How Trust Helps Managers Balance Speed And Ethics In AI Deployment

My flight landed in Budapest eighteen hours before the talk. This was enough time to review my notes, go for a walk to check on the local scene and try to get some sleep despite the struggle with the time zone change. I left the hotel, turned left and headed to Szabadság-szobor, the Liberty Statue, nestled on top of a hill overlooking the Danube River. The monument originally celebrated the city’s liberation from the Nazi occupation during the Second World War with an austere style that echoes the years of Soviet domination behind the Iron Curtain. The views were magnificent. The sun was setting behind the hilly Buda side, casting beautiful yellow shades over Pest. Buda and Pest, two sides of a city separated by the river. A perfect metaphor for AI deployment: the duality of speed and progress contrasted with responsible and ethical use. How trust could reconcile both was going to be at the center of my talk the next morning.

Enterprise AI adoption is accelerating. The International Energy Agency estimated that major technology companies’ capital spending would rise 75% in 2026 to approximately $715 billion. Its satellite tracking found that AI data center capacity more than tripled in the eighteen months until April 2026. Inside companies, adoption is intensifying. In August 2026, OpenAI reported that its top enterprise customers generated 8.3 times as much output per active user as typical customers.

The way companies use AI is also changing. At first, the system supported individual tasks, such as summarizing texts or drafting memos, and a person stayed close to the work. Users then moved to using the technology to write code and, in parallel, embed AI into business workflows for decision support. Today, AI agents complete complex tasks and, with each step, more authority gets delegated.