AI Forum Takeaways; Laying 'AI Builder' Bricks To Bridge AI Production Value

Research evidence excerpt

AI Forum Takeaways; Laying 'AI Builder' Bricks To Bridge AI Production Value

ructure may not require the same lift in software).

Demand Steady & Supported By Increasing V2/V3 Deals

Demand commentary was relatively unchanged and supported by cost takeout, AI, and

vendor consolidation efforts. CTSH reiterated its 3-vector strategy to drive growth, including

software engineering reinvention (autonomous, agent-led development increasing throughput

and reducing costs), industrializing AI (enterprise integration layer embedding AI into legacy

systems), and the expansion into operations (AI-driven transformation & management of

business processes).

AI deployments continue to scale and there is increasing demand for bespoke AI solutions,

with a greater number of Vector 2 and Vector 3 deals, now representing 20-40% of enterprise

spending vs 0-10% historically. For example, these areas include agent harness, AI infra, data/

training services, and context/model engineering. The changing composition of enterprise

spending is supportive of sustained AI demand, particularly areas where orchestration is

needed.

Flattening the Talent Pyramid, But Still Growing for Now

Part of the 'AI Builder' strategy aims to move away from its traditional pyramid delivery model

toward a flatter, interdisciplinary workforce integrating tech, ops knowledge, & domain

expertise; the intent is a flatter structure with an agent-augmented workforce. The new structure

would have middle-layer engineers orchestrating human & digital labor in delivery and serving

as 'player coaches' replacing merely coordination.

CTSH is making efforts to train/upskill its workforce for AI fluency and is creating new roles &

job families (such as frontier-certified engineers and business operators) to support this shift.