AI ROI cannot be calculated solely by measuring output speed. It involves organizing, implementing, and maintaining costs, manual verification, value of production capacity, and cash benefits. Using hypothetical calculations to illustrate net ROI and conservative scenarios helps companies determine whether to continue, adjust, or stop.
Trump AI is renamed SI, which refers to the US administration’s adjustment of official terminology. The White House issued an executive order on September 29, 2026, requiring that within the limits permitted by law, the name of the AI system be changed to Super Intell…
AI risk assessment involves organizing the purpose, users, data, models, output impact, and accountability of an AI application into evidence, and then determining potential harms, conditions of occurrence, degree of impact, and mitigation measures. The output of the assessment is not just a high, medium...
Generative AI usage guidelines are not a "do not use" list. Instead, they organize what the company allows, what cannot be inputted, who reviews the output, and how to report issues into common, actionable rules for employees. Good guidelines must both reduce the risk...
Just because people in the company are already using AI doesn't mean the company knows how to manage AI. When customer service uses it to organize complaints, marketing uses it to generate copy, and operations uses it to analyze data, the real question that needs to be answered is not "can we use it," but who approves its use, …
The AI ad delivery discussed in this article includes scenarios where platforms use automation to assist with bidding, audiences, placements, budget allocation, and creative combinations. This does not mean businesses can hand over their ad accounts to the system and stop managing them. The system will, based on the received goals…
The core of preparing for AI adoption is not buying tools first, but confirming that the enterprise has clear problems, legally usable data, processes capable of receiving the output, actual people in charge, as well as permissions, human review, and risk governance. Without these foundations, tools can...
The purpose of an AI PoC is not to prove that AI can generate a piece of text or recognize an image, but to reduce the uncertainty of whether a company should invest in the next phase. A good AI PoC starts from a specific problem and establishes the current state...
Companies know that AI can be useful, but they do not necessarily know whether to choose use cases first, organize data, purchase tools, or go straight to a development team. At this point, the value of an AI consultant is not to help companies chase every new model, but to help turn vague expectations...
