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Belgium 10-3-26 All Members Physical english

The Composable Enterprise: Engineered with AI

From modular business design to AI-driven pipelines, architectures, and operationsA composable enterprise is built on modular processes, API-driven ecosystems, low-code platforms, and cloud-native services. It promises speed and adaptability by allowing organisations to reconfigure their capabilities as conditions change. However, modular design alone does not guarantee resilience; the way these systems are engineered and operated is just as important.This is where AI is beginning to make a difference. Beyond generating snippets of code, AI is already influencing how entire systems are developed and run: accelerating CI/CD pipelines, improving test coverage, optimising Infrastructure-as-Code, sharpening observability, and even shaping architectural decisions. These changes directly affect how quickly new business components can be deployed, connected, and retired.In this session, we will examine how CIOs can bring these two movements together:Composable design is the framework for flexibility and modularity.AI-augmented engineering is the force that delivers the speed, quality, and intelligence needed to sustain it.The pitfalls of treating them in isolation: composability that collapses under slow engineering cycles, or AI that only adds complexity without a modular structure.The discussion goes beyond concepts to practical implications: how to architect organisations that can be recomposed at speed, without losing control or reliability. The outcome is an enterprise that is not only modular in design but also engineered to adapt continuously under real-world conditions.

Belgium 12-3-26 Physical english

The Third-Party Risk Reckoning: How far can you trust your vendors?

Tomato! Tomato! Tomato! Get your tomato now! Every vendor sells security. And every company depends on vendors, partners, and suppliers. The more digital the business becomes, the longer that list grows, and so does the attack surface. One weak link, and there is always one, or one missed update, and trust collapses faster than any firewall can react. What used to be a procurement checklist has become a full-time discipline. Questionnaires, audits, and endless documentation prove that everyone’s “compliant,” yet incidents keep happening. So it’s clear: the issue isn’t lack of policy, or maybe a bit, but mostly lack of visibility. Beyond a certain point, even the most secure organisation is only as safe as its least prepared partner (or an employee who hadn’t had their morning coffee). So how far can you trust your vendors? How do you check what you can’t control? And when does assurance become theatre instead of protection? Does it come at a different cost? Let’s exchange what works and what fails in third-party risk management: live monitoring, shared responsibility models, contractual levers, and the reality of building trust in a chain you don’t own. A closed conversation for those redefining what partnership means when risk is shared but accountability isn’t.

Belgium 19-3-26 Country Members Physical french

Vendor Detox: La consolidation vaut-elle le risque ?

Moins de Partenaires : La consolidation vaut-elle le risque ? Le problème est la prolifération des fournisseurs : trop d'outils causant de la complexité, une taxe d'intégration paralysante et de la redondance. La Taxe d'Intégration est le coût caché (en temps, en échecs et en ressources) d'essayer de faire fonctionner ensemble des systèmes disparates. Cet échange se concentre sur des stratégies éprouvées pour simplifier de manière agressive le parc technologique, consolider les fournisseurs et élever certains fournisseurs clés au rang de partenaires stratégiques.

March 12, 2026 Squad Session Invitation Only Physical english

The Third-Party Risk Reckoning: How far can you trust your vendors?

March 24, 2026 Squad Session Invitation Only Physical english

Killing Zombie Projects: Knowing when to stop, restart, or quietly let go

Every organisation has them, projects that keep running long after their purpose has faded. No one remembers who asked for them, but shutting them down feels riskier than keeping them alive. And eventually, people stay assigned, budgets stay allocated, and energy drains into work that no longer matters. Inertia at its finest.

March 26, 2026 Squad Session Invitation Only Physical english

Measuring Value in AI Initiatives: Defining ROI, accountability, and measurable outcomes in complex environments

AI projects continue to multiply, but proving their value remains difficult. Most organisations can track activity, not impact. Dashboards count pilots and models, yet few translate to measurable business outcomes. The result is familiar: success stories without clarity on what they actually delivered.

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Exscientia Uses Generative AI to Reimagine Drug Discovery

Exscientia uses generative artificial intelligence (AI) throughout the design-make-test-learn (DMTL) cycle to discover new therapies for patients quickly and relatively inexpensively.

“Using AWS, we reduce bottlenecks and accelerate the pipeline.”

David Hallett
Interim CEO and Chief Scientific Officer, Exscientia

Exscientia uses generative artificial intelligence (AI) throughout the design-make-test-learn (DMTL) cycle to discover new therapies for patients quickly and relatively inexpensively. Conventional drug discovery methods can take up to 15 years and cost over 2 billion dollars, with an average failure rate of 90–96 percent because scientists hunt for specific drug candidates among 10⁶⁰ bioavailable small molecules.

Built on Amazon Web Services (AWS), Exscientia’s innovative DMTL solution incorporates in silico design—using generative AI algorithms to design compounds in the cloud—and automated robots that make drug candidates in a lab. “We use generative AI to solve for efficiency and effectiveness,” says David Hallett, Exscientia’s interim CEO and chief scientific officer. “By predicting the molecular features of a safe and effective drug in silico, we minimize the number of costly experiments. Our platform, built in collaboration with the AWS team, is optimized for speed. We can repeat many DMTL learning loops, improving our drug candidates with every iteration.”

Using Generative AI for More Efficient Drug Discovery at Reduced Cost

Working backward from patient needs, Exscientia defines precise target product profiles (TPPs) that specify the complex combination of properties required by a well-tolerated and effective medicine. AI engineers design algorithms that generate panels of potential drug candidates to meet the TPPs. Active learning algorithms help expert designers to select a short list of drug candidates to synthesize in the lab, because they either move the TPPs forward or refine the models for future DMTL cycles.

Exscientia’s algorithms are trained on publicly available pharmacology data and proprietary in-house data generated from patient tissue samples, genomics, single-cell transcriptomics, and medical literature. By encoding data throughout the process and analyzing experimental results and previous design cycles, Exscientia can optimize upcoming design cycles and promote compound designs that are physically synthesizable. Using this synthesis-aware, iterative approach built on AWS, Exscientia makes 10 times fewer compounds than the industry average. “The idea is to iron out chemical liabilities to make safer and more effective drug candidates before we ever test them in patients,” says Hallett.

Exscientia has accelerated drug design by up to 70 percent while decreasing capital cost by 80 percent, compared with industry benchmarks. Using generative AI with other tools, Exscientia not only developed better drug candidates faster but also identified the right drug combinations to trial with patients in the clinic.

Cutting Time and Costs Using Automated Robotics to Make Better Medicines

Exscientia has incorporated cutting-edge chemistry synthesis and biology assay lab equipment with automation robots to avoid manual handling of lab equipment. Thus, its lab—orchestrated by AWS microservices—can operate 24/7 with minimal human supervision, “When our designs are ready, we can push a button, and within a few days, the robots are making the drug,” says Hallett. Maintaining extremely high levels of security and comprehensive disaster recovery, Exscientia will use this automated robotic capability to reduce the make and test timelines resulting from traditional offshore research contracts used across the industry.

As the company closes the loop with its robotic automation lab, it expects further productivity improvements. Data generated in the lab improves algorithmic predictions and speeds up DMTL cycles.

Introducing AI-Designed Molecules into Clinical Trials

Six molecules that Exscientia designed using AI have entered clinical trials. “Using AWS, we reduce bottlenecks and accelerate the pipeline,” says Hallett. “By switching on this highly integrated and automated DMTL loop, we can make drug candidates faster and more cost-effective.”

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Healthcare Circle

Digital Transformation is redefining the future of health care and health delivery. All stakeholders are convinced that these innovations will create value for patients, healthcare practitioners, hospitals, and governments along the patient pathway. The benefits are starting from prevention and awareness to diagnosis, treatment, short- and long-term follow-up, and ultimately survival. But how do you make sure that your working towards an architecturally sound, secure and interoperable health IT ecosystem for your hospital and avoid implementing a hodgepodge of spot solutions? How does your IT department work together with the other stakeholders, such as the doctors and other healthcare practitioners, Life Sciences companies, Tech companies, regulators and your internal governance and administrative bodies?

Telenet Business Leadership Circle

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Les Rencontres

Découvrez la dynamique du leadership numérique aux Rencontres de CIONET, le programme francophone exclusif de CIONET pour les leaders numériques en Belgique, rendu possible grâce au soutien et à l'engagement de nos partenaires de programme : Deloitte, Denodo et Red Hat. Rejoignez trois événements inspirants par an à Liège, Namur et en Brabant Wallon, où des CIOs et des experts numériques francophones de premier plan partagent leurs perspectives et expériences sur des thèmes d'affaires et de IT actuels. Laissez-vous inspirer et apprenez des meilleurs du secteur lors de sessions captivantes conçues spécialement pour soutenir et enrichir votre rôle en tant que CIO pair. Ne manquez pas cette opportunité de faire partie d'un réseau exceptionnel d'innovateurs numériques !

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CIONET is committed to highlighting and celebrating female role models in IT, Tech & Digital, creating a leadership programme that empowers and elevates women within the tech industry. This initiative is dedicated to showcasing the achievements and successes of leading women, fostering an environment where female role models are recognised, and their contributions can ignite progress and inspire the next generation of women in IT. Our mission is to shine the spotlight a little brighter on female role models in IT, Tech & Digital, and to empower each other through this inner network community.