Human Trust vs Automation: Will AI Replace Consulting?

As AI increasingly becomes implemented into everyday business operations, the question of its power over human capabilities is becoming more prominent.

Naturally, people across the world are concerned that AI will become so advanced that it will replace more and more human jobs, as it’s already starting to do.

Consulting is a sector in which this narrative is becoming increasingly common, though the reality of the situation is slightly misunderstood.

While AI tools proliferate across industries, the world’s largest consulting firms are expanding their influence by addressing the fears of executives, rather than competing with machine intelligence.

“McKinsey is dead [because of] AI. Except they’re not,” argues Stuart Winter-Tear, Strategic Advisor for AI Product Strategy in a LinkedIn post.

“Because the riskier the world gets for executives [because of] AI, the more they need someone to lean on – not for insight, but for absolution.”

Stuart identifies a core misconception about consulting’s purpose here, saying: “The people cheering for the downfall of the Big Four don’t understand what those firms are actually for. 

“They imagine these institutions exist to deliver information, facts and knowledge. But in a world of LLMs and infinite data, facts are cheap. Knowledge is abundant. 

“What’s scarce is the emotional permission to act – and the insulation to survive if it goes wrong.”

So, what are leading consultancy enterprises doing differently to responsibly use AI?

What businesses are using AI responsibly for consultancy and how?

The first challenge for consultancies is that, despite large language models (LLM’s) being able to process information at unprecedented scale, they cannot address the political and psychological dimensions of executive decision-making.

The consulting industry recognises this dynamic and has pivoted to productise corporate risk management in the AI era. 

Rather than competing with AI, these firms are building proprietary systems that leverage AI while maintaining the human oversight and accountability structures that executives need.

McKinsey
​​​​​​​The traditional consulting model relied on human-scale analysis delivered through strategy presentations based on expert interviews.

Yet, in an environment where organisations face multi-billion-dollar AI investment decisions, this approach provides insufficient justification for major technology commitments.

McKinsey & Company has responded by constructing proprietary intelligence layers that combine public data, licensed information and decades of internal client engagement data. 

The firm’s Gen AI platform, Lilli, uses a curated dataset of more than 100,000 internal documents and transcripts to produce insights that are unique to McKinsey’s institutional memory.

“We bring the best of our firm’s knowledge to our clients,” explains Erik Roth, McKinsey Senior Partner. 

A recommendation co-authored by Lilli represents a conclusion synthesised from the firm’s entire knowledge base rather than a simple suggestion. 

For boards of directors, this provides evidence-based foundations for decisions while de-risking executive team judgement.

Deloitte
​​​​​​​Deloitte has pursued similar strategies through its 'Trustworthy AI' framework. 

This operational methodology helps clients manage AI-related ethical and operational risks through auditable systems for algorithmic bias testing and data governance. 

The framework transforms abstract trust concepts into tangible risk management products.

“Trust is a key driver of value and a critical component to harnessing the power of AI,” says Beena Ammanath, Executive Director of the Deloitte AI Institute. 

By codifying trust into replicable products, Deloitte provides leaders with documented due diligence required for large-scale AI deployments.

Accenture and Microsoft 
​​​​​​​Consulting firms recognise that no single organisation can control entire AI technology stacks. 

They have forged alliances with technology giants including Microsoft, Google Cloud, Salesforce and Nvidia to position themselves as essential strategy and implementation layers around raw technology capabilities.

Therefore, Accenture has invested US$3bn in AI capabilities deeply integrated with its Microsoft partnership. 

Rather than advising clients to use Azure OpenAI services, Accenture builds industry-specific solutions including platforms for banking compliance and supply chain optimisation.

“We help clients move from pilot projects to scaling securely and responsibly,” says Julie Sweet, Accenture Chair and CEO. 

Enterprise customers receive industry-specific AI versions with pre-packaged implementation plans, change management support and risk frameworks rather than generic AI services.

This bundled approach provides single points of accountability that simplify procurement and deployment risks for clients. 

Human psychology driving consulting demand despite AI advances

Stuart emphasises that predictions of AI-driven consulting disruption misunderstand fundamental human behaviour patterns.

“This isn’t a knowledge problem. It’s a human one,” he argues, referencing Security Expert Ross Haleliuk’s observation that senior executives need cover rather than information.

“Senior execs at large companies aren’t dumb... What they need is cover, a credible third-party to endorse a course of action so that if it fails, the board isn’t asking, ‘Why did you pursue this strategy?’” Ross says.

Corporate decision-makers operate within systems where individual accountability creates career risks – whereas consulting firms provide risk-sharing mechanisms that allow executives to distribute responsibility for major decisions across credible external advisors.

“We’re not rational optimisers. We’re social, narrative-driven, blame-sensitive animals. We seek affiliation, fear shame and avoid risk we can’t share,” Stuart says.

Decision-makers seek defensible positions rather than optimal solutions, making consulting firms valuable for their logos and risk distribution capabilities.

The AI revolution has intensified these dynamics by creating new categories of corporate risk around data privacy, algorithmic bias, security vulnerabilities and strategic misdirection. 

Rather than eliminating consulting demand, AI adoption has created additional reasons for executives to seek external validation and risk mitigation support.

Stuart says: “Too many people like to think that tech is the solution to everything, but unless they’ve taken classes in social sciences like psychology or spent time studying human behaviour, they probably have a very oversimplified understanding of the world they live in.”

Strategic decisions in corporate environments involve perception management alongside technical analysis.

“Strategy, in the real world, is as much about perception as substance. It’s not just a decision – it’s a performance. And performances need audiences, scripts, context and blame management,” Stuart observes.

“If AI can’t absorb fear, status, power, ego, or the need to be seen as ‘doing the right thing’, it won’t be the solution execs actually need. Because strategy isn’t just about knowing. It’s about navigating – ambiguity, power, risk and reputation.

“You can automate insight. But you can’t automate absolution."