TLDR: J.P. Morgan’s latest analysis suggests that generative AI must boost IT services workloads by more than 55% to offset significant project cost deflation. The firm projects substantial cost reductions from AI-driven automation in coding, necessitating a corresponding increase in work quantity to maintain net revenue.
A recent note from J.P. Morgan indicates that generative artificial intelligence (GenAI) is poised to dramatically reshape the IT services landscape, requiring a more than 55% acceleration in work output to counteract the deflationary pressures on project costs. This projection comes as the financial giant assesses the profound impact of AI on productivity and pricing within the sector.
According to J.P. Morgan’s analysts, the automation of coding tasks by large language models (LLMs) could lead to an approximate 35% reduction in overall project costs on a like-for-like basis. This estimate is underpinned by an anticipated 90% deflation in routine coding, which currently accounts for about 40% of a typical project’s full-time equivalent (FTE) hours. Further cost reductions are expected in areas such as documentation and testing, while functions demanding higher-level reasoning, like requirements analysis and architecting, are projected to experience less price compression.
However, the report also highlights new tasks that will partially offset these deflationary effects. Prompt engineering, a newly introduced discipline, is expected to account for 15% of pre-AI project costs, or 23% of post-AI project composition. Additionally, code review is anticipated to double in its share of work, driven by the critical need for oversight of AI-generated code. Debugging, a task that GenAI can both automate and complicate, is assumed to remain cost-neutral.
J.P. Morgan’s calculations, based on a price-times-quantity model, underscore that if prices fall by 35%, a minimum 55% increase in work quantity is essential to prevent a loss in net revenue. The firm’s report outlines various combinations to achieve this threshold, including a 25% increase in both project volume and complexity.
The analysts express confidence that the adoption of generative AI is on track to surpass this 55% workload increase. This optimism is rooted in historical patterns where enterprises have consistently reinvested cost savings from prior technological shifts, such as cloud computing and offshore delivery, into new technology initiatives. Early indicators, including a reported 3% revenue lift by Genpact from clients utilizing agentic solutions, suggest a similar reinvestment trend is already underway.
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Broader industry trends support this outlook. A McKinsey Global Survey on AI revealed a significant jump in AI adoption, with the proportion of companies using AI in at least one business function rising from 55% in 2023 to 72% in 2024, with an even greater surge in generative AI usage. The global AI market is projected to reach over $1.8 trillion by 2030, with global spending on generative AI alone expected to hit $644 billion in 2025, marking a substantial 76.4% increase from the previous year, according to Gartner estimates. These figures underscore the rapid integration and transformative potential of AI across various sectors.
