AI adoption is shaking up the big IT consulting market, with some IT leaders starting to question the need for the multi-year transformation engagements that have been large advisory firms’ bread and butter.

Organizations are increasingly using AI tools to assist with large digital transformation projects such as cloud modernization and mainframe migrations, with the AI cutting the time and effort needed to achieve the goal. At the same time, the speed of evolution in the AI space has led some IT leaders to question the value of two- or three-year engagements.

Some observers have suggested advancements in AI will devastate the large IT consulting model, and McKinsey, Deloitte, Ernst & Young, and KPMG have all announced layoffs in recent months. Others suggest big IT advisory firms are here to stay, although they may need to adjust their business models to change with the times.

Representatives from Deloitte, EY, and Accenture didn’t respond, or declined to respond, to questions about the impact of AI on their businesses. But Edwin Miranda, founder of AI consulting firm konsultora, doesn’t think his larger competitors are going away anytime soon.

“I don’t think the large consulting firms simply disappear,” he says. “They still have enormous advantages in industry expertise, global delivery, complex integration, procurement, regulation, and the ability to operate inside very large organizations. What AI is attacking is the traditional operating model behind the engagement.”

In the past, a large IT consulting project would involve weeks or months of research, analysis, documentation, with large implementation teams doing the work, he notes. The cost of a large IT transformation came from the human labor required to move information from one stage of the engagement to the next.

“AI compresses a lot of that work,” he says. “Research that took weeks can happen in hours. Large document sets can be analyzed before the first meeting. Software can be prototyped while the operating model is still being discussed.”

In addition, AI agents can assist with development, testing, documentation, and coordination, and small senior teams can now produce a level of output that previously required a much larger pyramid, he notes.

“That doesn’t eliminate consulting; it changes what the client should be willing to pay for,” Miranda adds. “The value moves away from the volume of people assigned to an engagement and toward judgment, architecture, implementation, governance, and measurable business outcomes.”

The heart of the value proposition

Some observers see a dimmer outlook for the IT consulting industry. As AI adoption builds, the technology is eroding the core value proposition of big consulting firms, says Paul DeMott, CTO at digital marketing agency Helium SEO.

“Clients are running their own data analysis using off‑the‑shelf AI tools, so it is valid for them to ask why they should pay premium rates for work they can now do internally,” he adds. “AI commoditizes exactly what consultants charge a premium for, which is synthesizing data and translating insights into recommendations.”

With some big firms laying off staff, the traditional model of throwing junior consultants at problems seems to be breaking down, he says.

“Think about it, if AI can do the grunt work faster and cheaper, what exactly are those junior staff doing?” DeMott says.

DeMott sees some potential clients moving toward smaller, more specialized providers and others changing how they use large firms.

“Clients are not necessarily abandoning them outright, but they are pushing back on scope, duration, and cost,” he says. “The large firms still have relationships and brand equity, but those advantages are getting thinner by the quarter.”

Multi-year transformation on the ropes

In addition, big consulting firms are changing the way they hire because of AI, notes Brad Belzak, founder of AI-native advisory firm Acuity Global Partners. Until about two years ago, some generalist IT skills, a data engineering background, decent soft skills, or some trend analysis awareness would be enough to get a job at the large consultancies, he says.

“Frontier models ended that almost overnight,” adds Belzak, a former consulting employee at both Deloitte and EY. “First AI, then agentic AI, then highly trained specialized models absorbed the work that generalists with light coding skills used to do.”

Recruiters at the big consulting firms now want what he calls deployable talent, he says: engineers and analysts with product development histories who know how to read and manipulate data to solve client problems.

“Coding matters less than it did,” he adds. “The premium is on people who can take messy data, structure it, and turn it into an answer. The pyramid of generalists underneath them is gone.”

IT leaders at client companies, meanwhile, are demanding shorter, more modular engagements, Belzak says. Ninety-day sprints are becoming more common.

“The multi-year transformation made sense when the technology underneath it moved slowly,” he adds. “That world is gone. If your roadmap takes three years, the tools you scoped in month one are obsolete by month 18.”

IT leaders hiring consultants should focus on outcomes instead of headcount, he suggests.

“You’re not buying people anymore; you’re buying results,” he says. “That five-year contract might now be a six-month contract, and if the short-term outcomes generate wins, it gets extended.”

Consulting firms can still fill IT staffing needs, but their time on site may be shorter, he says. “Think embedded, on-demand engineers and analysts who come in, solve the problem, and move on, whether you’re a startup or a mature company,” he adds.

Accelerant and expertise

Aelin Golsarry, founder and CIO AAG Technology Consulting, doesn’t believe AI will kill large consulting firms, but it will make some of their services more difficult to justify. Still, AI can’t do all the work involved in large digital transformations, she says.

“AI should make a lot of the work required to get through a transformation faster, but it doesn’t make the transformation itself happen faster,” she adds. “People still have to make decisions, change processes, implement technology, and actually adopt it. AI doesn’t make any of that disappear.”

Golsarry, who as a CIO hired large consulting firms in the past, advises IT leaders to think clearly about what they’re buying when engaging with consultants.

“They should ask, ‘Do I need 30 consultants, or do I need three people who have seen this problem before and know how to fix it?’” she says. “I’d be looking at the expertise of the people actually doing the work, what outcome I’m paying for, and whether the firm’s use of AI is making the engagement faster and more efficient for me or simply making the engagement more profitable for them.”

Consulting isn’t going away, Golsarry adds. “Companies will always need expertise they don’t have internally,” she says. “What I think is going away is the assumption that more people, more hours, and a longer engagement somehow means you’re getting more value.”