Traditionally, 1) we start with big, established companies in tech. 2) A few people, dissatisfied with the trammels that big companies place on their employees, leave, found a new company, and then, 3) through superior grit, gumption, execution, flexibility, and speed, steal market share from the big companies. As the new company grows, 4) it accumulates organizational scar tissue and is slowly infiltrated by incompetent careerists, and finally, 5) becomes the very company that the founders set out to create.
We've been going through this cycle since the late 1950s, when the "traitorous eight" left Shockley Semiconductor Laboratory to found "Fairchild Semiconductor".
Machine learning might stop this cycle by breaking step #3. Big companies have access to huge data sets that no group of human developers, no matter how talented, can match. Even slow, hidebound, and barely-competent use of these data sets can squash upstart smaller companies.
It'll be like a planet, full of water and life, with a core that cools to the point where it can no longer sustain plate tectonics. Without constant replenishment, the crust seizes up, the oceans boil off, and the life dies. The tech industry will become Mars.