From Deck-Makers to Decision Partners: AI Is Remaking Consul…

The consulting industry is undergoing a structural shift as artificial intelligence automates the junior-level research and analysis work that once supported its pyramid-shaped staffing model. 

According to a global survey by McKinsey & Company, The State of AI in 2025, 88% of organisations now report using AI in at least one business function. 

Meanwhile, a Harvard Business Review (HBR) commentary argued that this trend is reducing the need for large analyst pools, the backbone of the traditional consulting pyramid, prompting firms to rethink how they deliver value. 

At a recent seminar on consulting in the age of AI, Bhaskar Ghosh, chief strategy and innovation officer at Accenture, said the sector is entering what he calls the “intelligent age,” where systems can sense, decide, act and learn autonomously. This, he argued, requires consulting to “redefine itself” by shifting from advice-driven work to measurable outcomes.

“AI is real, AI needs to create value; consulting must redefine itself,” he said, adding that the goal should be “problem solving with human creativity, plus machine efficiency.”

His view was echoed by Kartikeya Bolar Pramoda, associate professor at TA Pai Management Institute (TAPMI), Manipal, specialising in information systems and analytics. Pramoda believes that the future belongs to firms “bold enough to redesign their models, elevate their people, and harness AI as an amplifier of human judgement.”

Industry practitioners say this reflects shifting client expectations. 

According to Gaurav Gupta, head of R&D at consulting firm Kotter, traditional reasons companies hire consultants (access to information, benchmark knowledge, analytics, and external validation) are becoming less valuable as AI makes information abundant.

“What is continuing to be extremely useful is deep expertise,” he said, arguing that specialised skills and insights drawn from hard-earned experience are “not easy to emulate through automation.”

But the transition is exposing uneven effects across consulting careers. 

Shivaraj KM, principal analyst with ISG (Information Services Group), said efficiency gains are already visible at the bottom of the talent structure, especially in roles tied to research, client-delivery support, and marketing. 

While “AI has had little effect at mid-senior roles,” he warned firms are likely to operate with fewer entry-level staff as judgment-based work remains concentrated higher up.

“It is not the death of the industry,” he said, “just learning to work in the new environments of GenAI.”

Why This Shift

The pressure on consulting’s traditional model comes from multiple trends converging. First, AI tools, especially generative AI and “agentic” systems, are now mature enough to perform tasks historically done by junior analysts, like data gathering, summarising, modelling, and initial diagnostics. 

Second, the expectations of clients, the buyers of consulting, are changing. 

With internal capabilities growing and AI tools broadly accessible, many companies expect faster turnaround, tangible execution support, and real business outcomes rather than long drawn-out advisory reports. 

As Gupta noted, the value proposition is shifting away from information scarcity to “deep expertise” and execution capacity.

How Firms Are Responding

In response to these shifts, many consulting firms are retooling their structures, talent pipelines, and delivery models.

According to Ben Appleton, founder of Strat-Bridge, a specialist executive search partner and a consulting company, firms are increasingly adopting cross-functional teams or “pods” combining domain specialists, AI-fluent consultants, and senior strategic advisors. 

These teams, smaller than traditional consulting squads, lean heavily on AI to do groundwork: data extraction, summarisation, modelling, initial insights.

Human consultants are then freed to do what machines cannot: interpret ambiguous problems, apply judgment, navigate organisational complexity, and build trust with clients.

The result is that consulting engagements are shifting from slide-heavy decks to outcome-oriented delivery, execution, implementation support, and ongoing advisory. 

This shift echoes what Ghosh called “new consulting”: a model defined by value creation, agility, and human-machine collaboration.

Such firms are also rethinking hiring and training. Instead of recruiting large batches of generalist analysts, many are raising the bar for domain depth, sector experience, and “AI fluency”, the ability to work with AI tools, interpret machine outputs, and combine them with human insight. 

The Risks

But this transition is not without friction.

Despite widespread AI adoption, meaningful returns remain elusive. 

As the McKinsey survey noted, only a minority of firms report strong financial impact from their AI investments. Many remain in pilot or experimental phases, and benefits often lag expectations. 

For consulting firms, this means that scaling AI inside delivery models, while also preserving trust, intellectual property, confidentiality, and strategic depth, is a complicated balancing act. 

There is also the human dimension. Many early-career consultants, who once formed the bulk of consulting firms’ workforce, face uncertain futures. 

As Shivaraj’s observation suggested, efficiency gains are hitting the bottom of the pyramid first. The job is not vanishing, but its shape and scale are changing dramatically.

The post From Deck-Makers to Decision Partners: AI Is Remaking Consulting appeared first on Analytics India Magazine.

Generated by RSStT. The copyright belongs to the original author.

Source