Deloitte’s AI Institute has been expanding its Australian presence significantly. For enterprises navigating AI adoption, understanding what the big consultancies are doing – and why – provides useful context.

This isn’t a paid endorsement or a criticism. It’s an analysis of what Deloitte’s AI positioning tells us about the enterprise AI market.

What Deloitte Is Offering

The AI Institute packages several capabilities:

Strategic advisory. Helping organisations develop AI strategies, identify use cases, and build business cases. Classic consulting work applied to AI.

Technical implementation. Building and deploying AI solutions, often using cloud platforms (they have partnerships with all major providers) and their own accelerators.

Operating model design. Defining how AI capabilities should be organised, governed, and operated within enterprises.

Talent and change. Workforce planning for AI impact, skills development, and change management.

Responsible AI. Ethics frameworks, governance, and risk management for AI deployment.

This is comprehensive – deliberately so. The strategy is to be the single vendor for enterprise AI transformation.

What’s Driving the Investment

Deloitte isn’t investing in AI capabilities out of technological enthusiasm. The business drivers:

Client demand. Executives are asking for AI help. Consultancies that can’t credibly respond lose relevance.

Margin opportunity. AI projects can command premium rates. “Strategic AI transformation” bills higher than “technology implementation.”

Competitive necessity. McKinsey, BCG, Accenture, PwC, EY – everyone is building AI practices. Not investing means losing position.

Talent attraction. Data scientists and AI engineers want to work on interesting problems. Building a visible AI practice helps recruitment.

The Strengths

What Deloitte and similar firms bring:

Enterprise relationships. They’re already trusted advisors to many large organisations. AI can be added to existing engagements more easily than a new vendor can establish access.

Business context. They understand enterprise operations, constraints, and decision-making. AI solutions need this context to be practical.

Scale and breadth. They can staff large, complex programs with diverse capabilities – strategy, technology, change, industry expertise.

Risk absorption. Enterprises feel safer engaging a large firm for significant AI investments. The reputational warranty provides comfort.

The Limitations

What to watch for:

Platform agnosticism is partial. Despite claims of neutrality, partnerships with technology vendors influence recommendations. Understand the incentives.

Delivery quality varies. Large consulting firms staff projects with a mix of experienced and junior consultants. Project leadership quality matters enormously.

Rates are premium. You’re paying for the brand and the infrastructure. Whether that premium is justified depends on your alternatives and risk tolerance.

Knowledge retention is a risk. When consultants leave, knowledge goes with them. Ensure you’re building internal capability, not just consuming advice.

What This Signals About the Market

Deloitte’s AI investment reflects broader market realities:

AI is mainstream. When all the major consultancies are investing heavily, AI has crossed from emerging technology to enterprise priority. The conversation has shifted from “should we do AI” to “how should we do AI.”

Integration matters more than algorithms. The consulting bet is that business integration, change management, and governance are where value is added – not in building better models. That’s probably correct for most enterprises.

Buy vs. build is tilting toward buy. Enterprises are increasingly consuming AI platforms rather than building custom capabilities. Consultants help with selection and integration, not algorithm development.

The market is consolidating around platforms. Microsoft, Google, Amazon, and OpenAI are winning the infrastructure layer. Consulting adds value at the implementation and business layer, not the technology layer.

Practical Implications

For enterprises considering AI initiatives:

Deloitte and peers are credible options for large, complex AI transformations. They’re not the only option, and they’re not always the best option, but they’re reasonable choices for certain situations.

Small and mid-market alternatives exist. Boutique firms and smaller consultancies can deliver excellent AI work, often at lower cost. The trade-off is narrower capability and less risk absorption.

The cost-value equation requires scrutiny. Big-firm rates make sense for strategic, high-stakes work. For implementation-focused work, the premium may not be justified.

Internal capability development is essential regardless. Don’t outsource AI competence entirely. Build internal understanding alongside external support.

Check references rigorously. Past AI project success is the best indicator of future success. Ask for specific references and detailed discussions.

A Note on Conflicts

I should be transparent: my consulting practice competes with firms like Deloitte for some work. I have obvious incentives in how I position this analysis.

That said, I regularly recommend clients engage large firms when their situation warrants it. Enterprise relationships, scale, and risk profiles sometimes make that the right choice. Other times, smaller firms or internal teams are better suited.

The right answer depends on your specific context, not on anyone’s general preferences or conflicts.

Final Thought

Deloitte’s AI Institute – and similar practices at peer firms – reflects the maturation of enterprise AI. It’s no longer experimental territory where startups have inherent advantage. It’s becoming mainstream enterprise transformation work where established players have strengths.

For enterprises, this means more options and more credible support available. The challenge is making informed choices among those options rather than defaulting to the biggest brand or the lowest price.

The consulting market is responding to enterprise AI demand. How well they deliver remains to be proven at scale.