Knowing how to set tasks, assess answers, verify sources and improve workflows are the key skills for working with artificial intelligence, according to Ekaterina Lisovskaya, who leads AI service development for the mobile app at asset manager Alfa-Capital.

Neural networks can be given jobs such as gathering information, drafting texts, preparing meeting minutes and comparing documents, she said. But the request should not be vague: it helps to specify the audience, the time period, the sources and the desired structure.

Professional expertise matters because it lets a person judge whether a model's answer actually applies, Lisovskaya noted. Checking dates, the origin of figures and contradictions is a separate task in its own right.

She also suggested auditing your own week to spot repeated actions - searching for information, writing routine emails, consolidating tables, taking minutes, moving data between systems. Start with one process where the cost of an error is low, and decide in advance how the result will be checked. The payoff should be measured by time saved, quality of output and the number of corrections needed.

Both refusing to use the technology and treating a model's first answer as a finished solution get in the way of professional growth, she added.

Source: RIA Novosti