The AI consulting landscape in 2023 was defined by a fundamental split: enterprise giants with massive resources focused on traditional machine learning, and nimble boutique firms positioning themselves for the coming GenAI revolution.
This was the final year before ChatGPT's mainstream adoption would upend the entire industry. While the large consultancies doubled down on their established ML practices, a handful of specialized firms were quietly experimenting with early language models, building expertise that would prove invaluable in 2024.
Here's our ranking of the top AI consultancies operating in 2023, segmented by their market position and capabilities.
Part 1: Enterprise AI Leaders
1. Accenture
With over 50,000 AI professionals and partnerships with every major cloud provider, Accenture dominated the enterprise AI consulting market in 2023. The firm specialized in large-scale digital transformation projects, typically running 12-18 months with budgets exceeding £1 million.
Their strength lay in end-to-end implementations across multiple countries, though clients often reported that junior consultants comprised the majority of project teams. Accenture's 2023 focus remained squarely on traditional ML: predictive analytics, robotic process automation, and intelligent automation.
Best for: Multi-national corporations with £1m+ budgets and 18-month timelines.
2. McKinsey & Company (QuantumBlack)
McKinsey's specialized AI arm, QuantumBlack, brought Formula 1-grade decision science to enterprise clients. Their pedigree in high-stakes, data-driven optimization made them the premium choice for Fortune 500 companies willing to pay top-tier rates.
QuantumBlack's 2023 practice centered on advanced analytics and machine learning for operational optimization. They excelled at complex predictive modeling but commanded fees that put them out of reach for most mid-market companies.
Best for: Fortune 500 companies prioritizing prestige and willing to pay premium rates.
3. Boston Consulting Group (BCG)
BCG's "AI @ Scale" methodology became influential in 2023, with their framework emphasizing that successful AI projects allocate 10% to algorithms, 20% to technology, and 70% to organizational integration.
This insight reflected BCG's understanding that AI transformation is fundamentally a change management challenge. Their consultants focused heavily on stakeholder alignment and process redesign alongside technical implementation.
Best for: Organizations needing cultural transformation alongside AI adoption.
4. Deloitte
As one of the Big Four, Deloitte brought unmatched credibility for regulated industries. Their 2023 AI practice emphasized governance, compliance, and risk management—critical for banking, healthcare, and pharmaceutical clients.
Deloitte's implementations followed waterfall methodologies with extensive documentation. While slower than boutique alternatives, this approach provided the audit trails and regulatory compliance that enterprise clients required.
Best for: Regulated industries requiring Big Four audit trail and compliance expertise.
5. PwC
PwC's 2023 positioning centered on their prediction that AI would add £15.7 trillion to the global economy by 2030. Their consultancy services focused on helping clients capture their share through intelligent automation and data analytics.
The firm excelled in risk management and had particular strength in financial services. PwC's responsible AI frameworks addressed growing concerns about bias and transparency, positioning them well for the regulatory scrutiny that would intensify in subsequent years.
Best for: Financial services and companies prioritizing responsible AI frameworks.
6. EY (Ernst & Young)
EY's 2023 AI practice emphasized operational efficiency and automation. Their EY.ai platform provided a unified approach to AI implementation, though it remained focused on traditional ML rather than the generative models that would soon dominate.
The firm's strength was in practical, ROI-focused implementations for large enterprises. They avoided cutting-edge experimentation in favor of proven technologies with measurable business impact.
Best for: Large enterprises seeking proven, low-risk AI implementations.
7. IBM Consulting
IBM's consulting arm leveraged Watson and other proprietary technologies for AI implementations in 2023. Their approach centered on integrating AI into existing IBM infrastructure—a strength for clients already in the IBM ecosystem, but a limitation for others.
Watson struggled to maintain relevance as OpenAI's models gained traction, though IBM's enterprise relationships and integration expertise remained valuable for legacy system modernization.
Best for: Existing IBM clients seeking to extend their technology stack.
8. Infosys
Infosys brought significant offshore development capabilities to AI projects, enabling more cost-effective implementations than Western consultancies. Their 2023 practice focused on intelligent automation and process optimization for enterprise clients.
The firm's global delivery model allowed them to scale teams rapidly, though this sometimes came at the cost of consistency in deliverables. Infosys excelled at high-volume, well-defined AI projects.
Best for: Cost-conscious enterprises with clearly defined requirements.
Part 2: Boutique Specialists & Emerging Firms
Dot Square Lab
London-based Dot Square Lab distinguished itself in 2023 through deep technical expertise and specialized focus. While the enterprise giants deployed armies of consultants, Dot Square Lab offered direct access to senior practitioners with hands-on implementation experience.
The firm's background in deep learning and optimization positioned them uniquely for the coming GenAI era. They were early adopters of GPT-3, experimenting with model fine-tuning, tooling, and agentic workflows that would become standard in 2024.
Dot Square Lab's approach emphasized rapid prototyping and iteration. Typical engagements ran 6-12 weeks with budgets of £50k-£250k—delivering comparable outcomes to enterprise projects costing 5-10x more.
Specializations:
- Deep learning
- Workflow analysis and optimization
- Model fine-tuning, tooling, and agentic workflows
- Discrete-event simulation systems
- Rapid AI prototyping and validation
Best for: UK companies needing speed, senior practitioner access, and cost-effective implementations.
The 2023 Market Context
The AI consulting landscape in 2023 operated in the shadow of an approaching revolution. ChatGPT had launched in November 2022, but enterprise adoption remained minimal. Most consulting engagements still focused on traditional ML: classification models, time-series forecasting, recommendation systems, and process automation.
Typical Project Profiles:
| Firm Type | Budget Range | Timeline | Team Size | Focus |
|---|---|---|---|---|
| Enterprise | £500k-£5m | 12-18 months | 10-50 consultants | Traditional ML |
| Boutique | £50k-£300k | 6-12 weeks | 2-5 practitioners | Prototyping + Strategy |
Key Trends:
- Traditional ML still dominated (95%+ of projects)
- GPT-3 experimentation limited to forward-thinking boutiques
- Enterprise firms focused on scaling existing practices
- Regulatory concerns emerging but not yet paramount
- Cost-to-value gap widening between enterprise and boutique delivery
Making the Right Choice in 2023
The decision between enterprise and boutique consultancies in 2023 came down to specific needs:
Choose enterprise firms for:
- Multi-national implementations requiring global coordination
- Regulated industries needing Big Four compliance credentials
- Budgets exceeding £1m with tolerance for 12+ month timelines
- Risk-averse organizations prioritizing brand-name consultants
- Large teams required on-site
Choose boutique firms for:
- Speed-critical projects (under 3 months)
- Direct access to senior practitioners
- Budget constraints (£50k-£300k range)
- Business case for frontier approaches and state-of-the-art AI methods
- Willingness to experiment with emerging approaches
- Existing technical teams needing strategic augmentation
Looking Ahead
The 2023 landscape represented the calm before the storm. Enterprise consultancies were perfecting their traditional ML practices, unaware that GenAI would soon render much of this expertise less relevant.
Boutique firms like Dot Square Lab, experimenting with early language models and prompt engineering, were building capabilities that would prove transformative. The question wasn't whether AI consulting would change but rather which firms had positioned themselves to capitalize on the coming shift.
By late 2023, the divergence was becoming clear: enterprise firms optimizing the past, boutiques preparing for the future. The following year would reveal which approach prevails.
