In this Task Force, we framed indicators of ʻŌiwi Edge for E Ola! by focusing on how AI tools might support teacher well-being. To do this, we measured AI tool instructional effectiveness and efficiencies through a comparative evaluation design. Over twelve weeks, participants were purposefully sampled into two groups: 1) GenAI — given access to four commonly used large language models (LLMs), and 2) Specific AI tool (Kyron) — which provided lesson planning, AI-generated learning videos for haumāna, and an embedded AI tutor designed to support all learners through conversations, scenario-based tasks, interactivity, and coaching. 

All task force kumu submitted reflections via an AI Technologies Weekly Usage Form, capturing frequency of AI use, amount of planning time saved, perceived relief in mental load, and overall sense of well-being. Teachers also timed routine tasks like lesson planning. A statistical test revealed that the GenAI group saved considerably more time than the Kyron group, suggesting that flexible AI can streamline preparation while still honoring ʻŌiwi values.

To add depth, we held two focus groups in March and May with ten teachers from both cohorts. Their conversations revealed three main insights: first, many saw AI as a “thinking partner” that speeds up content creation and deepens engagement with ʻŌiwi knowledge; second, teachers emphasized the need to check and adapt AI outputs for proper language and cultural context; third, although AI cut down drafting time, teachers redirected those hours to refine cultural relevance and give students personalized feedback. 

Kyron users noted a steeper learning curve and occasional mismatches with ʻōlelo Hawaiʻi. Meanwhile, GenAI users appreciated the flexibility to rework content. Across both groups, all participants agreed that AI should enhance—but never replace—the relational, place-based elements central to ʻŌiwi Edge.

Taken together, this mixed-methods approach—triangulating weekly self-reports, time-tracking data, and iterative qualitative dialogue—offers a robust portrait of how AI tools can facilitate ʻŌiwi Edge indicators: measurable efficiency gains, strengthened teacher–student competencies, and improved well-being outcomes. By foregrounding both statistical significance and thematic depth, the HānAI Task Force study establishes concrete markers for integrating AI in ways that honor and uphold ʻŌiwi foundations, ultimately guiding future iterations of E Ola! toward an epistemology of Kuapapa Nui.