AI is making work faster, more creative but harder to stop. In this episode of Human+AI Impact, Dr. Sabrina Anjara is joined by Anthony Cannon to explore a less visible side of AI productivity: the rise of “always-on” work. As AI collapses the gap between idea and execution, it creates powerful flow states that can drive output, but also extend effort beyond sustainable limits. They unpack what this new pattern of work feels like in practice, why traditional signs of burnout don’t apply, and how leaders need to rethink productivity design. Sabrina proposes stopping rules, flow boundaries, and new signals of over-engagement. Because the next challenge in AI-enabled work isn’t just performance, it’s knowing when to stop.
Most organizations measure AI adoption by access: licenses issued, seats activated, usage frequency. But access is not fluency.In this episode of Human+AI Impact, Dr. Sabrina Anjara and Rachel Earley unpack what real AI fluency looks like in practice. Drawing on Human+AI Impact research, they explore why high-fluency users iterate rather than accept first drafts, why polished outputs reduce scrutiny and why the loudest users may actually be the most advanced.If your AI rollout feels quiet, that may not be success. Fluency shows up in behaviour — and behaviour is shaped by design.
Is Responsible AI slowing teams down—or is it just stuck in the wrong place? In this episode, Dr. Sabrina Anjara talks with Patrick Connolly about why governance must evolve for agentic AI systems. They explore how shifting governance into pipelines and runtime operations transforms it from a compliance bottleneck into a performance enabler. From AgentOps and real-time controls to trust as a measurable throughput signal, this episode shows how responsible AI becomes the infrastructure that lets organizations scale faster—and safer.
AI is generating more ideas, options, and outputs than ever before—so why are so many organizations capturing less value? In this episode, Dr. Sabrina Anjara speaks with Darragh Miller about the AI surplus paradox and why traditional KPIs fail in a world of recursive, learning systems. They unpack how static dashboards hide end-to-end value, why measurement must become a living system, and how leaders can reconcile competing CEO, CFO, CIO, and CHRO value lenses. A deep dive into why measurement is now strategic—and moral.
AI can make work faster—but does it make it better? In this episode, Dr. Sabrina Anjara is joined by Dr. Manaswi Saha to challenge the idea that speed equals productivity in knowledge work. They explore why “just add human oversight” often fails, how misdesigned collaboration patterns quietly scale risk, and what it really means to measure human–AI collaboration quality. From agency and cognitive effort to joint utility and trust over time, this conversation reframes productivity as something you design—not something you accelerate blindly.