In 2026, AI will rewrite the 'Industrial OS': Three shifts in hegemony
a16z's 'Big Ideas 2026' presents the perspective that AI is not just a 'convenient feature addition,' but a force that will redraw the blueprints of industries themselves. The video presents three changes: (1) an industrial foundation that 'moves the physical world' through electrification x AI, (2) the renewal of legacy banking and insurance, and (3) the shift in dominance of enterprise software from 'record' to 'execution.' Here, I will break down the technical jargon and organize where the true points of disruption lie, along with concrete examples.
1. Electrification x AI reshapes 'manufacturing and energy'
1-1. What is the 'electro-industrial stack'?
Ryan McEntush says the next industrial revolution will not happen in the appearance of factories, but in the 'internal components' that move machines. The 'electro-industrial stack' is the 'invisible foundation' that supports EVs, drones, data centers, and modern manufacturing by integrating batteries (energy storage), power electronics (power control), motors (drive), and computing resources (compute) with software and AI. a16z's explanation is clear: it refers to a state where the physical world 'begins to behave like software.'
1-2. It is 'supply chains,' not 'technology,' that determine victory or defeat
What is important is not the accuracy of models or robot demos, but the end-to-end process from minerals to components, assembly, and mass production. a16z sounds an alarm, stating that 'the power to build this stack, from refining critical materials to manufacturing advanced chips, is being lost,' and notes that this is directly linked to national industry and security. The closing phrase, 'Software ate the world. Now it will move it,' is symbolic.
2. Banking and insurance: From 'adding AI' to 'rebuilding the OS'
2-1. The 'risk of not changing' outweighs the 'risk of changing'
Angela Strange organizes the reason why a turning point will come in finance and insurance in 2026 as being because 'there is a limit to layering AI on top of legacy systems.' Specifically, data is scattered across aging core systems, and there is no unified data layer to leverage AI. The outlook is that major institutions will stop renewing long-term vendor contracts and begin shifting to AI-native alternatives.
2-2. What will change? (A world where loan screening is 'parallelized')
a16z summarizes the changes in three points.
Business becomes parallelized: From a world of switching back and forth between screens to copy and paste, agents can now list 'hundreds of tasks,' such as mortgage screening, and process simple tasks first.
Categories are integrated: Onboarding KYC, transaction monitoring, and the like are consolidated into a single risk foundation.
Winners become 10x larger: Software absorbs manual labor, and the market expands ('software market is eating labor').
In other words, the main battlefield for fintech is shifting from 'convenient UI' to 'data integration and execution engines (business OS)'.
3. Enterprise: From 'Systems of Record' to 'Dynamic Agent Layer'
3-1. Why the value of 'recording boxes' is falling
Sarah Wang's argument is that 'systems of record' (the core of records: ERP/CRM/ITSM, etc.), which have held hegemony in enterprise software, will begin to step down from the leading role in 2026. The background is that AI collapses the distance between 'intent' and 'execution.' When models can read and write business data, reason, and autonomously execute workflows, a 'dynamic agent layer' stands in front of the UI, and the record layer is described as approaching 'cheap persistent storage.'
3-2. Concrete example: ITSM from 'application reception' to 'immediate resolution'
ITSM (IT Service Management) is a domain that handles internal access requests, incident response, change management, etc., and ServiceNow defines ITSM as 'end-to-end management of IT service delivery.'
When an agent enters this space, it can extract intent from a user's request text, map it to the appropriate procedure, and shorten the time to execution. Furthermore, 'operational automation' is spreading to the SRE domain, and Reuters has reported on Resolve AI as a company with a direction of 'autonomously troubleshooting production incidents.'
Traversal also positions itself as an 'AI SRE,' advocating for alert noise reduction and root cause identification and recovery guides.
4. Checklist for 2026
The 'winning strategy' common to all three industries is simple.
Is the data unified?(AI won't grow if you just layer it on top of silos)
Can you shorten the path from intent to execution?(Can you eliminate the human hell of endless clicking?)
Can you design it to include the supply chain and the front lines?(Mass production and operation, not demos, are the real deal)
The disruptive power of AI is determined not by 'which industry will grow,' but by 'which layer (foundation) it reshapes.' 2026 is likely to be the year when that 'reshaping' surfaces all at once.
