Original research on what actually works in deployed AI
AWSM RSRCH™ (“research”) publishes original research on the questions that matter most for AI activation — grounded in proprietary data from real engagements: telemetry, post-deployment outcomes, and workflow analysis, never surveys or vendor claims. It’s the same method we bring to the work itself, turned outward: ROI-first, design-led, and iterative, built to prove what compounds value rather than what merely demos well. Four pillars organize what we study.
AI Value Attribution
How organizations attribute business value to AI investments — through the Four-Lens ROI framework — in ways that hold up to boards, PE sponsors, and CFOs.
Workflow Architecture
How work gets restructured when AI enters — which steps automate, which become human-AI loops, which collapse — across augmentation, recomposition, and replacement patterns.
AI Tool Efficacy
Which AI tools produce measurable outcomes against which workflows — scored on the workflow-tool pair, not product rankings, across five dimensions: outcome efficacy, adoption velocity, integration fit, total cost of ownership, and deployment risk.
AI Adoption & Governance
What organizational and behavioral conditions determine whether deployed AI actually gets used, trusted, and scaled — the most underserved territory in the market, fed directly by KNTRL telemetry.