Artificial Intelligence (AI) is presented as a possible cause of major technological disruption in the short and medium term for the media ecosystem. The widespread integration of AI, and specially of generative AI into content creation and distribution is predicted to transform the paradigms of productivity, labor and task automation. On the demand side, it's going to enhance user experience by personalising content, anticipating needs and programatic distribution. AI can be conceptualized as a computer system that can process, analyze, and respond to data inputs on tasks typically requiring human intelligence (De-Lima-Santos & Ceron 2022; Diakopoulos 2019). As any breakthrough technology, it is as relevant to analyse the typology of innovation (characteristics, trajectory of adoption and process enablement) as it is to consider its wider societal impacts (Millar et al., 2018). There are significant challenges ahead, mostly related to the rise of AI (Newman, 2023; Cardoso et al., 2022), as well as uncertainty on the ability most organisations have to balance the positive and negative outcomes of these technologies (Annoni et al., 2018). Organisations are sceptical about their capacities to get the most out of these tools and believe that professionals need to be trained in this field (Barbosa et al., 2022). However, without proper professionals training, AI could mainly be applied to intermediate production processes, such as transcription, summarisation or translation (De Lara et al., 2022) or be used to manage big data analyses making data outputs more efficient for data journalists. The verification of disinformation will have to be strengthened to react to content manipulated by AI, as the development of AI will create an increased threat to information, leading to the emergence of more sophisticated disinformation that is difficult to verify (Welter & Canavilhas, 2023). This could lead to the creation of effective training programmes that enable journalists and fact-checkers to acquire specific tools not only to understand the use of technology but also to promote media literacy, which is seen as the main tool for combating disinformation (Deuze & Beckett, 2022). At the same time, AI may act as an enabling agent in fact-checking by speeding up the verification process and thus mitigating one key negative aspect of this kind of journalism, which is the time it takes for the verification to be published after the spread of disinformation (Heinold et al., 2023). With this contribution, we aim to, as in traditional prospective / outcome reports, identify major areas of AI impact in media, but go further than the short-term prediction, based on the input of market and academic experts and editors. The research used mixed methods (qualitative and quantitative, based on both interviews and targeted online survey) and was based on extended consultation of experts - researchers and academics - and surveying of editors and managers of media companies in Portugal and Spain. Firstly, a total of 71 experts in 16 previously selected areas were consulted through interviews in order to produce a synthesis that outlines the panorama for each topic. Secondly, and based on the responses collected, a closed-ended online questionnaire was put to 101 media editors and managers. In other words, the perceptions of researchers and experts were surveyed among those working in the industry. This methodological approach aims to fill in a significant gap in the prospective studies / trends report fields, which is that most contributions usually consider one of the relevant dimensions to the prospection process, either the expert sphere or the direct feedback from industry. As a summary, the conclusions are twofold. On one hand there is a recognition of AI in general, and generative AI in particular, as an enabler for journalists to develop their creative work and fight disinformation, and for media outlets to strengthen their relationship with the audiences. On the other hand, despite their willingness, there are doubts about the ability of newsrooms to deal with the disruptive changes posed by AI. In addition to the organizations, journalists themselves do not view this interference in their work and journalist values in the same way. To what extent are journalist roles challenged or advanced as a result of automated journalism? (Schapals & Porlezza, 2020) It should be noted that this rapid change happens within a very specific context within the media industry, at a time where most media outlets are facing severe threats to their survival and scrambling to come up with sustainable business models in an environment strongly dominated by the big platforms and the rise of AI platforms (Caswell, 2023), while it may change the power structure of the internet, will hardly benefit traditional / historical media companies. In this context, the future negotiating stance of the news media industry (Poell, 2023) in the AI-driven landscape will be strengthened by a deep-rooted commitment to journalistic standards. It must as well take into consideration the way journalistic content is appropriated and used to train language learning models, meaning journalism must become part of a wider discussion regarding the appropriation and monetization of intelectual property for the training of language learning models (Fontana, 2024; Senftleben, 2024).

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