A 2026 Virtualis article by Matías Alvarado Leyton examines epistemological limits of applying distant reading to oral-history corpora, contending that computational methods reframe testimony through abstraction, aggregation and pattern detection and recommending a hybrid, stratified approach that pairs algorithmic tools with historiographic interpretation.
Claudia Benassini Félix frames the article with two objectives: to present open alternatives for knowledge construction from convergences among deep mediatization, media ecology and generative artificial intelligence; and to illustrate those convergences through analysis of a tweet generated by the communication team of the Suprema Corte de Justicia de la Nación associated with Yasmín Esquivel, drawing ethical implications for the minister’s use of generative AI for promotion.
Claudia Benassini Félix frames the article with two objectives: to present open alternatives for knowledge construction from convergences among deep mediatization, media ecology and generative artificial intelligence; and to illustrate those convergences through analysis of a tweet generated by the communication team of the Suprema Corte de Justicia de la Nación associated with Yasmín Esquivel, drawing ethical implications for the minister’s use of generative AI for promotion.
A webinar replay from Perspective with Axys shows how AI-driven data governance can help large companies speed convergence between Finance and ESG, improve data reliability and compliance, and deliver practical tools including automated data-quality workflows, deduplication and standardisation—targeting CFOs, CIOs and sustainability leads and offering a ROI roadmap and six use cases to inspire implementation.
Perspective published a webinar (available as a replay) produced with Axys that presents AI applied to data governance as a way for large companies to reconcile Finance and ESG data; the session promises concrete solutions—automating ESG and financial data quality, deduplication and standardisation—lists nine quality pillars, six use cases and a single roadmap claimed to clarify ROI and cite organisations that have already adopted these practices.
Karsten Wellert, Antenne Bayern board member and CDO, says the station deploys AI for testing, virtual listener personas and a WhatsApp chatbot, but insists every on‑air voice and editorial decision remain human. The chatbot is introduced transparently with an opt‑out. The company combines multiple AI models for back‑office support and treats live rollouts as iterative experiments.
Antenne Bayern uses AI only as a behind‑the‑scenes tool: teams run experiments, feed market‑research data into AI‑supported virtual listener personas for fast feedback, and operate a WhatsApp chatbot that identifies itself and offers an opt‑out. The group aggregates outputs from several models but maintains that programming and on‑air presentation are entirely human.
A Digiday+ Research survey in the first quarter of 2026 of more than 100 marketing professionals found that 49% report using AI in social media campaigns and 42% report using AI in retail media; Digiday+ Research says adoption varies by channel and often depends on trust.
A Digiday+ Research survey in the first quarter of 2026 of more than 100 marketing professionals found that 49% report using AI in social media campaigns and 42% report using AI in retail media; Digiday+ Research says adoption varies by channel and often depends on trust.
XR Institute reports that Reality Composer Pro 3 is now a standalone macOS app emphasizing faster iteration for visionOS through visual workflows, an entity/component model, GPU-driven compute simulations, prefab-like prototypes, live headset preview, baked lightmaps, and an integrated AI assistant.
XR Institute reports that Reality Composer Pro 3 is now a standalone macOS app emphasizing faster iteration for visionOS through visual workflows, an entity/component model, GPU-driven compute simulations, prefab-like prototypes, live headset preview, baked lightmaps, and an integrated AI assistant.
A Digiday+ Research report based on a survey of 142 brand and agency professionals and interviews finds marketers’ adoption of AI rose from 44% in 2022 to 86% in 2025, while the report states that employee training has not kept pace with that adoption.
A Digiday+ Research report based on a survey of 142 brand and agency professionals and interviews finds marketers’ adoption of AI rose from 44% in 2022 to 86% in 2025, while the report states that employee training has not kept pace with that adoption.
Digiday’s report, based on a survey of 142 brand and agency professionals and interviews with marketing and technology executives, finds AI tools have become embedded across marketing workflows entering 2026, yet trust and the complexity of agentic AI remain material barriers to wider adoption.
Digiday’s member-only research, titled “The marketer’s guide to AI applications, agentic AI, AI search and GEO/AEO in 2026,” surveyed 142 brand and agency professionals and included interviews with executives responsible for AI investments; the findings report broad embedding of AI in workflows alongside persistent concerns about trust and integration complexity.
A Digiday+ Research survey of 62 agency professionals conducted in the fourth quarter of 2025 found that agencies cite reduced client spending and the effects of AI as equal leading concerns for 2026, each selected by 38% of respondents.
In a late‑2025 Digiday+ Research poll of 62 agency professionals, 38% of respondents identified reduced client budgets as the industry’s biggest challenge for 2026 and an identical 38% pointed to the effects of AI; the survey continues a trend of spending pessimism from 2025, when 47% named reduced client budgets the top concern.
A Digiday+ Research report, based on a survey of 40 publisher professionals and interviews with publisher executives, says generative AI fits editorial workflows better than predictive AI. The finding appears in a member-exclusive Digiday article summarizing the report.
Digiday’s excerpt describes a report—drawn from a survey of 40 publisher professionals and follow-up interviews—that concludes generative AI is more compatible with newsroom editorial tasks than predictive AI, as publishers seek the right roles for AI after the technology moved into mainstream workflows.