This September 2021 archive article examined where AI could fit into everyday enterprise software. Its examples were tied to operational decisions: what to stock, when to service equipment and how to plan work.
The seven areas were sales forecasting, warehouse planning, production planning, predictive maintenance, financial management, recommendations and talent management. Several depend on the same foundation: consistent historical records connected to an operational workflow.
A forecast is useful only when someone can act on it. Inventory suggestions need purchasing constraints; maintenance alerts need an inspection process; recommendations need a way to measure their value. The original article presented opportunities for applying AI. It did not demonstrate that adding a model would automatically improve every enterprise system. A bounded use case and a measurable outcome provide a more useful starting point.
Published in March 2021, this archive overview described machine learning as one response to the operational changes of the pandemic. It focused on healthcare, finance, media, retail and manufacturing.
The original November 2022 explainer introduced three terms often grouped together under artificial intelligence: narrow AI, general AI and superintelligence. They describe different levels of capability, rather than three interchangeable labels for the same technology.
Our October 2022 industry overview looked at five areas exploring machine learning: healthcare, transport, finance, retail and property valuation. Each used prediction or pattern recognition, but with very different data and consequences for mistakes.
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