Depends heavily on the use case. Indeed many tasks humans carry out are done without touch feedback - but many also require it.
An example of feed-forward manipulation is lifting a medium-sized object. Classic example is lifting a coffee cup. If you misjudge a full cup for empty you may spill the contents before your brain manages to replan the action based on sensory input. It takes around 300ms for that feedback loop to happen. We do many thing faster than that would allow.
The linked article has a great example of a task where a human needs feedback control: picking up and lighting a match.
Sibling comments also make a good point on that touch may well be necessary to learn the task. Babies do a lot of trial-and-error manipulation and even adults will do new tasks slower first.
The industry's approach to "trial and error to learn the task" is to have warehouses of robots perform various tasks until they get good at them. I imagine that you'd rely on warehouses less once you have a real fleet of robots performing real tasks in real world environments (and, at first, failing in many dumb and amusing ways).
Robots can also react much faster than 300ms. Sure, that massive transformer you put in charge of high level planning and reasoning probably isn't going to run at 200 tokens a second. But a dozen smaller control-oriented networks that are directly in charge of executing the planned motions can clock at 200 Hz or more. They can adjust fast if motor controllers, which know the position and current draw of any given motor at any given time, report data that indicates the grip is slipping.