Artificial intelligence will take a large slice out of the work technology services firms bill for today, but it will also create more new work than it destroys, according to a new report from Boston Consulting Group (BCG). The catch, the consultancy argues, is that firms have only a few years to turn their existing engineers into the people who can deliver it.

The report, titled The Talent Is Already on Your Payroll. The Clock Isn’t., was released on 29 October 2026. It estimates that AI-driven effort compression will remove about $200 billion of existing services revenue by 2030, roughly a tenth of what the market would otherwise have been worth. At the same time, AI-led services are expected to add $300-400 billion of new work, leaving a net opportunity of $100-200 billion for firms able to build and run AI solutions at scale.

A market that grows while it shrinks

BCG projects the global technology services market to expand from around $1.6-1.7 trillion in 2025 to $2.2-2.4 trillion by 2030. The new AI-led demand comes from three sources: building and operating agentic AI solutions, work that becomes outsourceable as agentic tooling matures, and the human oversight and governance that clients are unlikely to hand over to a model.

The India angle is significant. Speaking to The Economic Times, BCG Managing Director and Partner Sreyssha George, a co-author of the report, said Indian firms account for about 60% of the services market. At a typical revenue-per-employee of about $30,000, India’s share of the $200 billion contraction is equivalent to the work of around four million people. She stressed that this illustrates the scale of work affected rather than forecasting job losses, since the overall market keeps growing. Firms that fail to capture the new AI-led revenue, however, are likely to feel the squeeze.

Not a talent shortage, a talent decision

The report’s central argument is that services firms already employ most of the people they need. “Technology services firms do not have an AI talent shortage; they have a talent decision to make,” George said, adding that clients are shifting from paying for hours to paying for outcomes, which changes how work is staffed and rewarded.

BCG’s analysis, based on more than 2,500 AI-tagged job postings, over 50,000 professional profiles across more than 15 firms and its own skills database, found a stark gap in how AI talent is used:

• Applied AI, meaning building, deploying and running AI-native and agentic solutions in production, accounts for only 10-15% of the AI-tagged workforce at technology services firms, against 90-95% at AI-native companies.
• Nearly half of the applied AI talent at AI-native firms works as forward-deployed engineers who sit close to clients and own results. At traditional services firms, the figure is under 5%.
• Hiring externally into new Applied AI titles can cost up to 35% more than comparable traditional roles.

40 roles, each with a path from today’s jobs

BCG has mapped 40 distinct Applied AI roles, each linked to an existing technology role. A data scientist or full-stack developer can grow into a forward-deployed engineer, a DevOps engineer into an AI Ops engineer, and a data engineer into a semantic engineer. The effort varies: moving a data scientist into a forward-deployed engineer role takes roughly three times the upskilling of moving a data engineer into an AI data engineer role.

The report groups these roles into four actions: buy the scarce anchor roles, build the scale drivers in volume, retain the delivery core and watch the early signals. George estimated that only about 15% of the new roles, such as forward-deployed engineers and digital workforce managers, will need to be hired from outside. The key enabler, according to BCG, is role architecture, with a skill taxonomy, proficiency gates, pay bands and a dedicated job family so that every Applied AI role has a defined title and level.

From pyramid to diamond

The shift also challenges the pyramid structure that Indian IT has been built on, with a wide base of freshers and a thin senior layer. George said workforces are moving towards a diamond shape. Fresher hiring will continue, but firms increasingly expect new hires to be productive and client-facing from day one. She also flagged that outcome-based contracts are still early, with only about 10-15% of deals converting to outcome-linked pricing, and that AI agents carry their own, fast-changing costs.

Competition for this talent is intensifying. Global capability centres employ about 2.5 million people in India, and more than 250,000 already work in AI and machine learning roles, according to George. Most new GCCs set up over the past 18 months have launched with AI centres of excellence from the start, drawing on the same talent pool as services firms.

Why it matters

For India’s IT services industry, the BCG findings frame AI less as an existential threat and more as a race against time. The deep client and domain knowledge built up over years of running enterprise systems remains an advantage, but only if firms redesign roles, career paths and incentives quickly enough to turn that knowledge into AI delivery capacity before AI-native firms and GCCs recruit it away.

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