Tech services firms face $200 billion AI opportunity, but talent gap threatens growth: BCG

Technology services companies could tap a $100-200 billion opportunity in artificial intelligence (AI)-led services by 2030, but their ability to capitalise on the growing market will depend on how effectively they retrain existing employees, rather than relying heavily on external hiring, according to a new report by Boston Consulting Group (BCG).

The global services market is projected to expand from $1.6-1.7 trillion in 2025 to $2.2-2.4 trillion by 2030. AI-led services are expected to contribute $300-400 billion to this growth, although around $200 billion in existing revenue contracts could be displaced by AI-driven efficiencies, leaving a net opportunity of $100-200 billion, the report said.

Applied AI talent remains limited

BCG's analysis of more than 2,500 AI-tagged job postings and over 50,000 professional profiles across more than 15 firms found a significant gap between technology services companies and AI-native businesses.

Applied AI professionals, who build, deploy and operate AI-based solutions, account for just 10-15% of the AI-tagged workforce at technology services firms. The corresponding share at AI-native companies stands at 90-95%. The remaining 85-90% at technology services companies primarily comprises professionals using AI tools to improve existing workflows.

The difference is also visible in client-facing roles. Around 45% of Applied AI talent at AI-native firms works in forward-deployed positions, where teams collaborate directly with clients and take responsibility for delivering outcomes. At technology services firms, such roles account for less than 5% of the Applied AI workforce.

“Technology services firms do not have an AI talent shortage, they have a talent decision to make,” said Sreyssha George, managing director and partner at BCG and a co-author of the report.

Hiring externally can cost up to 35% more

The report identifies 40 distinct Applied AI roles, each of which can be linked to an existing technology job. Data scientists and full-stack developers, for instance, can transition into forward-deployed engineering, while DevOps professionals can move into AI operations.

However, the effort required varies. Moving a data scientist into a forward-deployed engineer position requires roughly three times the upskilling effort needed to transition a data engineer into an AI data engineer role.

BCG estimates that hiring for new AI roles can cost up to 35% more than recruiting for comparable traditional technology positions. It recommends selectively hiring for scarce specialist roles while developing existing employees for positions that can be filled internally.

Clear career paths key to retaining talent

The report calls for companies to establish dedicated AI job families, defined skill requirements, proficiency levels and compensation bands. It also recommends creating five career tracks, allowing employees to progress into technical, research, managerial, product or client-facing roles.

With AI-led services reshaping delivery models and client expectations, BCG said companies need to define roles and provide employees with hands-on experience quickly to capture the opportunity by 2030.