We have seen a transformation over the last 30 years from an economy dominated by demand to the one dominated by supply. Symbiotic autonomous systems are likely to stay in the same path of increasing the supply against a demand that is growing at a slower pace.
Clearly different market sectors show different unbalances, with few geographical areas and market sectors showing a demand that exceeds supply but in general, and in particular in the technology area, this is the case. Even though the Moore’s law has come to an end the variety of technologies available will continue to create an oversupply. There are some predicting an energy gap between supply and demand but I don’t believe that is going to be the case, given the advance in power production. In the last decade we have seen a decrease in price of oil, an indicator of oversupply, and although the expectation is for an increase in energy demand (40% increase by 2040) the availability of renewable should provide more than enough supply at global level, although the price of oil is expected to increase by 2040 to the peak level experienced in the past decade (this estimate may actually be wrong if electrical vehicle will replace fossil fuel ones).
Symbiotic autonomous systems will clearly create a demand for innovation and for technology advance but they will keep evolving based on technology that is available, that is, I do not see a crises looming ahead hampering their evolution because we are lacking needed technology.
The symbioses is likely to provide increasing value thus, in a way, increasing the supply side. Again, there will be niches where demand will exceed supply (particularly in the coming two decades for human machine symbioses for human augmentation widening the gap between the have and have-not).
Autonomous systems, in particular robots, are already having an economic impact in levelling the cost of production across the world. After decades of offshoring the production to places with lower labour cost we are starting to see the first signs of in-shoring. Thanks to their flexibility, boosted by deep learning (for perception and situational awareness) and machine learning algorithms, they can have a much longer life cycle, hence their cost can be partitioned over longer period of production cycles. Increased flexibility in machine to machine interaction exploiting artificial intelligence makes it possibile to sustain Industry 4.0 paradigm of advanced cooperation and distributed manufacturing. In turns this can lead to business disruptions since it favours a reshuffling of the whole value chain.
The symbiotic relation may also lead to a revisitation of business models (in particular in relation to energy exchange among autonomous systems and accountability aspects) but it is still to early to grasp in its full economical implications.
Finally, the adoption of symbiotic autonomous systems is likely to take place in different market sectors at different times in different Countries. In many cases, particularly those of huge manufacturing plants (like Foxconn) is going to be very capital intensive and can be sustained only through high production volumes. Hence the deployment of autonomous systems may happen first in big companies that can afford them and in turns will strengthen their market position thanks to the greater resulting efficiency. A different scenario, more in line with the disruption of Industry 4.0, may result from the adoption on a much smaller scale of autonomous systems for limited production in specific markets that over time will loosely aggregate with others achieving scale and chewing on the market quota of big companies. This will require a significant re-thinking of the value chains and of the logistic glue among players.