To accelerate technological innovations using atomic layer deposition (ALD) coatings, we need to establish better understanding of structure-property relationships for ALD films. Historically, the ALD community has had difficulty connecting the atomic structure of ALD films with their performance, largely because of the significant challenge in determining the atomic-scale structure of ultrathin ALD films that are often amorphous, polycrystalline, or defective. In this work, we describe a series of recent efforts that collectively aim to improve understanding of the atomic structure of ALD coatings and inform structure-property understanding. These efforts employ experimental measurements including (a) inert-transfer XPS, (b) in-situ synchrotron high energy X-ray diffraction, and (c) cryogenic electron diffraction. Of particular focus in this talk is the use of X-ray and electron diffraction measurements in combination with pair distribution function (PDF) analysis and reverse Monte Carlo (RMC) structural modeling. We describe a newly developed approach employing alternating RMC and molecular statics steps (RMC-MS) that improves the physical accuracy of model structures derived from experimental diffraction data with minimal additional computational cost over conventional RMC modeling. We also describe efforts using localized cryogenic electron diffraction and PDF analysis (cryo-ePDF) with a ≤ 5 nm spot size to measure atomic structure at ALD interfaces. Together, these advances allow us to quantify differences in the atomic structure as a function of position through the depth of ALD films. A simple two-phase model comprised of bulk and interfacial layers with distinct atomic structure features is consistent with our measurements for both aluminum oxide and zinc oxide ALD coatings. The approaches we report yield atomic structure models that can be used to inform computational studies of the properties if ALD films and will aid in the selection and modification of ALD coating chemistries to address technological needs.