AI in audit: where automation changes the economics of the engagement
Audit AI already drafts papers and scans ledgers. Managing partners must know which procedures it truly transforms and how to reprice engagements.
Perspectives
Analysis and perspectives from our partners on the trends, disruptions, and opportunities facing global enterprises.
Audit AI already drafts papers and scans ledgers. Managing partners must know which procedures it truly transforms and how to reprice engagements.
Agentic AI is moving from pilot to purchase order. A framework for CPOs on where to grant autonomy, where to withhold it and how to earn it.
How a growing company can deploy AI agents against specific workflows in sales, service and operations, and measure the result before it hires.
Most AI disappointments are process and data problems in disguise. Here is what a COO should repair first, and in what order.
Labour costs are rising and most UK sites remain barely automated. A benchmark and checklist for COOs deciding between robots-as-a-service and ownership.
Which interactions should stay with human agents once AI is in the flow, where those agents should sit, and how to contract for loyalty, not deflection.
When software agents perform routine work, someone must own each one. The roles, decision rights and controls a CHRO should define before agents scale.
The high-risk deadline has moved to December 2027, but deployers still carry duties today. A practical plan for CIOs, built on an AI inventory.
AI compresses the reading, not the judging. Evidence from Deloitte, McKinsey and Stanford on where deal teams gain speed and where people must stay in charge.
AI is compressing the price of hours. A CEO's guide to the shift from people-based advice to software, data products and managed services, and how to make it pay.
With deals needing faster growth to hit target returns, buyers now price the cost to modernise. Here is what technology and cyber findings change, and how sellers prepare.
Open-source tools have removed the licence fee for marketing mix modelling. The harder questions for a mid-market CMO are data, expertise and decisions.
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