Today, in the era of the fourth industrial revolution, also known as Industry 4.0 (I4.0), Robotic Process Automation (RPA) technology has been considered an important tool for digital transformation in operations and supply chains because of its lightweight approach to automate and optimize repetitive tasks, streamline and improve internal processes, and control end-to-end business processes, which enables cost and operational risk reduction. Driven by COVID-19, the market for RPA technologies continues to be one of the fastest growing segments in the enterprise software market. However, in the academic literature there are still few works referring to the RPA theme with the approach focused on the supply chain, even though it is increasingly used in the purchasing area with a focus on process automation. Moreover, despite the existence of technology acceptance models (e.g., TAM and TAM2), which have relevant criteria to assess innovation, there are still few studies that combine these criteria with multicriteria decision support methods to propose a more robust methodology for technology selection in the I4.0 era. And, from the literature review there is still no research relating RPA technology adoption criteria and group multicriteria approach through the lens of innovation diffusion theory. Given this, the objective of this research is to propose a methodology for evaluating RPA platforms in the context of I4.0 and through the lenses of innovation diffusion theory. This methodology is tested from the selection of an RPA platform for application in the procurement process of an offshore oil, gas and wind energy operating company. The research methodology involves mixed methods, with a group multicriteria approach, which combined two methods: Fuzzy Delphi and AHP-express, and data collection through structured questionnaires elaborated from the reports of the consulting companies Gartner (2021) and Forrester (2021) regarding the RPA platforms present in the market. From the research results, the RPA platform Workfusion was selected as the best platform to be applied in the purchasing area of the company that is the object of study, due to its good evaluation in the criteria: structured data processing, assisted automation and RPA applications developed for front-end users, however the RPA platform Blue Prism was in the lowest level of the ranking of the 14 RPA platforms evaluated, due to its low score in the criteria: available in the cloud, integrated dashboards and autonomous automation. Thus, from a practical point of view, the work contributes a new methodology for selecting RPA platforms for the procurement industry, which has relevance for academic literature and brings its contribution to industry that in future studies, should be applied to more companies in the oil, gas and wind energy industry.