We present an automated procedure that simultaneously derives the effective temperature Teff, surface gravity logg, metallicity [Fe/H], and equatorial projected rotational velocity vsini for "normal" A and Am stars. The procedure is based on the principal component analysis (PCA) inversion method, which we published in a recent paper. A sample of 322 high-resolution spectra of F0-B9 stars, retrieved from the Polarbase, SOPHIE, and ELODIE databases, were used to test this technique with real data. We selected the spectral region from 4400-5000 Ang as it contains many metallic lines and the Balmer H{beta} line. Using three data sets at resolving powers of R=42000, 65000 and 76000, about ~6.6x10^6 synthetic spectra were calculated to build a large learning database. The Online Power Iteration algorithm was applied to these learning data sets to estimate the principal components (PC). The projection of spectra onto the few PCs offered an efficient comparison metric in a low-dimensional space. The spectra of the well-known A0- and A1-type stars, Vega and Sirius A, were used as control spectra in the three databases. Spectra of other well-known A-type stars were also employed to characterize the accuracy of the inversion technique. We inverted all of the observational spectra and derived the atmospheric parameters. After removal of a few outliers, the PCA-inversion method appeared to be very efficient in determining Teff, [Fe/H], and vsini for A/Am stars. The derived parameters agree very well with previous determinations. Using a statistical approach, deviations of around 150K, 0.35dex, 0.15dex, and 2km/s were found for Teff, logg, [Fe/H], and vsini with respect to literature values for A-type stars. The PCA inversion proves to be a very fast, practical, and reliable tool for estimating stellar parameters of FGK and A stars and for deriving effective temperatures of M stars.