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Kalman Tiboldi - CTO & Founder at GemOne-TVH - Simplify or Die: Why Complexity Is the Real IT Challenge
Italy Sep 25, 2025 Invitation Only Physical italian
Nel percorso verso l’AI e la trasformazione digitale, dati e automazione sono gli elementi centrali di ogni strategia tecnologica. Ma senza una governance chiara, rischiano di diventare non solo fonte di inefficienza, ma anche di rischi e incoerenza. Come garantire che i dati siano completi, accessibili e affidabili? Come automatizzare le operation IT e i processi aziendali mantenendo controllo, compliance e sicurezza? Durante questa roundtable esclusiva, organizzata da CIONET Italia e IBM, affronteremo: La governance come abilitatore di dati affidabili e automazione sicura. Come prepararsi a un’adozione dell’AI realmente scalabile. Il ruolo di controllo, resilienza e gestione del rischio nell’innovazione.
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Belgium Oct 16, 2025 Invitation Only Physical english
AI isn’t just another tool. It changes how we work, how we think, how we organise ourselves.Yet most organisations still approach it like a digital upgrade, deploying assistants, automating workflows, testing use cases inisolation.The results are predictable. Short-term wins. Long-term confusion.Effort spent. Value unclear.Many companies can’t connect AI to their actual strategic goals,and the promised ROI never materialises.At the same time, something deeper is shifting.AI can now reason, decide, adapt. Not just mimic processes butcontribute to them.The technology is evolving, but the way we implement it hasn’tcaught up.If your AI still fits inside a single department, you’re likely solvingthe wrong problem.If it works only for individuals, you're missing how your teamsactually deliver value.If it replaces people instead of supporting them, you're buildingfor today, not tomorrow.The next step isn’t more AI. It’s the right AI.Built for your business, your teams, your way of working.Not a tool to add but a structure to build around.Are we ready to treat AI as a shared capability, not a scatteredexperiment?Can we move beyond individual efficiency and build systems thatcollaborate, learn and adapt with us?Those are the questions we’ll explore at the round table.
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Germany Oct 28, 2025 Country Members Physical german
Am 28. Oktober lädt CIONET CIOs und Digital Leaders nach Köln ein: hier stellen wir reale Anwendungsfälle vor, in denen KI-Agenten Aufgaben autonom übernehmen, Prozesse beschleunigen und Entscheidungen vorbereiten – mit messbarem Nutzen für das Business.
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France Nov 4, 2025 Country Members Physical french
À l’ère des mutations géopolitiques et réglementaires, l’établissement d’une souveraineté numérique est devenu un élément stratégique essentiel pour les entreprises. Ce dialogue stratégique mettra en lumière le rôle fondamental du réseau dans la mise en place du contrôle, de la confiance et de la résilience. Nous explorerons comment une infrastructure moderne et résiliente permet d’appliquer des politiques de gestion des données et d’assurer la continuité opérationnelle. Ce dialogue stratégique, réservé à un groupe restreint de pairs, est conçu pour permettre aux leaders du numérique d’échanger sur l’un des enjeux les plus urgents aujourd’hui. Nous discuterons des réseaux « sovereign-ready » et débattrons des préoccupations croissantes autour de la souveraineté des données, qui motivent l’adoption de politiques de confidentialité et de protection des données de plus en plus strictes à l’échelle mondiale.
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Netherlands Nov 10, 2025 Public Physical english
CIONET Nederland vertrekt met een groep Nederlandse CIO's en digital leaders 10 t/m 12 november 2025 voor de geheel verzorgde CIO Innovation Trip naar de Web Summit in Lissabon, Portugal. Reis jij mee of neem je collega(s) mee!
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Unilever: Using AI to freeze out competition & discover “breakfast for dessert”
Unilever has used AI to sort through their structured data for years. Partnering with American, Chinese, Israeli and U.K. startups to analyze information from content people post and reactions to that content, Unilever has been able to unearth insights in gap areas in their marketing they would have otherwise missed.
Unilever, a British consumer goods company, made a sugary sweet move to freeze out their competition when they implemented the usage of twenty-six AI data centers across the globe to synthesize insights from a range of sources, including social listening, CRM, and traditional marketing research. Unilever owns over 400 brands spread across 190 countries, and thirteen of those brands have sales over a billion dollars. Such brands include Lipton, Sunsilk, Dove, Knorr, Magnum and hundreds of other food, vitamin, beauty and cleaning products. While Unilever has used AI to sort through their structured data for years, they recently took a deep dive into their qualitative data by gleaning through text, audio, social media and phone activity as a means to influence more of its marketing. Partnering with American, Chinese, Israeli and U.K. startups to analyze information from content people post and reactions to that content, Unilever has been able to unearth insights in gap areas in their marketing they would have otherwise missed.
A prime example is their development of Ben & Jerry’s cereal-flavored ice-cream (Fruit Loops and Frozen Flakes) after listening to over 50 songs in the public domain that had lyrics talking about “ice cream for breakfast.” One of the AI algorithms Unilever enlisted in a partnering startup recognized a data set that revealed an opportunity for a new product. Although Dunkin Donuts sold ice cream in the morning for years, Unilever never had the data to prove this customer pain point. As a result, ice cream companies like Ben & Jerry’s missed this niche market opportunity. With the new product on the shelves, competitors are now incorporating breakfast ice cream in their own name brand product lines, But that’s just the icing on the (ice cream) cake.
In addition to infiltrating the ice cream market, Unilever is using AI to pioneer the recruitment of executives and marketers in order to decrease the money and time spent invested in the hiring process. They currently spend over 100,000 hours hiring over 30,000 people a year and processing 1.8 million job applications. Partnering with Pymetrics, Unilever built an online platform that used the aptitude, logic and reasoning of a candidate acquired through a neuroscience gaming activity to sift through preliminary screening of applicants. Pymetrics used this information and measured it against the role for which they applied as well as the profiles of successful employees currently working at the company.
Unilever deployed video analyzing software in 2018 that introduced candidates into the second stage of the interview process where their facial expression, body language and word choice were scanned from the comfort of their own homes as they sat in front of their computers or mobile phones. The machine learning algorithm examines the candidate after listening to the candidates answer questions for 30-minutes and then determines who is a good-fit through a variety of natural language processing and body language analysis.
This automated screening system is programmed to look for cues in behavior that selects candidates who demonstrate “systemic thinking, resilience, and business acumen.” Unilever also uses this proprietary technology to deliver feedback to applicants by giving them a detailed list of how they did in the interview, what characteristics align with the company, what traits do not, and how to be more successful in the application process in the future. The irony is that artificial intelligence is actually allowing companies to be more human. Instead of large companies allowing applicants CV’s fall into the black hole, they are connecting and addressing areas of growth and improvement.
Within the first 90 days of adoption, Unilever doubled the amount of application to jobs success rate moving from 15,000 to 30,000. In addition, they hired their most diverse candidate pool by focusing on hiring non-white applicants and increasing representation 2,600 universities as opposed to 840 universities in the years prior. For the first time in their hiring history, they achieved gender parity in their hiring, as well as increasing socioeconomic representation by 20%. In terms of the efficiency of the hiring process, the average hiring time went from four months to four weeks and saved a cumulative 50,000 hours. Recruiters spent 75% less time reviewing applications, and the acceptance rate of offers to candidates went from 64% to 82%, and the completion rate of the Pymetrics game was 98%.
After the hiring process, Unilever incorporated machine-learning into their onboarding initiatives to help new employees adapt to new routines and corporate culture. They built a bot using natural language processing to understand important employee information that is retrieved for new candidates and acts as an HR specialist, IT assistant, and general logistical support that answers questions pertaining to parking, salary, reviews, and time-off allowances. A customer-service corporate bot varies with a consumer-facing bot in that it must appropriately identify the employees information by using geographical location, level of seniority and other differentiating information in order for real and authentic support to be provided.
Current data comes from internal sources like schedules, policy documents, guidelines and the warehouse of data that comes from the litany of questions employees pose everyday. This data is currently being used to develop learning material.
Other initiatives Unilver is piloting is their smart sourcing technology that uses satellite imagery, cloud computing and AI to help achieve sustainable commodity sourcing by monitoring the effect sourcing has on the environment and communities. Their goal is to help companies avoid waste by building out an algorithm that shows the “optimum probability curve of need, demand and consumption.”
Unilever is harnessing the latest advancement in AI to most past outdates recruitment practices and improving candidate and employee experiences. In addition, they are using AI to innovate and learn from their users to create products that people crave, and not just for breakfast.
Kalman Tiboldi - CTO & Founder at GemOne-TVH - Simplify or Die: Why Complexity Is the Real IT Challenge
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Isabelle Droll - CIO for Airline, Corporate, Hotels & Resorts and Sustainability at TUI - Data, Diversity, and Destinations
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Sharon Prior - CIO in transition - How Great Tech Leadership Begins with Business Thinking
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José Antonio López, Group CIO at TOUS - Jewels, Data & AI: Inside the Digital Transformation of TOUS
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Tom Tanghe - General Manager ITC EMEA at Daikin Europe - Reinventing the CIO Role
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CIOFEST 2025 - From Order Taker to Proactive Disruptor
Geopolitical tensions have dominated the headlines for over two years now. In this context, the cyber threat landscape is also evolving rapidly. The protection and security of critical infrastructure – both physical and digital – is becoming increasingly important.
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