I believe the following claims are true, but I cannot prove them. Can anyone provide a proof or a reference?
For any matrix $A$, each entry, $X_{ij}$ of $$ X:=\int_{0}^{T}e^{At}dt $$ can be written as $$ \sum_{k=0}^{K_{ij}}a_{ijk}e^{b_{ijk}T}T^{c_{ijk}} $$ with $K_{ij}<\infty$ and unique, possibly complex, coefficients $a,b,c$. If $A$ is invertible, then $A^{-1}=-Y$, where $$ Y_{ij}:=\sum_{k \text{ s.t. } b_{ikk}=c_{ijk}=0} a_{ijk}. $$
Note that this is easy to show if $A$ is diagonalizable or if the spectrum of $A$ is strictly contained in the left half plane.
More generally, I believe the constant term of $$ \int_{0}^{T}e^{At}Ce^{Bt} dt $$ solves the Sylvester equation $$ AY+YB=C $$ whenever a unique solution exists.
The result you give is not exact (see last equation). In fact if $A$ is a scalar ($1 \times 1$ matrix) :
$$ \text{if} \ A=a, \ \ \int_0^T\exp(ta)dt= T+\tfrac12T^2 a +\cdots \tag{1}$$
And in the general case :
$$\int_0^T\exp(tA)dt= TI_n+\tfrac12T^2 A+\cdots \tag{2}$$
Here is a proof of (2) in the case where $A$ is diagonalizable :
$$A=P\Lambda P^{-1} \ \ \text{where} \ \ \lambda=diag(\lambda_1\cdots \lambda_n)\tag{3}$$
Equivalently :
$$tA=P (t\Lambda) P^{-1} \ \ \text{where} \ \ t\Lambda=diag(t\lambda_1\cdots t\lambda_n)$$
Therefore :
$$\exp(tA)=P M P^{-1} \ \ \text{where} \ \ M=diag(e^{t\lambda_1},\cdots e^{t\lambda_n})$$
$$\int_0^T \exp(tA)dt=P N P^{-1}\tag{4}$$
with
$$N=diag(\int_0^Te^{t\lambda_1}dt,\cdots \int_0^T e^{t\lambda_n}dt)$$
$$N=diag(\frac{1}{\lambda_1}(e^{\lambda_1T}-1),\cdots \frac{1}{\lambda_n}(e^{\lambda_nT}-1))$$
$$N=\Lambda^{-1}(\exp(T\Lambda)-I_n)\tag{5}$$
Plugging (5) into (4) :
$$\int_0^T\exp(tA)dt=P \Lambda^{-1}(\exp(T\Lambda)-I_n) P^{-1}=P \Lambda^{-1}(T\Lambda+\tfrac12T^2 \Lambda^2+\cdots) P^{-1}$$
giving (2).