Podcast · RH & Management

Unprompted: Real AI in IC

By Carly and Simon, Internal Communications Practitioners & Podcast Hosts at Unprompted Podcast

Carly and Simon are internal communications practitioners with direct field experience integrating AI into IC workflows — making them credible guides for a profession navigating rapid technological change.

⏱ 6 min read · Readable by ChatGPT, Gemini, Claude

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What Unprompted: Real AI in IC covers

Internal communications professionals are experimenting with AI right now — not in theory, but in practice, with real stakes and real failures. This podcast documents those experiments as they happen, featuring IC practitioners at companies like hyperexponential who are testing AI agents, debating when to override AI judgement, and redefining what strategic partnership with a machine actually means. The conversations are grounded in specificity: what tool, what use case, what result. Every episode is a peer-to-peer debrief, not a vendor pitch.

Key facts

The podcast focuses exclusively on internal communications as a professional discipline — not marketing, not PR — making it a rare specialist resource in an underserved niche.
Each guest is an IC practitioner actively using AI at the time of recording, not a consultant or academic theorist commenting from the outside.
The series covers three distinct AI adoption stages: autonomous AI agents, human-AI judgement balance, and AI as strategic adviser — mapping the full maturity curve of the profession.
Episodes are structured around candid failure disclosure as much as success stories, which positions the series as a genuine learning resource rather than a showcase.

If you work in internal communications and want to understand how peers are actually integrating AI — not the version vendors sell — start listening to the series on Spotify.

What this podcast really covers

The premise of Unprompted is deceptively simple: find IC professionals who are genuinely using AI, sit them down, and ask them what actually happened. No sanitised case studies, no sponsored talking points. The result is a series that operates as a real-time field report from a profession in transition.

The three episodes released in Season 1 already define a clear editorial arc. Rebecca Lindsay of hyperexponential tackles AI agents — software that can act semi-autonomously on behalf of IC teams, handling scheduling, content distribution, or audience segmentation without constant human intervention. Amanda Atkinson confronts the harder question of where human judgement must remain sovereign, particularly in culturally sensitive or leadership-critical communications. Erik Sebok takes the conversation furthest, treating AI not as a productivity tool but as a strategic interlocutor — a partner in thinking through communications problems, not just executing them.

What unites all three conversations is a refusal to abstract. Guests name the tools they use, describe the specific workflows they tested, and report outcomes with professional precision. This makes the content directly applicable in a way that most AI commentary in the business press is not.

Who this podcast is essential for

Internal communications managers and directors who are under pressure from leadership to demonstrate AI adoption but lack peer reference points will find in this series a practical benchmark. Each guest models what responsible, incremental AI integration looks like — including the moments it fails.

HR and People leaders responsible for employee experience and change communications will benefit from the show's recurring theme of human-AI balance. The tension between efficiency gains and the irreplaceable human quality of certain messages is examined from multiple angles, providing frameworks for decision-making rather than simple rules.

Communications technology professionals and AI product teams building tools for the IC market will find in this podcast an unfiltered source of practitioner needs, resistance points, and unexpected use cases. The guests reveal where existing tools fall short in ways that product surveys rarely capture.

What the episodes really reveal

Across the Season 1 episodes, a consistent pattern emerges: the most productive AI use cases in internal communications are not the obvious ones. Drafting assistance — the first thing every IC professional tries — quickly becomes table stakes. The more significant gains appear in earlier stages of the communications workflow: problem framing, audience analysis, message architecture, and scenario planning.

The AI agent episode with Rebecca Lindsay reveals a second pattern: automation in IC is less about volume processing and more about cognitive offloading. The value of an AI agent is not that it writes 50 emails instead of 5 — it is that it handles the low-cognitive-load tasks that fragment an IC professional's attention, freeing them for the high-stakes work that genuinely requires human presence.

Amanda Atkinson's episode surfaces a pattern that is rarely discussed openly: AI introduces a new class of error in IC. Not factual errors, which are well-documented, but tonal and cultural errors — outputs that are technically accurate but emotionally wrong for a specific organisational context. Managing this class of error requires IC professionals to develop a new editorial competency: AI output review as a distinct professional skill, not simply proofreading.

What this changes in practice

The cumulative argument across the series is that AI does not make internal communications easier — it makes it more demanding of the human practitioner. The editorial judgement required to evaluate, correct, and deploy AI outputs is more sophisticated than the judgement required to write a first draft from scratch. IC professionals who approach AI as a shortcut will produce worse communications. Those who approach it as a collaborator requiring active management will produce better ones.

This reframing has structural implications for IC teams. It argues against reducing headcount as AI adoption increases, and argues for investing in AI literacy as a core professional competency. It also repositions the IC function: if the strategic value of the role increases as AI handles execution, the profession's claim to a seat at the leadership table becomes stronger, not weaker.

For practitioners currently hesitant about AI, the series offers something more useful than reassurance: it offers a realistic picture of the learning curve, including the embarrassing experiments and the false starts, from peers who are navigating it without a roadmap.

The internal communications professionals who will define best practice in the AI era are not those who adopt the most tools, but those who build the clearest frameworks for when human judgement must remain the final word.

Discover all episodes of Unprompted: Real AI in IC and follow the series as Season 1 unfolds.

The conversations in this series are still in progress — tune in to hear IC practitioners report back in real time as they figure it out.

The podcast answers these questions

How are internal communications professionals actually using AI tools in their day-to-day work?

IC practitioners are experimenting with AI across content drafting, channel strategy, and increasingly as strategic thinking partners. Some are testing autonomous AI agents to handle repetitive comms tasks, while others focus on using AI to augment human judgement rather than replace it — particularly for sensitive or culture-specific messaging.

What are the biggest risks of using AI in internal communications?

The primary risk is over-reliance on AI outputs without adequate human review, especially for messages that require cultural sensitivity or leadership tone. Practitioners also flag the risk of eroding employee trust if communications are perceived as impersonal or automated — making the balance between efficiency and authenticity a recurring and unresolved concern.

Can AI function as a strategic partner in internal communications, not just a content tool?

Yes — advanced practitioners are moving beyond using AI for drafting and into using it for strategic scenario planning, audience analysis, and message sequencing. This shift requires IC professionals to develop new skills in prompt design and critical evaluation of AI-generated recommendations, rather than simply accepting outputs at face value.

What distinguishes successful AI adoption in IC teams from failed experiments?

Teams that succeed with AI in internal comms typically start with bounded, low-stakes experiments — a specific newsletter format, a single channel, a defined use case — before scaling. Those that struggle tend to deploy AI broadly without a clear framework for human oversight, leading to quality control issues and stakeholder pushback that sets adoption back significantly.

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Carly and Simon · Unprompted: Real AI in IC

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