How can a PhD in Machine Learning and AI help you in a life out of Academia? I have applied for a Ph.D. in Computer Science. I do not, however, plan to become an academic afterward. What I want to achieve is to try to commercialize my research by founding a startup or find a job outside of Academia, using the knowledge I will obtain for enhancing or building products/services for my employer.

What I would like ideally, is to achieve Academic as well as Industry expertise in machine learning and AI, through a job or by trying to found a startup with a related thematology. Becoming a professor is completely out of my goals. However, I want to be able to study academic literature with ease.

Do you think my goal is reasonable, or a Ph.D. is an overkill that would make me overqualified, losing precious time in case I change my mind in the future?

The reason I want the Ph.D. is to learn more things and receive more hands-on experience in Machine Learning. I believe that this process will also enhance my critical skills and analytical thinking.

I understand this can get difficult and risky but I am willing to try.

Does my goal make any sense or do I need a reality check? I need a hard critique...
Is that a healthy reason for attending graduate school?
Working at your startup

One thing for sure is that, if you want to start a company (a startup), you should not be afraid of being overqualified, since you will be "the boss" and there is no one to classify you as such.

Working in the industry

While being overqualified sometimes (perhaps, even, often) applies to positions in the industry, a Ph.D. graduate is highly unlikely to be considered as such in ML/AI domain, where it is often a requirement for most positions.

Working for other people's startup

Even though most startups generally don't care about degrees, those, working in ML/AI-related domains, will be happy to consider and hire a good Ph.D. graduate for the obvious reason: due to relatively high complexity of the required ML/AI-related subject domain expertise.

P.S. Please note that my answer addresses only your concern of being overqualified, but does not touch a larger question of feasibility of your plan, factors to consider in decision making and so on. However, it implicitly suggests that this one of possible routes to achieve your goal (whether it's the best or the optimal one, depends on a lot of factors, including your personal circumstances).