When organisations think about getting help with AI, the default is usually a Big 4 firm or one of the major tech consultancies. But there’s another option worth considering: boutique AI specialists.

Silverpond, based in Melbourne, is one of the more established Australian examples. Looking at how they operate offers useful insights into when specialist firms might be the right choice.

The Silverpond Story

Silverpond started in 2015, which in AI terms makes them veterans. They built their reputation on deep technical work – machine learning, computer vision, and natural language processing – before these became mainstream business topics.

Their team is technically heavy. Unlike the Big 4, where partners typically have business backgrounds and technical work is done by junior staff, Silverpond’s leadership includes people who’ve done actual ML engineering.

They’ve worked across Australian enterprises in retail, manufacturing, healthcare, and government. Not household names usually, but meaningful implementations.

What Boutique AI Firms Offer

The value proposition of specialist firms like Silverpond:

Deep technical expertise: When your problem is genuinely technically complex, you want people who’ve solved similar problems before. Specialist firms accumulate this expertise.

Practitioner access: At a Big 4, you buy the partner’s time but get associate and analyst time. At a boutique, the senior technical people often do the actual work.

Focus: They only do AI. They’re not trying to sell you ERP implementations or audit services. This focus means deeper capability in their domain.

Agility: Smaller teams can pivot faster, experiment more readily, and adapt approaches mid-project without bureaucratic overhead.

Often better rates: Without Big 4 overhead, hourly rates are frequently lower, even for more senior resources.

Where Big Firms Have Advantages

Boutiques aren’t universally better. Large consultancies have genuine advantages:

Scale: For enterprise-wide transformations requiring dozens of consultants, boutiques can’t scale.

Integration capabilities: Large firms have practice areas in change management, process redesign, and technology integration that complement AI work.

Risk mitigation: “Nobody got fired for hiring McKinsey” – large firm names provide political cover for executives.

Global reach: For multinationals needing consistent global delivery, Big 4 global networks matter.

Ongoing relationship: If you already have a big firm embedded in your organisation, using them for AI may be more practical.

When to Choose a Boutique

Based on patterns I’ve observed, boutique AI specialists make sense when:

The problem is technically complex: If the challenge is at the frontier of what’s possible – custom model development, novel applications, edge cases – specialist expertise matters.

You want senior people doing the work: If you’re paying for expertise, you want that expertise actually engaged, not just overseeing junior staff.

The scope is contained: For defined AI projects with clear boundaries, boutiques are often more efficient.

Budget matters: If you need to maximise the AI work done per dollar spent, boutique rates are typically better.

You value collaboration over delivery: Boutiques often work alongside internal teams, building capability. Big firms tend toward “we’ll deliver it to you.”

When to Choose a Large Firm

Big consultancies make more sense when:

Transformation is broader than AI: If AI is part of a larger change program involving process redesign, organisation change, and technology modernisation, integrated delivery from one firm may be simpler.

Political cover is needed: For bet-the-company initiatives, having a blue-chip firm involved provides executives with defensible decision-making.

Scale is required: Large programs requiring many consultants simultaneously exceed boutique capacity.

Global coordination matters: Multinational implementations benefit from global firm networks.

What to Watch For

If you’re considering a boutique AI firm, due diligence points:

Reference clients: Have they done something similar to your project? Can you speak with references?

Team stability: Who specifically will work on your project? What’s their background? What happens if they leave?

Financial stability: Small firms have higher failure risk. You don’t want your AI partner disappearing mid-project.

Intellectual property: Who owns the models, code, and processes developed? This varies significantly.

Scaling ability: If the pilot succeeds and you want to expand, can they support that? Or do you need to transition to another partner?

The Hybrid Approach

Some organisations use both: boutique specialists for technically complex AI development, large firms for integration and change management.

This can work well when:

• Clear boundaries exist between technical AI work and broader transformation
• Both firms can collaborate effectively (not always the case)
• You have internal capability to coordinate multiple vendors

The downside: coordination overhead and potential finger-pointing when things go wrong.

My View

Having worked on both sides – at large consultancies and with boutique partners – I think the default Big 4 assumption is often wrong for AI projects.

For technically demanding AI work, the quality of who actually does the work matters enormously. Boutique specialists often provide better value: more senior practitioners, deeper expertise, and lower overhead costs.

That said, context matters. Some situations genuinely need large firm capabilities. The key is choosing deliberately rather than defaulting to familiar names.

Questions to Ask Any AI Partner

Regardless of firm size:

1. Who specifically will work on my project? What’s their relevant experience?
2. What similar projects have you delivered? Can I speak with those clients?
3. How do you handle IP ownership?
4. What happens if key people leave?
5. How do you measure success, and what happens if we don’t achieve it?
6. What’s your approach when things go wrong?

Good partners – large or small – welcome these questions. Evasive answers are telling.

Final Thought

The AI consulting landscape is broader than most people realise. Boutique specialists like Silverpond offer a different model from large consultancies – one that’s often better suited to technically demanding AI work.

Don’t assume one model is always better. Understand what you actually need, then find the partner that matches.