Most conferences are built the same way. A committee brainstorms a theme, a team chases speakers, a designer lays out a program, and everyone hopes the real value happens in the corridors. Three days in Dubai this October worked differently.
The operating model was deliberately lean: two people shaping the ideas and running the room, and two part-time organisers steering the AI that handled the rest. Phil Midland and Dr Alex Lin of Strategic Renaissance 21 (SR21) designed and facilitated the workshop with the World Government Summit, while Khor Zijian and Lin Fanghong piloted the AI.
The result was not a faster version of a conventional conference. It was a different kind of event.
Finding the theme: “The Breaking Point”
The theme was derived, not brainstormed. Before naming a single session, AI worked through a large body of material: think-tank reports, academic papers, policy articles, market commentary, and news analysis on geopolitics, energy, capital flows, financial trust, and artificial intelligence. The question was what the world’s strategic conversation was converging on.
The signal was consistent. Across domains that rarely share a stage, analysts were describing systems under cumulative stress: supply corridors, debt and reserve-currency dynamics, trust in banks and institutions, and the speed at which AI was entering all of them. The shared question became the event’s framing: how much stress can the complex world system absorb before it breaks, and what does rebuilding look like?
AI surfaced the pattern, and the humans decided it was worth building a conference around. That division of labor held throughout.
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Sessions built around the people in the room
A good theme is useless if the room can’t speak to it. The second job for AI was turning “The Breaking Point” into sub-themes that matched what the confirmed participants actually knew.
The system took each attendee’s profile, publications, and professional background and mapped them against candidate angles. The program settled into four tracks:
- Track A: kinetic conflict and hard power
- Track B: capital and energy
- Track C: trust, in banking and human systems
- Track D: AI as multiplier and disruptor
The regional focus was the Middle East, North Africa, and the Indian Ocean. Each day moved from situational awareness to rebuilding. As the attendee list shifted, AI re-tested the track assignments against who was actually coming. Matching speakers to sessions by hand is slow and tends to default to reputation. Matching against demonstrated expertise produced sharper sessions.
It also fit the kind of room SR21 convenes. As SR21 Chairman Dr. Howard Morgan said:
“Every year this group gets a little better at seeing structural change before it becomes conventional wisdom. This year we’re pushing that a step further — turning what we see into commitments the room can actually be held to.”
We built the program to give that ambition somewhere to go.
Preparing the room before the room existed
The usual weakness of a high-level gathering is that participants arrive cold and spend the first day getting oriented. We remove that.
For each track, AI assembled a reference reading list, then synthesised it into a concise thematic paper and a podcast-style audio briefing. Participants could read at their desks or listen on the way to the airport. The goal was a shared baseline of facts and framings, so that conversation could start the minute the group convened.
Each paper also included proposed discussion points and prompts for facilitators. These were designed to cover every angle of a topic, including the uncomfortable ones, and to draw out insights from both the speakers and the audience. A quiet expert in the third row is often holding the most useful observation in the room. A well-built prompt gives the facilitator a reason to go and get it.
The papers were also built backward from the final day’s goal, which I’ll come to shortly. Each track’s reading mapped to the practical measures participants would draft on day three, so the preparation fed directly into the output.
The logistics: The least significant AI contribution
It’s worth being honest about this part, because most people assume AI’s value lies here. AI did the manual compilation: assembling the pre-conference materials into a single conference booklet, going through multiple versions as the program, venue, and schedule changed, and drafting press releases with quotes from relevant personalities.
This saved real hours, and it let two part-time organisers keep up with a moving target. But it was probably the least significant thing AI did. Formatting a booklet is a task any competent assistant could do. The real value was upstream, in how the content was chosen and prepared, and downstream, in what was extracted from the proceedings.
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In the room: Recording everything, analysing beyond the words
From 5 to 7 October at Emirates Towers, the proceedings were recorded for immediate analysis. The workshop brought together 48 senior leaders, including retired flag officers, sitting and former government ministers, sovereign-wealth and private-capital principals, technologists, and academics, all under the Chatham House Rule. Ministers from the UAE government attended, including H.E. Omar Sultan Al Olama, Minister of State for Artificial Intelligence, Digital Economy, and Remote Work Applications, and his deputy.
Conventional session summaries record who said what. Ours were built to capture what the conversation meant, and AI let us go well past the spoken word:
- Bias and opinion identification. We separated statements of fact from statements of position, and flagged the framing behind each.
- Data error citation. When a speaker quoted a figure that didn’t match the published record, the system noted the discrepancy and cited the correct source, rather than letting it pass into the summary as truth.
- Emotional and persuasive language. AI flagged loaded or persuasive wording, showing where the heat in a discussion was and where conviction outran evidence.
- External trajectory data. We cross-referenced on-stage discussions with prediction markets like Polymarket and Google Trends to see where public attention and market probabilities were heading. A topic was no longer just “discussed”. It came with a trajectory.
No human team could do this at the speed a conference demands. A person can listen to a panel, but cannot simultaneously fact-check every figure, score the rhetoric, pull live market data on each topic raised, and produce a structured summary within hours. The AI did the heavy lifting, and the participants got insights they couldn’t have extracted themselves.
Humans stayed where they add the most value: choosing which questions mattered, judging which signals were real, and deciding what the findings meant. AI extracted. People decided.
Day three: From diagnosis to Trust and Confidence Building Measures
A conference that only diagnoses a problem leaves people anxious and no better equipped. So the final day focused on practical Trust and Confidence Building Measures (TCBMs), concrete mechanisms to help the world be better prepared before it reaches the breaking point.
The drafting session drew on the tracks’ reference readings and insights from the previous two days. Because the workshop ran under the Chatham House Rule, I won’t detail the individual measures. In general terms, they covered AI system governance, the security of critical trade corridors, human oversight of automated decision-making, verification of de-escalation steps, and the interplay of energy, capital, and currency stability.
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Because the earlier work was systematically prepared and captured, participants didn’t start day three from scratch. The system also summarised the discussion into actionable insights and draft plans for moving forward. As a result, local and international participants alike left with drafted language, shared frameworks, and a clearer sense of who to talk to next. They left with tools and ideas, and were better prepared for what’s next.
What this means for event organisers
For Asia’s startup and venture community, which attends and runs more conferences than almost anyone, a few lessons stand out:
- Use AI upstream, not just at the admin layer. Theme derivation and session design are where it changes outcomes. Booklet assembly is a convenience.
- Prepare participants as seriously as you program speakers. Synthesised readings, audio briefings, and facilitator prompts raise the floor of every conversation.
- Treat the recording as raw material. An event’s most valuable output is often the analysis of what was said, not the footage.
- Keep humans on judgment. The team’s small size was a feature. Two part-timers could pilot the AI, and two facilitators could run the room, because the AI handled breadth.
What comes next
The engine behind the in-room analysis is a process we call Machine Augmented Insights Extraction (MAIE). In my next article, I’ll walk through the detailed, AI-assisted flow of MAIE: how a raw conversation becomes a structured, fact-checked, trajectory-aware set of insights, and how you can apply it to your own meetings, boards and events.
The Dubai workshop made one thing clear to me. A conference is no longer just a meetup and a networking event. It can be a deeper learning experience, one that gives participants far more than a presentation on stage can.
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The post Two part-timers and one AI orchestrator: Inside a Dubai conference on “The Breaking Point” — Part 1 appeared first on e27.