️ with podcast host Eva Simone Lihotzky
Responsible AI stops being a compliance exercise the moment an
agent acts without you. Only 21% of organisations deploying AI
agents have a mature governance model for them, and 35% concede
they could not shut one down if it went wrong. This episode is
for leaders running agentic pilots who could not, if pressed,
name the person who answers when one of them fails.
Episode overview
Eva Simone Lihotzky takes the Harvard Business Review's claim
that trust is becoming a competitive advantage and tests it
against what she sees inside client organisations. The episode
traces the move from generative to agentic to physical AI and
argues that each transfer of autonomy changes what trust has to
cover: you check an output before it leaves your hands, you check
an action once it is already out and handed on, and with physical
systems you are trusting a consequence that has already happened.
From there it turns to governance, a word she concedes lands
badly in most rooms, and to why she thinks the structures behind
the technology are the part that compounds. Underneath runs a
question she leaves open: technology needs defined inputs,
guardrails and outcomes, creative work needs close to the
opposite, and she does not claim to know where the line between
them sits. It closes on five questions leaders can run against
their own systems, and on why a narrative built around efficiency
makes resistance the rational response.
🪜 Key themes
Why each step up the autonomy ladder is also a step up the
trust ladder, and why the moment you could still check arrives
later at every rung
What survives when the models get replaced, and why
accountability lines outlast vendor and architecture decisions
Whether governance slows an organisation down, or is the
reason it can move at all
Where technical specification and creative freedom have to be
negotiated, and why that negotiation never settles
What an unowned decision costs, and the five questions that
expose one
About the host
[PLACEHOLDER - see flag below. Structure to fill: Eva as founder
of raidiant, the client work that produces the governance
argument, and her governance and assurance background, which is
the specific detail that matters for this episode because it is
why she can concede how badly the word lands and argue for it
anyway. Co-author of '10 Moral Questions: How to Design Tech
& AI Responsibly', referenced in the episode as prior art for
building governance into the design stage.]
️ Chapter markers
[03:27] Where the human stops being the operator
[08:12] Trusting the output, then the action, then the
consequence
[12:16] Outstructuring the competition while the models keep
changing
[16:53] What technology needs defined, and what creative work
needs left open
[22:14] Five questions, and the decision with no name
attached
Links
Eva Simone Lihotzky on LinkedIn -
https://www.linkedin.com/in/evalihotzky/
raidiant - https://www.raidiant.eu
Harvard Business Review, "Responsible AI is Becoming a Growth
Strategy" -
https://hbr.org/2026/07/responsible-ai-is-becoming-a-growth-strategy
Stanford AI Index 2026 -
https://hai.stanford.edu/ai-index/2026-ai-index-report
McKinsey research on agentic AI risk and security
concerns: https://www.mckinsey.com/capabilities/tech-and-ai/our-insights/tech-forward/state-of-ai-trust-in-2026-shifting-to-the-agentic-era
Informatica CDO Insights
2026: https://www.informatica.com/about-us/news/news-releases/2026/01/20260127-new-global-cdo-report-reveals-data-governance-and-ai-literacy-as-key-accelerators-in-ai-adoption.html
Writer research on AI strategy and rogue
agents: https://writer.com/blog/enterprise-ai-adoption-2026/
IBM research on agent decision-making
visibility: https://community.ibm.com/community/user/blogs/sarah-bowden/2025/11/18/agentic-ai-is-here-5-key-learnings-from-ibms-lates
10 Moral Questions: How to Design Tech & AI
Responsibly: https://www.10moralquestions.com/the-book
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