There’s a widespread fear that big data and AI will “take jobs” from engineers and dispatchers. But practice shows the opposite. Analytics removes routine from people, leaving them what machines can’t yet do: strategic thinking, creativity, making complex decisions in non-standard situations.
A power grid operator used to spend hours collecting data from different sources, compiling reports, analyzing indicators. Now the system does all this in seconds. The operator only needs to make decisions based on ready information. This isn’t profession replacement, it’s liberation from boring work for more important tasks.
Dashboards that visualize station operations in real time have become industry standard. On one screen, an operator sees the capacity of each turbine, equipment status, production forecast for the next hours, current demand, and thousands of other parameters. All of this is presented in clear graphical form, not as endless tables of numbers.
When the system detects a potential problem, it doesn’t just signal with a red light. It shows exactly where the problem is, how critical it is, what possible action options exist. And the final decision is made by a person who considers factors unavailable to the algorithm: on-site weather conditions, repair crew availability, company priorities.
There are excellent examples of human-machine symbiosis. Company engineers receive AI notifications about equipment operation anomalies. They go on-site, check the physical condition, decide on repair necessity. AI doesn’t replace their knowledge and experience, it just directs attention where it’s needed most.
Moreover, big data creates new jobs. Specialists in data analytics, system integration engineers, cybersecurity specialists, data scientists who understand energy specifics are needed. These are high-paying positions requiring deep knowledge and continuous learning. Energy is becoming a high-tech industry, not just “equipment maintenance.”
