When ## a ## is just a real number, one can use a Taylor series to represent ## e^{at} ## as
## e^{at} = \sum_{n=0}^{\infty} \frac{(at)^n}{n!} = 1 + at + \frac{1}{2}(at)^2 + \ldots ##
By analogy, one can define the exponential of ## \mathbf{A}t ##, where ## \mathbf{A} ## is now a matrix, as
## e^{\mathbf{A}t} = \sum_{n=0}^{\infty} \frac{(\mathbf{A}t)^n}{n!} ##.
Because multiplying a matrix by itself is perfectly well defined, the above sum makes sense. Now if ## t ## is not too large, we can truncate the series and write
## e^{\mathbf{A}t} \approx (\mathbf{A}t)^0 + \mathbf{A}t \equiv \mathbf{I} + \mathbf{A}t ##,
where ##\mathbf{I}## is the identity matrix. Using this truncated sum, your formula can be derived, except for the time dependent functions ##\alpha_1(t)## and ##\alpha_2(t)##. Perhaps someone else can shed some light on where those might be coming from. What is the context in which you are seeing this equation?