Big Four AI Consulting Alternative

A Big Four AI Consulting Alternative That Advises and Builds

Aaga is an AI-native consultancy: a lean, senior team that advises on AI and builds the systems it recommends. "Big Four" usually refers to Deloitte, PwC, EY and KPMG, and buyers often compare them with strategy firms such as McKinsey and BCG for AI consulting. For buyers comparing these firms with Aaga, the main difference is the delivery model. Large professional services and strategy firms are typically structured for consulting-led, organization-wide programs. Aaga is structured for focused AI work, where the same engineers rank the use cases, build the pilot and measure the result.

Both models have their place. This page explains when an advise-and-build partner like Aaga is the better fit, and when it is not.

What Is the Large Consulting Model for AI?

The large consulting model usually starts with assessment and strategy. A team reviews current processes and capabilities, identifies AI opportunities across the business, designs a target operating model and governance, builds a roadmap and then moves into delivery. Strategy, risk and delivery work are often handled by different teams, sometimes with implementation partners.

That approach suits large enterprises where the hardest part of AI is alignment: many business units, many countries, regulators, boards and thousands of employees who need to change how they work.

What Is the Advise-and-Build Model?

The advise-and-build model puts advice and delivery in one small team. You start with a business outcome, rank a short list of use cases and build a working pilot early. Real results then shape the strategy.

At Aaga, that looks like this:

1. Outcome call. We agree the business result you want, such as faster claim handling, quicker quote turnaround or fewer manual data-entry steps.
2. Ranked shortlist. We score candidate use cases on value, effort, risk and data readiness, and test the top one on samples of your data.
3. Pilot blueprint. A few pages, not a long deck: scope, architecture, metrics, risks and a budget range.
4. Working pilot. We build it on your real systems, for example an AI agent connected to your CRM, and measure it against the agreed metrics.

Our AI strategy consulting service covers the strategy side in more depth, from the use-case portfolio to governance.

Why Does AI Reward Building Early?

AI is unusually hard to judge on paper. A model that does well on benchmarks may struggle with your scanned documents, your product names or your customers' language. Costs depend on real usage volumes. Accuracy depends on your data. The fastest way to know whether a use case works is to build a small version and test it.

That is why we keep strategy short and pair it with a pilot. You still get direction, priorities and governance, but every recommendation is checked against what it takes to deliver.

Advisors Who Also Build

A common frustration in AI projects is the gap between the people who recommend and the people who deliver. When strategy and implementation sit with different teams, assumptions get lost in the hand-over and the delivery team has to rediscover what the strategy meant.

At Aaga, the engineers who run your consultation design and build the system. If they recommend a model, a retrieval approach or an approval flow, they are the ones who will make it work, so they have every reason to be realistic.

When Is a Large Consulting Firm the Better Choice?

Be clear about your scope. A large professional services or strategy firm is likely the better fit if you need:

• AI as part of an organization-wide transformation across many countries and business units
• Large-scale change management for tens of thousands of employees
• One partner covering strategy, risk, regulatory, finance and technology advice together
• An advisor that is fully independent of implementation, for example to review other vendors' work

If your project is a defined AI use case, or a focused AI program that needs to reach production quickly, Aaga is designed for exactly that. Many companies combine the two: a large firm for enterprise-wide strategy and change, and a lean AI-native team for fast, focused builds.

How to Compare AI Consulting Firms Fairly

Whichever firms are on your list, ask them all the same questions:

• Who will do the work? Meet the people, not only the partners or account team.
• What will exist at the end of the first phase? Look for a working pilot or a clear test, not only documents.
• How will AI quality be measured? Expect test sets on your data, accuracy targets and human review for edge cases.
• Who owns the result? Code, prompts, evaluation sets and documentation should be yours.
• How do we exit? Hand-over and knowledge transfer should be planned from the start.

Our guide to the best AI consulting firms explains the main types of AI consultancy, with a scorecard and 20 questions to ask. For the broader picture, see how Aaga compares with large IT services firms.

Getting Started

Engagements usually start with a free consultation and a scoped pilot. There is no long contract to sign before you see results. Read more about how our AI consulting engagements run, or use the form on this page to tell us the outcome you want.

Deloitte, PwC, EY, KPMG, McKinsey & Company and BCG are trademarks of their respective owners. Aaga is not affiliated with or endorsed by any of these firms. This page describes typical delivery models, not any specific company.