Conservation agriculture offers proven benefits for soil health, water retention, and farm resilience, yet adoption across the United States remains far below its potential. The technical assistance system that connects producers to conservation practices is under strain: advisor shortages, administrative complexity, fragmented data infrastructure, and backlogs stretching up to two years leave many producers — particularly small-scale and limited-resource operations — without adequate support. At the same time, a new generation of AI and digital tools is rapidly expanding what is possible in agricultural advising. This white paper examines whether, and how, these technologies can help close that gap. Drawing on a comprehensive literature review, an assessment of more than one hundred digital and AI-enabled tools, and stakeholder consultations including focus groups and expert interviews, it identifies four mutually reinforcing barriers — advisor capacity constraints, organizational capacity gaps, mission alignment challenges, and structural limitations — and eight critical gaps in the current tool landscape. It finds that the problem is not a shortage of tools, but a shortage of tools that are trustworthy, locally calibrated, accessible, and integrated into the institutions that serve producers. The paper presents a theory of change, a logic model, and an indicators-and-learning framework to guide responsible adoption, along with a portfolio of nineteen research and pilot opportunities to help advisors, agencies, funders, and partners shape the integration of AI into the conservation system.