Enterprise AI is shifting from experiments to infrastructure, and that changes everything. In this episode, Dr Andree Bates interviews Jocelyn Houle, Senior Director of Product Management at Securiti.ai, to explore the future of enterprise AI, agents, automation, and the single biggest blocker to scale: trust.

Jocelyn shares what she is seeing across highly regulated industries as organisations move beyond proof of concept into production. She explains why the agent era raises the stakes: when you add LLMs into workflows, systems become non-deterministic and harder to trace end to end. In her words, once the data goes in, you cannot easily untangle it, so organisations need stronger controls around permissions, auditing, and policy enforcement.

A major theme is that data foundations matter more than ever. Jocelyn warns that agents will not magically repair messy data, they will expose weak data quality immediately. From there, she outlines how trust can be won or lost at the prompt layer, both outbound (what the model says to customers) and inbound (what users share with the organisation). She also discusses “toxic combinations”, where overlapping access can accidentally leak sensitive information, plus the growing need for prompt screening and tracking to reduce risk.

The conversation also digs into explainability and auditability, with Jocelyn being refreshingly honest that the perfect solution is not here yet. Instead, enterprises are using practical approaches like benchmarking releases side by side, cataloguing AI agents in use, and building governance that is starting to look more like modern cybersecurity: baked in from the start, not added as an afterthought.

Jocelyn closes with clear advice for leaders: start “left” with raw data controls, build a truly cross-functional team, and begin setting up auditability even with imperfect tools, because regulators are catching up and they will expect responsible behaviour.

Topics Covered

Where enterprise AI adoption really stands today
What makes AI agents different from traditional automation
Non-determinism, traceability, and why permissions matter
Data mapping, policy controls, and reducing sensitive data leakage
Prompt security: outbound and inbound trust risks
“Toxic combinations” and exposure through agent workflows
Explainability, benchmarking, and parallel release testing
AI governance becoming as essential as cybersecurity
Top 3 pieces of advice for CTOs starting their AI journey
Why enterprise AI will become so embedded we stop talking about it

AI For Pharma Growth is the podcast from pioneering Pharma Artificial Intelligence entrepreneur Dr Andree Bates, created to help pharma, biotech and healthcare organisations understand how AI-based technologies can save time, grow brands, and improve company results.

This show blends deep sector experience with practical conversations that demystify AI for biopharma leaders, from start-up biotech right through to Big Pharma. Each episode features experts building AI-powered tools that are driving real-world results across discovery, R&D, clinical trials, medical affairs, market access, regulatory, insights, sales, marketing, and more.

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About the Podcast

E208 : The future of enterprise AI: agents, automation, and trust

AI For Pharma Growth