Obviously, just watching every video in real-time a single time is not an adequate review process. Things can be missed, misunderstood, or just take more time to process, so it is likely that more review would be necessary for non-obvious cases. But, on the other hand, it is not necessary to review literally every second of every video. If they only reviewed reported videos and reports were required to specify the timestamp, they would probably instantly reduce this total burden by a factor of 10x-100x (assuming they filter out obvious spam reports). This would allow them to allocate more independent reviewers to the actual non-obvious cases resulting in reasonable accuracy with a human appeals process while reducing their overall cost burden significantly lower than the previously stated ~50%. They could then tier their review process based on the amount of views to allowing them to limit how many resources they spend on unpopular and irrelevant videos to focus on more visible and profitable videos while still providing a base level of review. And, all of this is assuming that they do not have any automated mechanism to directly decide on cases that are trivially obvious, thus reducing their burden even lower to only the contentious cases where the automated systems can not create a clear-cut answer. Frankly, I could go on about various other potential mechanisms they could do to reduce costs while increasing efficiency and avoiding bad actors, but what I have already said should already be sufficient to handle the basic problem.
All in all, they could probably institute a reasonable human review process that could handle all reasonable cases for <5% of yearly revenue and frankly I would be shocked if it were anywhere near the high end of that estimate. Even without any automated systems I would put my median cost prediction at 1% of yearly revenue and with even basic automated systems probably close to 0.2%.