Primum non nocere[1]
KPMG, one of the world`s largest auditors of private and public entities, manages to cut its own audit fees for total 2025 by 14% with AI – an efficiency delivered by its long-term partner Grand Thornton UK. Many of the KPMG` clients, however, are now demanding that these cost savings are now passed on to them[2].
Despite such early tangible success stories, AI is not yet a guarantee of seamless cost reduction. In 2025, the Australian government received partial compensation for a Deloitte report after discovering significant errors – false references and fabricated academic citations – caused by an AI use (Azure OpenAI GPT-4o) during the draft creation[3].
Overall, top corporate performers are shifting focus from efficiency to velocity, trying to scale agentic AIs. Companies are prioritizing AI investments above cybersecurity and broader technology modernization. Velocity is emerging as the new competitive advantage. “Moving fast is the only way to capture innovation at scale”[4]. With these developments, “price of everything” could decline over the long term as output and efficiency rise.
A macroeconomic lens on the labor market is essential. Prof. Anton Korinek of the University of Virginia argues that the key difference in this technological wave is that labor is no longer scarce[5]. As he notes, “there is no economic law that implies technology always creates new jobs”. During the industrial revolution, the scarcity of human labor was the engine behind rising living standards over the past two and a half centuries. By contrast, the age of AI technology – evolving from 2010 early versions of narrow Deep learning into autonomous AI agents in 2025 – introduces the possibility for partial task to complete job displacement. In this new era, labor could be reproduced and automated, with technology potentially becoming “to the workforce what an asteroid did to the dinosaurs”[6].
Labor market is a dynamic equilibrium between demand and supply. Some forward-looking scenarios explore the possibility of a structural shift toward “cognitive obsolesce”, where the relative value of physical work temporary increases. In simulations with exponential total growth of output, wages initially rise due to higher productivity. Yet, once a critical threshold is reached – around 80% automation in the model – wages collapse while return on capital surge. This dynamic might lead to significant redistribution and rising inequality, as the lower “price of everything” may still exceed wages in relative terms.
Our modern Meander[7] focusses on managing and steering this transition, ensuring a fair distribution between major winners and losers. Macro-systems such as taxation, pensions and healthcare will require substantial redesign, as the primary source of public finance shifts from labor income to consumption and eventually to capital. Non-economic values – as meaning, agency and dignity – must also be considered. Human experiences of uncertainty, inequality, resources constraints, and accelerating pace of change deserve equal weight alongside technological breakthroughs when evaluating long-term progress.
[1] “First, do no harm”, Hippocrates
[2] KPMG forced Auditor for a 14% AI Discount…Will the \”Billable Hour\” die?, 12 February 2026
[3] Deloitte\’s AI Fallout Explained: The $440,000 Report That Backfired, 8 October 2025
[4] McKinsey Global Tech Agenda 2026, How CIOs are shaping enterprise strategy and growth | McKinsey, 9 February 2026
[5] Scenarios for the transition to AGI, Korinek, A, Suh, D. March 2024
[6] Tyrangiel, J. America isn`t ready for what AI will do to jobs, The Atlantic, 10 Feb 2026
[7] Greek key symbol that represents eternal motion of things, the labyrinth path of life
