Resources
Assessment, use cases, return on investment, maturity, AI agents: the questions boards, CIOs and business leaders ask, answered without jargon.
Enterprise AI assessment: what it delivers and how to judge it
An enterprise AI assessment shows where AI will save your teams time, with numbers: a map of the work as it is really done, quantified use cases ranked by value, and a roadmap. Two weeks is enough for a focused scope, as long as the figures come from the field and not from a workshop.
AI use cases in business: how to find and prioritise them
A good AI use case is a repetitive, frequent task, fed by accessible data, where a mistake costs little. Rank candidates by scoring impact, feasibility and cost, then set aside any whose risk is too high.
ROI of an AI project: how to calculate the gain and the payback period
To calculate the ROI of an AI project, value the hours actually freed (hours × fully loaded hourly cost), subtract build and running costs, then set the net gain against the cost. The payback period, in months, is the figure a committee reads first; it holds only if every assumption is written down.
Enterprise AI maturity: the four tiers and how to place yourself
An organisation’s AI maturity reads on four tiers, from ad hoc use to an AI-native operating model; your tier is the one your practices demonstrate, not the one your intentions announce. Moving up takes a few precise decisions, not more tools.
Enterprise AI agents: use cases, limits and human validation
An enterprise AI agent pursues a goal: it picks its own steps, uses your tools and acts, where an assistant only answers. It pays off on repetitive, high-volume tasks, provided an expert reviews and signs every result before it is delivered.