November 25-27

In artificial intelligence (AI)-driven environments, creative and strategic decisions are increasingly shaped by predictive systems that anticipate and pre-structure outcomes. While these systems accelerate execution, they also risk eroding authorship, accountability, and trust.

This talk introduces a practical framework for preserving human decision-making in environments where content, ideas, and strategies can be generated at scale. Drawing on real-world experience in filmmaking and global brand communication, Marco Gentile explores how organizations can integrate AI without delegating responsibility.

Participants will leave with five concrete principles for using AI in creative and strategic processes, ensuring that automation enhances execution while preserving the human capacity to define meaning, make decisions, and remain accountable for outcomes.

Most organizations measure artificial intelligence (AI) success by the number of processes automated. Robinswood, a French mid-market consultancy, took a radically different approach: it built Night Agent, an autonomous AI system that writes, tests, and deploys production code without human developers.

In this session, Thibault Fritsch shares concrete metrics from 18 months of operating Night Agent in production, including 513 code stories delivered, deployment frequency, defect rates, and total cost of ownership compared with that of traditional development teams.

Attendees will learn how to design AI agent architectures that scale from prototype to production, apply a measurement framework to assess AI-generated code quality and business impact, address real failure modes and implement recovery patterns when running autonomous agents at scale, and determine when AI agents outperform human developers – and when they do not.

Pascal Wiscour-Conter explains that society has entered an era of exponential change, with multiple technologies disrupting how people live and work. The most notable and widely discussed of these, artificial intelligence (AI), affects how people communicate and, as Pascal argues, will “inherently force us to become human… again.”

In a hyper-connected, noisy world, people can choose to use “Creative AI” intentionally, harnessing AI as a productivity and creativity tool, instead of passively engaging in “Lazy AI.” As technological developments accelerate, people can learn to overcome the “cognitive gap” and leverage their unique metaskills to reach new heights while communicating more effectively.

Based on research in various fields, including neuroscience and epigenetics, it is possible to codify the process of crafting and applying meaningful storytelling, including within corporations. When vision, mission, value proposition, and culture are aligned, communication can maximise engagement, both externally with clients and internally with collaborators.

A “Story Guide” helps craft this “Corporate DNA” and incorporate it into all corporate communications. AI agents can be trained and used in a “writers’ room” setup to facilitate and enhance the process.

However, human creativity and curiosity cannot be replaced. AI can and should be used to enhance them meaningfully for the greater good.

Governments are among the world’s largest purchasers of technology and innovation, yet many organisations continue to approach them using traditional business-to-business (B2B) sales strategies that rarely succeed.
Drawing on more than three decades of experience spanning diplomacy, government relations, international business development, and AI-supported stakeholder engagement, Alistair Starling presents a practical framework for building successful business-to-government (B2G) relationships across Europe.
The session introduces the European Diplomats methodology for AI-powered commercial diplomacy – a structured approach that combines stakeholder mapping, policy intelligence, relationship architecture, and strategic engagement planning. Participants will learn how AI can accelerate the identification of key decision-makers, analyse complex institutional ecosystems, monitor policy developments, prioritise engagement opportunities, and strengthen long-term relationships with governments rather than relying on transactional sales.
Rather than focusing solely on procurement, the presentation demonstrates how organisations can engage at an earlier stage within policy, regulatory, and innovation ecosystems, allowing them to become trusted partners before procurement processes even begin.
Using practical examples from education, digital transformation, AI adoption, international partnerships, and government engagement across Europe, the session demonstrates how organisations have reduced time to engagement, improved stakeholder targeting, strengthened institutional partnerships, and expanded access to public-sector opportunities.
Attendees will leave with a practical framework, an implementation roadmap, a stakeholder-mapping methodology, and an AI-supported workflow, all of which can be applied immediately within their own organisations.

Telecommunications operators in the Asia-Pacific (APAC) region are beginning to treat artificial intelligence (AI) tokens as billable allowances, much like gigabytes of mobile data or minutes of voice. This session will explore what this emerging “AI token economy” means for telecommunications operators, why the APAC model matters, and how Western operators can adapt the concept for enterprise, sovereign, and regulated AI services.

The APAC market shows how operators can move beyond simply carrying AI traffic and begin packaging, rating, bundling, and billing for access to intelligence. By offering AI usage allowances to consumers, households, developers, small and medium-sized enterprises (SMEs), and larger enterprises, operators are positioning tokens as a recurring unit of consumption. However, this model does not transfer directly to Western markets, where consumers already access AI through global applications, hyperscalers, and device-native assistants. For many operators, the stronger opportunity is likely to be in business-to-business (B2B) services, including private inference, AI factories, graphics processing unit as a service (GPUaaS), sovereign AI platforms, edge AI, and AI model marketplaces.

The presentation will also focus on a critical technical and commercial issue: token visibility. Operators cannot reliably count AI tokens from encrypted network traffic alone; authoritative usage records must come from the AI gateway, model platform, marketplace, or provider settlement layer. This creates a strategic choice: remain a connectivity provider or move into the AI service control plane.

Stephen Douglas will also examine why AI-native key performance indicators (KPIs) are becoming essential. Traditional measures such as latency, throughput, and availability remain important, but the AI experience depends on new metrics, including time to first token, inter-token latency, tokens per second, task completion time, cost per token, tokens per watt, and tool-call latency. These metrics will shape assurance, service-level agreement (SLA) management, and monetisation models.

Attendees will leave with practical insights into three telecommunications AI monetisation models: connectivity-only services, AI assurance, and AI service brokerage. The core message is clear: APAC is making tokens the new gigabyte; Western operators could follow suit or position tokens as the new cloud consumption unit.

In ten years, will a company still exist – or only the version of it that survived AI? AI does not add to what a business does. It rewrites how that business creates value. One person with AI can now do the work of ten, and the bottleneck is no longer skill – it is the organisation. The companies that move first take the market. The ones that wait become the market.

Drawing on his own live company rebuild, Šarūnas Chomentauskas walks attendees through six principles that define an AI-native operating model, including integrated delivery that lets one person own end-to-end work; specialist functions as horizontal slices, not silos; and AI as the new professional service. Each principle is grounded in what worked, what broke, and what it cost. Attendees leave with a blueprint for the next decade – and a clearer view of which side of the line their company is on.

For thirty years, the web has split marketing into specialist silos, with organic search, paid media, public relations (PR), customer relationship management (CRM), and analytics each running its own team, budget, and dashboard. Artificial intelligence is now welding those silos back into one practice, because search engines, answer engines, ad surfaces, and buyer-facing agents all resolve to a single question about a company: can the machine read, trust, and cite the brand, and do real people feel warmly enough toward it to be quoted approvingly? The answer resolves to the oldest asset in the business: positive sentiment that converts to sales, running under the name marketers used before the web: branding.

In this talk, Marty Weintraub walks attendees through the full board he tracks every day, showing how organic, paid, PR, platforms, and measurement have quietly fused into one integrated discipline, and how the teams that govern brand facts as a shared source of truth will out-earn the federated teams still arguing over which budget should fund the work. Attendees will leave with a working model for running marketing as one connected system built for humans and machines at once.

Attendees will leave able to:

Map the five converging lanes of organic, paid, PR, platforms, and measurement as facets of one integrated brand system.
Build a single source of truth for brand facts so automated systems broadcast a clean, consistent signal.
Read brand-era metrics like share of voice, sentiment, and citation persistence alongside clicks to prove the sentiment-to-sales loop still closes.
Assign clear ownership for brand truth across the organizational chart before the next platform shift forces the decision.
Turn earned coverage and third-party validation into citation infrastructure that models can quote back to buyers.

English is a second language for most tech professionals in Europe. For Malcolm Stewart, English is his native language, but even he has witnessed it deteriorate and morph into something uncanny. In this talk, Malcolm Stewart shares the story of how he got his language back, offering tips and tricks on how to make AI-generated content sound authentic and on-brand.

What happens when an ad does not sit next to the content, but inside the answer itself? In this talk, Kotryna Kurt will break down how large language model (LLM)-powered ads, such as ChatGPT-style ads, change the rules of targeting, creative, and measurement for brands whose advertising strategies have been built around search, social, and display. She will walk through real scenarios of how conversations become inventory, what “intent” looks like in a chat interface, and how brands can show up without seeming intrusive or interruptive.

Dr. Rybachuk draws a direct parallel with pharmaceutical regulation: no drug company could distribute a product affecting brain development in 450 million children without long-term clinical trials. Yet this is precisely what is happening with educational AI today. The talk presents the case for neuroscience-based regulatory frameworks for EdTech, proposes a certification model analogous to pharmaceutical oversight, and offers a practical roadmap for developers and policymakers who want to act before legislation forces them to.