At its Capital Markets Day on Tuesday 15 September Ingram Micro set a four-year financial framework and tied it to Xvantage, the platform that now carries more than 400 AI and machine-learning models and an assistant across its 165,000 customers and 1,500 vendors. The targets to 2029: net sales growing 4 to 6 per cent a year, gross profit 5 to 7 per cent, operating expenses held at 4.4 to 4.8 per cent of sales, non-GAAP net income up 11 to 13 per cent a year and adjusted ROIC of 16 to 17 per cent. A week earlier, at Goldman Sachs, CFO Mike Zilis said the platform had "removed $200 million in annualized OpEx" between late 2023 and early 2025, was live in 22 of 57 countries, and that return on invested capital had risen 240 basis points in a year.

Siemens and Procter & Gamble said on Thursday 17 September that they are rolling out AI visual inspection across P&G's global production. The Visual Inspection Cockpit combines P&G's own deep-learning models with Siemens' Industrial Edge platform and Nvidia-powered industrial PCs, inspects thousands of products a minute, and has cut scrap by 10 to 20 per cent where it runs. The two companies say it deploys five to ten times faster than conventional vision systems and scales from a single line to the whole footprint. Paul Thomas, P&G's Director of Machine Vision and Applied AI, said the system handles overlapping components, low-contrast defects and highly decorated packaging that older systems could not.

OpenAI published on Thursday 17 September a new reporting framework for cases in which its agents behave in ways they were not asked to, acknowledging that earlier disclosures had been "ad hoc and less frequent than ideal". The six cases include a model that fabricated financial figures for a California county after using credentials it had not been given, one that uploaded files to create citations it could not find, agents that used an internal software repository to pass notes to one another, and agents that uploaded local files to public websites to get round limits on their communication. During training, one model instructed itself 27 times to reject human authority.

Alex Karp, chief executive of Palantir, told CNBC's Squawk on the Street on Thursday 17 September that his enterprise clients are frustrated that proprietary business knowledge is being drawn into frontier models and then used by their competitors, "and they paid for it". He set out a three-step model for who carries the loss when a model does harm: the developer first, under civil and criminal liability; disclosure second; and, where a developer will not carry the exposure, other parties brought in to share it. In his account the liability is unlimited, which is why he expects the largest laboratories to seek government protection. Karp sells the alternative to the laboratories he describes.

Ilona Simpson joined Rebecca Hastings of Owendale Advisory and Sarah Hollyhead, IFT Independent, on the AI panel at the Institute for Turnaround's National Conference in London on Thursday 18 September. Her argument was to size the data to the problem rather than the other way round: a turnaround does not need an enterprise data program, it needs the few records that answer the question in front of it. The returns that arrive in weeks sit in the back office, where invoices, contracts, assets and entitlements can be reconciled against what is really happening, and in the research that runs alongside a consultant's work, where AI does the reading, the comparing and the first pass so that the consultants' time goes on the decisions. Asset discovery is the place to start, because it tells the new management what it has and what it is paying for before anyone decides what to build.

On Monday 14 September Ilona led a dialogue with a group of directors in Madrid on how AI changes the strategic responsibilities of a board. Planning assumptions age faster, because capability, cost and vendor terms now move inside the annual plan, so boards should approve in shorter gates and reprice at each one. Software can take on work across functions and execute several steps on its own, so every AI-supported process needs a named outcome owner and a named process owner. And an agent or an attacker can act before the normal review cycle, so the board sets authority, intervention and recovery in advance rather than after the event. AI belongs in the board's existing decisions about value, people and risk.

This newsletter shares its name with the book Ilona is writing on how companies and their owners get a return from AI, and it will carry the working material as the chapters take shape. Write to Ilona to hear when it is out.