Artificial intelligence, applied to the business
Long-form guides with no filler on what an AI project in a company actually costs, how long it takes and what it delivers. Every article is written by someone who ships these systems in production, and every figure we quote links to its original source (McKinsey, Stanford HAI, MIT, Gartner, BCG, the World Economic Forum) so you can verify it rather than take our word for it.
AI Agents for Business: What They Are, How They Work and Real Use Cases
What AI agents for business are, how they differ from chatbots and RPA, how they work and which use cases already run today. With sources cited from Gartner.
How to implement AI in a company: a step-by-step guide
How to implement AI in a company, step by step: pick the process, audit data, prototype, production, governance. Cited sources: MIT, Gartner, BCG, McKinsey.
AI process automation: 10 processes your company can automate today
AI process automation: 10 concrete processes, what each one gains and what it does not fix. With cited sources from NBER, Science, the OECD and the U.S. Census.
AI for business: 15 use cases with real impact on the numbers
AI for business: 15 use cases by function, with the expected impact of each one and how solid the evidence behind it really is. Sources cited throughout.
How to calculate AI ROI on a real project
How to calculate AI ROI: freeze the baseline, count the full cost, value the benefit, and run a worked example step by step. Every figure has a cited source.
AI implementation cost: what an AI project really costs
An honest breakdown of AI implementation cost: data, build, inference and maintenance. Public reference ranges, what they hide, and every source cited.
AI cost reduction: 10 processes where your company can create real efficiencies
AI cost reduction: 10 processes with measurable efficiencies, the mechanism behind each saving and how to tell it apart from freed capacity. Sources cited.
AI agents for sales: automate prospecting, follow-up and quoting
A practical guide to AI agents for sales: prospecting, speed-to-lead, qualification, follow-up and quoting. With sources cited from McKinsey, NBER and more.
AI agents for customer service: from the traditional chatbot to the intelligent agent
AI agents for customer service: why decision-tree chatbots failed, what changes with agents that execute real actions, and how to measure them. Sources cited.