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Trust, Visibility, and the Cost of Sharing Expertise
How 111 business professionals are sharing expertise at work: 59% say helping others is their primary motivation, 45% prefer one-to-one or small-group formats over broadcast, 79% name time and production effort as the main barrier to sustained sharing, and 99% require guardrails before adopting AI-assisted sharing.
AI At Work: Adoption, Friction, and Workforce Redesign
This research examines how organizations are moving from AI experimentation into practical workforce adoption, with a focus on where AI is being used, what is slowing broader deployment, and how leaders are adapting roles, hiring, and management expectations in response. The topic matters because AI is no longer just a technology decision; it is becoming an operating model and workforce design question, shaping how work gets done, what skills are valued, and how companies balance productivity gains with governance, trust, and human judgment.
Bounded Autonomy: How Enterprises Are Scaling AI
How 303 enterprise leaders are scaling AI without ceding control: 93% have hit real automation failure modes, 54% name risk and liability as their top constraint, 77% keep sensitive work assistive-only with human approval, and 79% are actively preparing infrastructure for agentic workflows.