Re: Presumably they have multiple sources of cooling
The value is probably in predictive analysis - ie trend data to optimise pre-cooling and moving to virtual predictive 'simmerstat' rather than thermostat approach combined with any optimal combination of cooling techniques (free cooling, thermal mass, solar, ice making etc).
'decently tuned PID' - getting the decent tuning is that hard bit - and long an AI application in its own right. You also have to managed a network of the things that add noise and complex interactions. That takes significant investment of domain engineers and is rarely worth it in complex systems (like commercial buildings). You also have to manage context drift on those tuned PID controllers.
There are benefits to be had from explicitly doing the predictive analysis (in some senses a PID controller is a simplistic implicit predictor) and a separate constraint based optimiser. That can be done at the system level and with set point adjustment thus be reasonably robust with badly tuned local controllers.
The interesting bit is whether we have reached the point that this can be done with general tech and general it skills and thus save energy rather than every time being a engineering problem. Its long been possible to improve heating system efficiency and add simple predictive controllers - just rarely has it been a sustainable use of the necessary skills.
In data centers of course getting smart whilst being able to rule out over set point overshoot is probably worthy of study all in its own as staying with the thermal design parameters of the kit is rather important ...