano, J. (2025) "AI Is Changing the Structure of Consulting Firms." Harvard Business Review
4. Management Consultancies Association (2025) "MCA Forecasts Growth and Highlights Continuing Improvements in Social Mobility in the Consulting Sector." MCA Press Releases
5. Gartner (2025) "Gartner Says Worldwide AI Spending Will Total $1.5 Trillion in 2025." Gartner Newsroom

Ready to integrate AI into your marketing strategy?

Whitehat helps B2B companies leverage HubSpot's AI capabilities, build attribution your CFO will trust, and capture visibility in AI search engines. Let's talk about what AI-powered marketing looks like for your business.