The way "data quality" is being talked about is wrong, it misses important points about the problem of data in real world AI projects. My view is that the largest room for improvement in model accuracy is not in the either/or of algorithm / data "quality".
When should the question of algorithms come up in AI projects? AI algorithms do a lot of useful things. We look into the basics of algorithms here, what they do, their advantages and drawbacks and consider to what extent they will solve your problem.
Public hype about AI algorithms doing everybody's work for them, doomsday predictions of AI taking over humanity, AI is talked about as if the algorithms had agency. They don't. AI doesn't do what a lot of people pretend it does.