Mike Morath’s TEA Connected Alpha School With Texas Districts

Key Takeaways

• The Texas Education Agency helped Alpha School affiliates contact at least 10 districts, although the agency says it had no formal partnership with Alpha Schools.
• Houston, Fort Davis and Aldine piloted Alpha School’s AI software for supplemental learning as policy development lagged adoption.
• The episode highlights procurement, transparency, privacy and instructional-governance questions for education technology vendors and public school leaders.

The Texas Education Agency, led by Commissioner Mike Morath, helped Alpha School affiliates approach at least 10 Texas school districts about using the company’s artificial intelligence software. Houston, Fort Davis and Aldine later piloted the technology for supplemental learning, according to reporting by the Texas Tribune and ProPublica.

TEA has said it had “no formal partnership” with Alpha Schools. Still, the agency’s role in facilitating introductions gave Alpha School access to district decision-makers and added institutional weight to the outreach. For public-sector technology buyers, that distinction matters. An introduction is not a contract or endorsement, but vendors that arrive through state officials can receive attention that ordinary sales outreach might not command.

The State Board of Education raised concerns about Alpha School’s AI. Those concerns land amid a wider debate over how quickly AI products should enter classrooms, what evidence should support adoption and which public bodies are accountable when pilots move ahead.

School AI adoption is already running ahead of governance. During the 2024-25 school year, 54% of U.S. students and 53% of core-subject teachers reported using AI for school, increases of more than 15 percentage points from earlier surveys, according to RAND findings summarized by ETC Journal. Yet more than 80% of students said teachers had not explicitly taught them how to use AI for schoolwork. Only 35% of district leaders reported offering student AI training, and 45% of principals said their school or district had AI guidance or policies.

Texas shows an even sharper mismatch. In a fall 2025 survey of district leaders by UT Austin and the Texas Association of School Administrators, 86% reported teacher AI use and 61% reported student use. However, only 29% had a student AI policy, while 20% had a staff policy. Coverage of the Texas AI in Education Task Force by Winssolutions reflects the growing pressure for clearer statewide approaches.

What should a district evaluate before an AI pilot begins? Product accuracy is only one consideration. Leaders also need to examine student-data collection, retention, third-party access, accessibility, bias, curriculum alignment and the ability of teachers to review or override automated recommendations. Contracts should clarify whether student interactions can be used to train models and how data will be deleted after a pilot.

Evidence is another sticking point. Supplemental-learning pilots can produce useful operational information, but they do not automatically demonstrate durable academic gains. Districts may benefit from defining success before deployment, using measures tied to specific learning goals and comparing outcomes across student groups. Otherwise, engagement metrics such as time in an application can be mistaken for educational impact.

That said, Alpha School is part of a much larger market shift. Khan Academy’s Khanmigo and Google Gemini for Education illustrate how AI tutoring, lesson preparation and personalized support are moving into mainstream education systems. The business opportunity is substantial, but vendors face a demanding customer base where purchasing authority is fragmented and decisions are politically visible.

International and technical frameworks offer useful starting points. UNESCO’s 2024 AI Competency Frameworks for Students and Teachers emphasize human agency and educator capability, while its 2025 guidance says AI should support rather than replace teachers. The NIST AI Risk Management Framework, published in 2023, gives districts a broader structure for identifying, measuring and managing risks.

For Mike Morath, TEA and Alpha School, scrutiny will likely center on process as much as product performance. Districts need to know when an introduction represents informal outreach, policy encouragement or something closer to state-backed validation. Vendors, meanwhile, can reduce friction by disclosing evaluation methods, data practices and the limits of their systems early. In education technology, access opens the door. Transparent evidence and accountable deployment determine whether it stays open.