Set that against the technology itself. A more capable frontier model arrives every few weeks, clearing benchmarks that once seemed insurmountable. We estimate that 93% of U.S. jobs are already exposed to AI-led change, a level we had forecast for 2032.
The raw capability available to any company has multiplied many times over within a single budget cycle, yet the share of organizations converting it into value has barely moved. This gap, what I call “the AI velocity gap,” between how fast models advance and how slowly skills, organizational design, and governance adapt, is widening, not closing.
Closing this gap is a trillion-dollar growth opportunity not just for companies in the IT services industry but for the entire economy: closing the gap between what AI can do and what it delivers.
The opportunity runs on two engines. The first engine runs on work companies already pay for, now done in entirely new ways, such as modernizing systems, writing software, and running operations with AI and agents alongside our people. Call it the old work, reinvented. Yes, it is deflationary by nature. AI compresses the hours and cost of work our industry has billed for decades, but that same compression is what lets us deliver more value, faster than ever before. At Cognizant, nearly 40% of our code is already written with machine assistance, freeing our teams to take on the higher-order work that clients value most.
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