{"format":3,"method":"deterministic","version":"445ba2430c88","generated_at":"2026-11-01T17:46:17.173043Z","reason":null,"reason_detail":null,"provenance":"verificada_contra_la_fuente","claims":[{"id":"D1","kind":"cifra","fact_id":"A17","value":47.0,"said_as":"47","text":"Top AI-related concerns among the 47 survey respondents: ethical governance, algorithmic partiality (defined in the report as fairness or bias in AI algorithms), and data security.","period":null,"said_in":[{"scene":1,"second":null}],"owner_scene":1,"backing":"respaldada_en_su_escena","on_screen":"notShown","citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":"2025"}},{"id":"D2","kind":"cifra","fact_id":"A18","value":94.0,"said_as":"94%","text":"Despite high ethical and privacy concerns, organizational restructuring has been minimal among the 47 survey respondents: 94% reported no new leadership positions designated for AI oversight or strategy; 91% indicated no new staff or faculty roles created to manage or develop AI initiatives; 87% confirmed no restructuring of existing leadership responsibilities to formally incorporate AI-related duties. The report describes this contrast as 'stark.'","period":"2025","said_in":[{"scene":2,"second":null}],"owner_scene":2,"backing":"respaldada_en_su_escena","on_screen":"drawn","citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":"2025"}},{"id":"D3","kind":"cifra","fact_id":"A18","value":91.0,"said_as":"91%","text":"Despite high ethical and privacy concerns, organizational restructuring has been minimal among the 47 survey respondents: 94% reported no new leadership positions designated for AI oversight or strategy; 91% indicated no new staff or faculty roles created to manage or develop AI initiatives; 87% confirmed no restructuring of existing leadership responsibilities to formally incorporate AI-related duties. The report describes this contrast as 'stark.'","period":"2025","said_in":[{"scene":2,"second":null}],"owner_scene":2,"backing":"respaldada_en_su_escena","on_screen":"drawn","citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":"2025"}},{"id":"D4","kind":"cifra","fact_id":"A18","value":87.0,"said_as":"87%","text":"Despite high ethical and privacy concerns, organizational restructuring has been minimal among the 47 survey respondents: 94% reported no new leadership positions designated for AI oversight or strategy; 91% indicated no new staff or faculty roles created to manage or develop AI initiatives; 87% confirmed no restructuring of existing leadership responsibilities to formally incorporate AI-related duties. The report describes this contrast as 'stark.'","period":"2025","said_in":[{"scene":2,"second":null}],"owner_scene":2,"backing":"respaldada_en_su_escena","on_screen":"drawn","citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":"2025"}},{"id":"D5","kind":"cifra","fact_id":"A4","value":11.0,"said_as":"eleven","text":"Phase 2 (July 2025): 11 small, structured virtual focus groups of 90 minutes each, held as simultaneous regional breakout sessions under the framing question 'Where are we now with AI?', with more than 100 participants representing 41 universities. Qualitative method.","period":"2025","said_in":[{"scene":3,"second":null}],"owner_scene":3,"backing":"respaldada_en_su_escena","on_screen":"drawn","citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":"2025"}},{"id":"D6","kind":"cifra","fact_id":"A5","value":175.0,"said_as":"175","text":"Phase 3 (September 2025, in person): Structured prioritization through two sequential 45-minute activities — brainstorming and prioritization — with 175 participants representing 66 Land-grant universities. Qualitative method.","period":"2025","said_in":[{"scene":4,"second":null}],"owner_scene":4,"backing":"respaldada_en_su_escena","on_screen":"drawn","citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":"2025"}},{"id":"D7","kind":"cifra","fact_id":"A5","value":66.0,"said_as":"66","text":"Phase 3 (September 2025, in person): Structured prioritization through two sequential 45-minute activities — brainstorming and prioritization — with 175 participants representing 66 Land-grant universities. Qualitative method.","period":"2025","said_in":[{"scene":4,"second":null}],"owner_scene":4,"backing":"respaldada_en_su_escena","on_screen":"drawn","citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":"2025"}},{"id":"D8","kind":"cifra","fact_id":"A9","value":47.0,"said_as":"47","text":"Phase 1 survey garnered 47 responses from Extension and agInnovation professionals across 29 states, representing a varied cross-section of roles. (All Phase 1 percentages refer to this base of 47 responses and reflect the perceptions of the leaders surveyed, not a measure of the Land-grant system as a whole.)","period":"2025","said_in":[{"scene":5,"second":null}],"owner_scene":5,"backing":"respaldada_en_su_escena","on_screen":"drawn","citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":"2025"}},{"id":"D9","kind":"cifra","fact_id":"A9","value":29.0,"said_as":"29","text":"Phase 1 survey garnered 47 responses from Extension and agInnovation professionals across 29 states, representing a varied cross-section of roles. (All Phase 1 percentages refer to this base of 47 responses and reflect the perceptions of the leaders surveyed, not a measure of the Land-grant system as a whole.)","period":"2025","said_in":[{"scene":5,"second":null}],"owner_scene":5,"backing":"respaldada_en_su_escena","on_screen":"drawn","citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":"2025"}},{"id":"D10","kind":"cifra","fact_id":"A10","value":67.0,"said_as":"67%","text":"Of the 47 survey respondents, 67% held leadership positions, including Deans, Assistant Deans, and Directors. Role breakdown: 34% Directors, 27% Executive Leaders, 17% Professional Staff, 15% Managers.","period":"2025","said_in":[{"scene":5,"second":null}],"owner_scene":5,"backing":"respaldada_en_su_escena","on_screen":"drawn","citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":"2025"}},{"id":"D11","kind":"cifra","fact_id":"A11","value":73.0,"said_as":"73%","text":"73% of the 47 survey respondents characterized their institution's leadership outlook on AI as either enthusiastic or cautiously optimistic.","period":"2025","said_in":[{"scene":5,"second":null}],"owner_scene":5,"backing":"respaldada_en_su_escena","on_screen":"notShown","citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":"2025"}},{"id":"D12","kind":"cifra","fact_id":"A16","value":52.0,"said_as":"52%","text":"52% of the 47 survey respondents were unsure about the overall direction of their institution's AI-related policies; 53% were uncertain whether current policies adequately address the risks associated with AI; 30% did not know which institution policies, if any, had been updated in response to AI.","period":"2025","said_in":[{"scene":5,"second":null}],"owner_scene":5,"backing":"respaldada_en_su_escena","on_screen":"notShown","citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":"2025"}},{"id":"S1","kind":"enunciado","fact_id":"A26","value":null,"said_as":"Extension professionals describe AI arriving into a “governance vacuum.” Leaders see a strategic opportunity. One Land-grant system, two readings.","text":"Five themes emerged from Phase 5 (qualitative; no participant count or percentages declared): (1) Institutional Governance Scaffolding — a state of 'institutional suspension' and a 'governance vacuum,' with vague guidance and organizational silos; (2) Intellectual Sovereignty — fear of shifting from original knowledge creation to being an 'information verifier' auditing AI-generated content; (3) Stewardship of Public Trust — the educator as 'frontline defense' against misinformation, with special concern in youth programs such as 4-H; (4) Professional Development and Capacity Building — AI adoption perceived as an additional responsibility on an already full workload, compounded by tool costs and cybersecurity restrictions; (5) Societal Ethics and the Extension Mission — a perceived contradiction between promoting sustainability and adopting technologies that require significant energy and water consumption through large-scale data infrastructure, described as a 'central moral conflict.'","period":null,"said_in":[{"scene":0,"second":null},{"scene":6,"second":null},{"scene":7,"second":null},{"scene":8,"second":null},{"scene":11,"second":null}],"owner_scene":0,"backing":"respaldada_en_su_escena","on_screen":null,"citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":null}},{"id":"S2","kind":"enunciado","fact_id":"A28","value":null,"said_as":"Extension professionals describe AI arriving into a “governance vacuum.” Leaders see a strategic opportunity. One Land-grant system, two readings.","text":"Points of Divergence between leadership and workforce perspectives: (1) Administrative efficiency (leadership view) vs. verification labor — professionals describe a 'productivity paradox' where time savings are offset by the need to verify AI-generated content; (2) Strategic opportunity (leadership) vs. resigned acceptance (workforce); (3) Environmental-mission gap — professionals identify a contradiction between AI's resource demands and Extension's sustainability mission, less prominent in leadership findings; (4) Top-down strategy (leadership) vs. capacity constraints — professionals describe AI adoption as an additional burden without sufficient time or support.","period":null,"said_in":[{"scene":0,"second":null},{"scene":8,"second":null},{"scene":10,"second":null},{"scene":11,"second":null}],"owner_scene":0,"backing":"respaldada_en_su_escena","on_screen":null,"citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":null}},{"id":"S3","kind":"enunciado","fact_id":"N4","value":null,"said_as":"Extension professionals describe AI arriving into a “governance vacuum.” Leaders see a strategic opportunity. One Land-grant system, two readings.","text":"In February 2026, Extension professionals — agents, specialists, and educators — gathered at the Joint Council of Extension Professionals (JCEP) national conference in Savannah, Georgia. Through structured activities designed to capture both individual and collective perspectives, they described AI adoption not as opportunity but as an additional responsibility layered onto already full workloads, compounded by tool costs and cybersecurity restrictions. Their accounts introduced the 'productivity paradox' and the 'governance vacuum' into the study's findings.","period":null,"said_in":[{"scene":0,"second":null},{"scene":6,"second":null},{"scene":10,"second":null}],"owner_scene":0,"backing":"respaldada_en_su_escena","on_screen":null,"citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":"February 2026"}},{"id":"S4","kind":"enunciado","fact_id":"A1","value":null,"said_as":"The Extension Foundation led the study with University of New Hampshire Extension, supported through NTAE with USDA NIFA. A national survey ran in June and July 2025. Eleven virtual focus groups followed, asking: “Where are we now with AI?”","text":"The study is a sequential systems mixed-methods study on the AI landscape across Cooperative Extension and agInnovation in the Land-grant university system, led by the Extension Foundation (EXF) in collaboration with University of New Hampshire Extension and supported through the New Technologies for Ag Extension (NTAE) cooperative agreement with USDA's National Institute for Food and Agriculture (NIFA). Contributing members: Extension Foundation, Oklahoma State University Extension, and University of Maryland Extension.","period":null,"said_in":[{"scene":3,"second":null}],"owner_scene":3,"backing":"respaldada_en_su_escena","on_screen":null,"citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":null}},{"id":"S5","kind":"enunciado","fact_id":"A3","value":null,"said_as":"The Extension Foundation led the study with University of New Hampshire Extension, supported through NTAE with USDA NIFA. A national survey ran in June and July 2025. Eleven virtual focus groups followed, asking: “Where are we now with AI?”","text":"Phase 1 (June–July 2025): National AI Landscape Assessment survey distributed across all 112 Land-grant Universities. Quantitative method.","period":null,"said_in":[{"scene":3,"second":null}],"owner_scene":3,"backing":"respaldada_en_su_escena","on_screen":null,"citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":"2025"}},{"id":"S6","kind":"enunciado","fact_id":"N1","value":null,"said_as":"The Extension Foundation led the study with University of New Hampshire Extension, supported through NTAE with USDA NIFA. A national survey ran in June and July 2025. Eleven virtual focus groups followed, asking: “Where are we now with AI?”","text":"In July 2025, eleven small focus groups convened simultaneously as regional virtual breakout sessions, each lasting 90 minutes. One hundred and six Extension and agInnovation leaders and administrators from 41 universities logged in from across the country, guided by a single framing question: 'Where are we now with AI?' The sessions surfaced a landscape the report describes as complex yet promising — widespread enthusiasm paired with decentralized, largely uncoordinated adoption driven by individual faculty rather than institutional strategy.","period":null,"said_in":[{"scene":3,"second":null}],"owner_scene":3,"backing":"respaldada_en_su_escena","on_screen":null,"citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":"July 2025"}},{"id":"S7","kind":"enunciado","fact_id":"A6","value":null,"said_as":"In September, 175 participants from 66 Land-grant universities met in person. ChatGPT and Google Gemini helped cluster their responses; the team reviewed that synthesis by hand.","text":"Phase 4 (September 2025, in person): Implementation workshop where participants self-selected into breakout groups to develop strategies moving the nine priorities from concept to practice. Between Phases 3 and 4, the facilitation team used ChatGPT and Google Gemini to help synthesize hundreds of qualitative responses into thematic clusters; that AI-assisted synthesis was then reviewed manually to ensure validity, accuracy, and interpretive rigor. Qualitative method.","period":null,"said_in":[{"scene":4,"second":null}],"owner_scene":4,"backing":"respaldada_en_su_escena","on_screen":null,"citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":"2025"}},{"id":"S8","kind":"enunciado","fact_id":"A2","value":null,"said_as":"In September, 175 participants from 66 Land-grant universities met in person. ChatGPT and Google Gemini helped cluster their responses; the team reviewed that synthesis by hand.","text":"The study was originally organized in four sequential phases (June–September 2025) and expanded with a fifth phase in February 2026. In total, 175 individuals across 66 Land-grant universities participated in the original four-month study.","period":null,"said_in":[{"scene":4,"second":null}],"owner_scene":4,"backing":"respaldada_en_su_escena","on_screen":null,"citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":"2026"}},{"id":"S9","kind":"enunciado","fact_id":"N2","value":null,"said_as":"In September, 175 participants from 66 Land-grant universities met in person. ChatGPT and Google Gemini helped cluster their responses; the team reviewed that synthesis by hand.","text":"Between Phases 3 and 4 of the in-person convening in September 2025, the facilitation and analysis team fed hundreds of qualitative responses from the brainstorming sessions into ChatGPT and Google Gemini to consolidate them into thematic clusters. The AI tools identified redundancy, similarity, and co-occurring concepts across the datasets. The team then reviewed the AI-assisted synthesis manually to ensure validity, accuracy, and interpretive rigor before presenting results back to participants.","period":null,"said_in":[{"scene":4,"second":null}],"owner_scene":4,"backing":"respaldada_en_su_escena","on_screen":null,"citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":"September 2025"}},{"id":"S10","kind":"enunciado","fact_id":"N3","value":null,"said_as":"In September, 175 participants from 66 Land-grant universities met in person. ChatGPT and Google Gemini helped cluster their responses; the team reviewed that synthesis by hand.","text":"In September 2025, 175 leaders from 66 Land-grant universities gathered in person for two sequential 45-minute activities. In the first, small groups generated as many strategies as possible for advancing AI policy, strategy, and application across three focus areas, submitting ideas through a shared digital form. In the second, participants reviewed the full set of submitted ideas and deliberated to identify their top three priorities within each category, using a structured worksheet and shared online database — arriving at nine priorities to guide future implementation.","period":null,"said_in":[{"scene":4,"second":null},{"scene":12,"second":null}],"owner_scene":4,"backing":"respaldada_en_su_escena","on_screen":null,"citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":"September 2025"}},{"id":"S11","kind":"enunciado","fact_id":"A7","value":null,"said_as":"In February 2026, a fifth phase reached the field: agents, specialists and educators at the JCEP conference in Savannah, Georgia. They describe “institutional suspension.”","text":"Phase 5 (February 2026, in person): Engagement with Extension professionals — agents, specialists, and educators — across program areas and career stages at the Joint Council of Extension Professionals (JCEP) national conference in Savannah, Georgia. No participant count declared for this phase. Qualitative method.","period":null,"said_in":[{"scene":6,"second":null}],"owner_scene":6,"backing":"respaldada_en_su_escena","on_screen":null,"citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":"2026"}},{"id":"S12","kind":"enunciado","fact_id":"N5","value":null,"said_as":"They fear becoming an “information verifier.” Youth educators, including in 4-H, call themselves a “frontline defense” against misinformation.","text":"Across Phase 5, Extension professionals articulated a concern that their role was shifting from original knowledge creation to that of an 'information verifier' — spending increasing time auditing and fact-checking AI-generated content. They described this as a threat to the unique thought processes and research-based expertise that define Land-grant academics, and called for institutional guardrails to preserve the visibility of human and science-based origins of knowledge.","period":null,"said_in":[{"scene":7,"second":null}],"owner_scene":7,"backing":"respaldada_en_su_escena","on_screen":null,"citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":"February 2026"}},{"id":"S13","kind":"enunciado","fact_id":"N7","value":null,"said_as":"They fear becoming an “information verifier.” Youth educators, including in 4-H, call themselves a “frontline defense” against misinformation.","text":"During Phase 5, professionals working in youth programming — including 4-H — described themselves as a 'frontline defense' against misinformation, responsible for helping the public identify red flags and navigate digital content responsibly. They expressed particular concern that AI-mediated interactions could replace human relationships or compromise privacy in programs serving young people.","period":null,"said_in":[{"scene":7,"second":null}],"owner_scene":7,"backing":"respaldada_en_su_escena","on_screen":null,"citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":"February 2026"}},{"id":"S14","kind":"enunciado","fact_id":"N6","value":null,"said_as":"And they name a “central moral conflict”: a sustainability mission beside technologies that draw on energy and water at scale. Among leaders, that concern is less prominent.","text":"Phase 5 professionals described a 'central moral conflict': Extension's mission of resource stewardship and sustainability promotion sits in direct tension with adopting AI technologies that require significant energy and water consumption through large-scale data infrastructure. They expressed concern that adoption driven primarily by external or corporate pressures could conflict with the values they are tasked with upholding — creating a perception of systemic inconsistency.","period":null,"said_in":[{"scene":8,"second":null}],"owner_scene":8,"backing":"respaldada_en_su_escena","on_screen":null,"citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":"February 2026"}},{"id":"S15","kind":"enunciado","fact_id":"A27","value":null,"said_as":"Beside the leaders, four points converge: a demand for institutional guidance; public trust grounded in educators' transparency, not the technology; readiness barriers; and AI that augments human expertise.","text":"Points of Convergence between leadership and workforce perspectives: (1) Demand for institutional guidance — both groups identify a critical gap in formal structure, policy, and direction; (2) Maintaining public trust — trust is grounded not in the technology itself but in the transparency and accountability of human educators; (3) Workforce readiness barriers — current self-directed learning approaches are insufficient; (4) Human-centric ethics — AI should augment, not replace, human expertise.","period":null,"said_in":[{"scene":9,"second":null}],"owner_scene":9,"backing":"respaldada_en_su_escena","on_screen":null,"citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":null}},{"id":"S16","kind":"enunciado","fact_id":"A22","value":null,"said_as":"In September, leaders proposed nine priorities across three areas. Training dominated: a proposed national, tiered program led by Extension.","text":"Nine priorities emerged from Phase 3, organized in three areas. Culture, Ethics, and Public Trust: (1) Be transparent and build public trust; (2) Ethical governance and safeguards; (3) Human-centric education. Capacity, Infrastructure, and Policy: (4) Train people; (5) Set clear rules; (6) Shared systems, resources, and infrastructure. Strategic Readiness and Alignment: (7) Future-ready workforce; (8) Establishment of use cases and best practices; (9) National strategy and collaboration.","period":null,"said_in":[{"scene":12,"second":null}],"owner_scene":12,"backing":"respaldada_en_su_escena","on_screen":null,"citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":null}},{"id":"S17","kind":"enunciado","fact_id":"A23","value":null,"said_as":"In September, leaders proposed nine priorities across three areas. Training dominated: a proposed national, tiered program led by Extension.","text":"Training emerged as the single most dominant priority from Phase 3. Leaders proposed a national, tiered AI training program led by Extension, featuring beginner-to-advanced pathways for faculty, researchers, agents, and community audiences, including foundational AI literacy and ethics, advanced modules such as prompt engineering and data validation, train-the-trainer models, and clear certification pathways.","period":null,"said_in":[{"scene":12,"second":null}],"owner_scene":12,"backing":"respaldada_en_su_escena","on_screen":null,"citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":null}},{"id":"S18","kind":"enunciado","fact_id":"A29","value":null,"said_as":"The report closes on three priorities. People: it names workforce readiness as the single biggest hurdle. Trust: public trust is the system's most critical asset, and “policy must lead technology.” Coordination: shared data systems, common platforms, aligned policies.","text":"The report's three overarching conclusion priorities: (1) People — 'The single biggest hurdle isn't technology; it's workforce readiness'; (2) Trust — public trust as the system's most critical asset; 'policy must lead technology'; (3) Coordination — shared data systems, common platforms, and aligned policies.","period":null,"said_in":[{"scene":13,"second":null},{"scene":15,"second":null}],"owner_scene":13,"backing":"respaldada_en_su_escena","on_screen":null,"citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":null}},{"id":"S19","kind":"enunciado","fact_id":"A25","value":null,"said_as":"The report closes on three priorities. People: it names workforce readiness as the single biggest hurdle. Trust: public trust is the system's most critical asset, and “policy must lead technology.” Coordination: shared data systems, common platforms, aligned policies.","text":"Across both leadership and workforce themes, participants voiced a consistent conclusion: 'policy must lead technology.' Human oversight, ethical governance, and coordinated capacity building are described as prerequisites for AI to achieve its full potential in research and community engagement.","period":null,"said_in":[{"scene":13,"second":null},{"scene":15,"second":null}],"owner_scene":13,"backing":"respaldada_en_su_escena","on_screen":null,"citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":null}},{"id":"S20","kind":"enunciado","fact_id":"A30","value":null,"said_as":"The essential first step it proposes: a National AI Program Action Team, led by ECOP and agInnovation, still to be created.","text":"The report proposes as the essential first step the creation of a National AI Program Action Team (PAT), to be led by ECOP and agInnovation.","period":null,"said_in":[{"scene":14,"second":null}],"owner_scene":14,"backing":"respaldada_en_su_escena","on_screen":null,"citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":null}},{"id":"S21","kind":"enunciado","fact_id":"A32","value":null,"said_as":"The essential first step it proposes: a National AI Program Action Team, led by ECOP and agInnovation, still to be created.","text":"The Extension Foundation describes its own tools MERLIN (Machine-driven Extension Research and Learning Innovation Network) and ExtensionBot in its 'Extension Foundation Insights' section as early-stage models of AI-enabled information discovery and decision support. ExtensionBot requires human validation and content review before publishing. These tools are presented as the Extension Foundation's own initiatives, not as findings validated by the study.","period":null,"said_in":[{"scene":14,"second":null}],"owner_scene":14,"backing":"respaldada_en_su_escena","on_screen":null,"citation":{"title":"2026 Extension Foundation National AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"as_of":null}}],"sources":[{"title":"Extension Foundation 2026 AI Report","url":"https://extension.org/wp-content/uploads/2026/05/AI-REPORT-2026.pdf","doi":null,"authors":["Aaron Weibe","Dhruti Patel"],"role":"principal","read":true,"claims":["D1","D2","D3","D4","D5","D6","D7","D8","D9","D10","D11","D12","S1","S2","S3","S4","S5","S6","S7","S8","S9","S10","S11","S12","S13","S14","S15","S16","S17","S18","S19","S20","S21"]}],"summary":{"codex":"present","figures_total":12,"backed_in_scene":12,"derived":0,"unbacked":0,"context_only":0,"figures_on_screen":{"drawn":9,"approx":0,"withheld":0,"notShown":3},"plotted_values_approx":0,"plotted_values_withheld":3,"figures_outside_the_cut":0},"doi":null,"certifications":[],"claimsDigest":"58c425dcac67bf0d9e0386cdc71e60ea78d320b4b079c664c534f7a9d7b0e177"}