Here's a bunch of data points from what looks like exponential growth:
Looks nicely convex, and that red curve is an actual exponential fit to the data,
\[
y = 0.0057 \, \exp(0.0977 \, x) \qquad [R^2 = 0.971].
\]
Model explains 97.1% of variance. I mean, what more proof could one want? A board of directors filled with political apparatchiks? A book by [a ghostwriter for] a well-known management speaker? Fourteen years of negative earnings and a CEO that consumes recreational drugs during interviews?
Alas, those data points aren't proof of an exponential process, rather, they are the output of a logistic process with some minor stochastic disturbances thrown in:
\[
y = \frac{1}{1+\exp(-0.1 \, x+5)} + \epsilon_x \qquad \epsilon_x \sim \text{Normal}(0,0.005).
\]
The logistic process is a convenient way to capture growth behavior where there's a limited potential: early on, the limit isn't very important, so the growth appears to be exponential, but later on there's less and less opportunity for growth so the process converges to the potential. This can be seen by plotting the two together:
Ironically, knowledge is one of the few things that shows a rate of growth that's proportional to the size of the [knowledge] base. Which would make knowing stuff (like the difference between the convex part of an s-shaped curve and an exponential) a true exponential capability.
But that would require those who talk of "exponential economy" to understand what exponential means.