AI is emerging as an essential performance driver for industry: predictive maintenance, production optimisation, automated quality control, real-time inventory management, etc. The promises are numerous. But between strategic vision and operational reality, integrating AI into factories raises a number of challenges. How can we adapt infrastructures that are often heterogeneous or ageing? What data should be collected and how can it be used effectively? How can we guarantee interoperability with existing systems, while ensuring data security and sovereignty? How can we comply with regulatory frameworks (AI Act) and define responsibilities when AI is used in critical environments? How do you train your teams and maintain the employability of your employees? These are all key factors in ensuring an effective transition from experimentation to scale-up.

After taking over the industrial world, robotics is now entering a new era: that of services. Hospitality, logistics, healthcare, cleaning, security, catering, personal assistance… robots are leaving production lines to accompany, assist and sometimes even replace humans in everyday tasks. Which industries are currently building (both literally and figuratively) this new robotic workforce? What skills are required in these hybrid value chains combining electronics, AI, human-machine interfaces and design? What are the prospects for robotics engineers, start-ups and laboratories, but also and above all for the user sectors? And how can we anticipate the social, regulatory and ethical impacts of this automation of service professions? A deep dive into the new world of services.

At the heart of industrial transformation, the convergence of IT and OT systems is redefining production and plant management models. This integration is paving the way for a more agile, more connected industry, but it rests on a foundation that is as strategic as it is complex: data management. How can we effectively collect, structure, secure and exploit data from heterogeneous, often siloed and historically separate environments? What tools and architectures are needed to ensure that information flows smoothly and reliably between the field and the analysis systems? And above all, how can this mass of data be transformed into operational value, without compromising (cyber)security or digital sovereignty? As a critical issue, data management is central to the modernisation of production tools.

Attacks on security equipment at the edge of information systems, targeted ransomware, sophisticated phishing attacks, attacks on supply chains, theft and leakage of sensitive data, exploitation of vulnerabilities in everyday tools: the cyber security landscape is changing fast, driven by the increasing professionalism of cyber criminals and the proliferation of attack vectors. Cyber threats now come from everywhere and spare no-one: from very small businesses to major groups, including public authorities, healthcare and higher education establishments, no organisation is immune. Whatever its size, business sector or level of digital maturity. Against this backdrop, how can you anticipate tomorrow’s cyber attacks, strengthen your organisational resilience and ensure that cyber security becomes everyone’s business?

Artificial intelligence, robotics, connectivity solutions, space, cybersecurity, social networks, data management: from raw materials to electronic components, from hardware to software, from infrastructures to media… in all areas of tech, the United States and China are engaged in a race for speed and power that is monopolising resources (material, human and financial) and leaving little room for other ambitions and strategies. In its role as regulator, Europe is trying to lay down the rules for more ethical, sustainable and fair competition. A regulatory framework that should make it possible to regain control of the governance of technologies, create the conditions for digital autonomy and give European players (public and private) the means to lead the battle for innovation. So, faced with Donald Trump’s United States and Xi Jinping’s China, can Europe restore the balance of technological power?

Against a backdrop of energy tension and the transition to a more energy-efficient industry, intelligent sensors and edge computing are becoming key allies in the real-time optimisation of energy consumption. By combining fine-grained data capture and local processing, these technologies enable more responsive, more autonomous control that is better adapted to local constraints. But how do we move from intention to implementation? What types of sensors should be deployed, and for what uses? How can Edge computing ease the pressure on networks while guaranteeing rapid decision-making? And above all, how can these components be integrated into industrial environments that are often complex, heterogeneous and even ageing? Making better use of their energy data wherever it resides: a key challenge for combining energy efficiency, operational performance and digital agility.

Artificial intelligence is no longer limited to algorithms confined to the cloud or digital interfaces: it is increasingly embodied in machines capable of acting, interacting and adapting in the physical world. This is the emergence of Physical AI: a new frontier where AI and robotics converge to give rise to autonomous, mobile, perceptive and intelligent systems. From digital twins to surgical robots, humanoid robots and autonomous vehicles, Physical AI gives machines the ability to understand and master the laws of the real world. It enables machines to learn, adapt and interact with their environment in an autonomous and realistic way. Laying the foundations for a future where intelligence is no longer just virtual, but embodied. So how is AI profoundly transforming the physical capabilities of machines? What are the technical challenges involved in making AI work in real time in uncertain environments? What hardware and software architectures enable this autonomy in the field? And what are the concrete impacts for the sectors (industry, logistics, health, services)?

Europe’s cybersecurity regulatory landscape is expanding at a rapid pace: the NIS2 directive for critical sectors, the DORA regulation for the financial sector, the Cyber Resilience Act (CRA) for digital products, etc. These reference texts impose new obligations in terms of resilience, transparency, governance and security. But between legal complexity and operational impact, companies often struggle to turn these requirements into concrete action plans. Common points, specific features, upcoming deadlines: how do these three major regulatory pillars affect organisations’ cyber resilience strategies? What are the essential steps for compliance? How do these requirements fit in with existing cyber security systems? What are the new responsibilities for managers, CIOs and technology suppliers? Here are some answers, to help you move from a reactive approach to a controlled compliance strategy.

In a rapidly changing industrial world, where innovation, sustainability and competitiveness have become imperative, design is emerging as a major strategic lever. Going far beyond mere aesthetics, placing design at the heart of industrial challenges means that highly differentiating aspects can be addressed right from the design phase: consideration of uses, life cycle analysis and environmental impact, and consideration of {cyber}security issues (security by design). How is design transforming industrial production methods, relationships with users and economic models? What role do designers play in multi-disciplinary teams, and how do they reconcile creativity, technical constraints and security issues? A central role, often underestimated, in industrial competitiveness and resilience.

What if the IoT did away with batteries? Driven by advances in ambient energy recovery (light, thermal, kinetic, radio frequency, etc.) and ultra-low-power communications, the Ambient IoT is paving the way for a new generation of connected objects that are autonomous and invisible. Self-powered sensors, smart labels, ubiquitous networks: this discreet but profound revolution is redefining the paradigms of connectivity, with major impacts on logistics, health, industry and smart cities. With less maintenance, greater sustainability and an unprecedented mesh of our physical environment, the Ambient IoT offers technological promise, meets industrial challenges and brings new uses to the fore as we move towards a future where objects communicate wirelessly… and without batteries.

Against a backdrop of accelerating digitalisation and increasingly sophisticated cyber threats, the question is no longer whether an organisation will be targeted, but when and how. SMEs and SMIs in particular are on the front line when it comes to cyber attacks, which are often targeted precisely because they are less prepared than large companies. Yet it is possible to protect oneself effectively without mobilising resources that are out of reach. It all starts with a clear understanding of your exposure to risk. That’s why cyber risk analysis is becoming an essential step in anticipating vulnerabilities, prioritising security actions and strengthening resilience. How can we put in place a practical approach to assessing exposure to cyber threats? What are the tools and methodologies for identifying the relevant risks? How can technical issues be translated into strategic decisions? What practices should you adopt to build a clear, actionable risk map tailored to your sector? Discover the keys to moving from a reactive posture to a genuine culture of proactive risk management.

Which, AI or quantum, will save the planet? The list of (very real) problems that these two technologies could solve grows longer every day. Among them: finding more efficient or less rare materials for batteries, helping to capture CO2 more effectively, identifying less energy-intensive methods for synthesising the ammonia needed for fertilisers, and so on. And to achieve this, we need to take up nothing less than one of the greatest challenges facing science: modelling the interactions between atoms and molecules‘, explained the newspaper Le Monde earlier this year, in an investigation devoted to the ’match” between these two seemingly distinct, but profoundly interconnected sciences. How can AI algorithms take advantage of the power of quantum computing? How can machine learning methods help to optimise quantum architectures? Should we think of these technologies as two competing forces or as complementary particles destined to evolve together?

The integration of AI into embedded systems is gaining momentum, driven by promises of autonomy, optimisation and real-time adaptation. However, between limited computing power, energy constraints, safety requirements and development costs, porting AI models to embedded architectures poses real challenges and involves real optimisation choices, and even compromises on expected performance. So how can we clearly analyse the cost/benefit ratio of AI in embedded systems? In which cases is its integration really justified? What trade-offs need to be made between performance and consumption? How can the return on investment be assessed according to the applications (industrial, automotive, aeronautics, IoT, etc.)? These are all questions that need to be answered in order to make informed decisions about the future of your intelligent systems.

Faced with the challenges of relocation, competitiveness and labour shortages, robotics and cobotics are emerging as key drivers of reindustrialisation. Far from the fantasy of total automation, these technologies are becoming flexible, intelligent and collaborative tools capable of adapting to the realities of modern workshops, particularly in SMEs and mid-cap companies. Improved productivity, reduced drudgery, increased quality and adaptation to increasingly customised production: what roles do industrial robots and cobots play in the transformation of production lines? What are the conditions for successful robot deployment? How can robots be integrated into a human environment without disruption? What are the real gains in terms of costs, agility and resilience? Can intelligent robotics be a concrete catalyst for rebuilding a more modern, efficient and human industry?

Quantum computing, still in its infancy, already poses a credible threat to the traditional cryptographic algorithms on which information system security is based. Faced with this prospect, post-quantum cryptography (PQC) is no longer a theoretical possibility: it is becoming a strategic imperative to protect today the data that must remain confidential tomorrow. Algorithms currently being standardised (NIST), performance and implementation challenges, constraints for integration into existing systems and transition timelines for businesses and government agencies: is quantum-resistant cryptography technically and operationally ready? Discover the cryptographic changes that must be made without delay, or risk exposing critical infrastructure to future threats today.

The value of Threat Intelligence in SIEM and SOC environments is well established. But did you know that this flow of information, which plays an essential role in anticipating, detecting and neutralising cyber-attacks, can also enhance the capabilities of your Next Gen firewalls?

Predictive maintenance, process optimisation, automated quality control and supply chain improvement: AI is establishing itself as an essential driver of innovation in industry. However, despite its promise, AI still raises serious questions about its reliability, transparency, robustness and real added value in critical environments. Can we trust algorithms that are often perceived as opaque? How can we guarantee their performance in real-world conditions, far removed from idealised data sets? Who is responsible in the event of failure? And how can intelligent automation be reconciled with human expertise? Current limitations, explainability issues, model validation and best practices for deployment: how can manufacturers harness the potential of AI without sacrificing control, security or trust?

Collaborative robotics is rapidly growing in sectors as diverse as logistics, industry and healthcare. By enabling direct interaction between humans and robots, without cages or isolation, it opens up new possibilities in terms of efficiency, flexibility and reduced drudgery. But how can cobotics be used properly? What are the real benefits? What are the pitfalls to avoid in terms of ergonomics, safety, acceptability and return on investment? How can tools be adapted to real needs on the ground without giving in to fashion trends? While many industries have successfully integrated these new tools into their processes, is it always appropriate to transfer them to other sectors? Sharing experiences.

Connected objects, smart sensors, data platforms: the IoT has established itself as a catalyst for transformation in many sectors, from industry to energy, logistics and construction. But behind the technological promises, the success of an IoT project depends above all on a rigorous methodology, a suitable architecture… and careful anticipation of pitfalls. Sensor selection, connectivity, data management, cybersecurity, maintenance, interoperability, environmental impact: what are the best practices for designing, deploying and scaling an IoT project? Discover how to approach the IoT, not as a gadget experiment, but as a robust lever for performance and value.

In a context where industrial infrastructures are increasingly interconnected, managing access to control systems (SCADA, PLC, DCS, etc.) has become a key issue in operational cybersecurity. Remote access, external maintenance, network segmentation, user rights: the slightest flaw can open the door to attacks with serious consequences for production, security and business continuity. What are the specific challenges of identity and access management (IAM) in industrial environments? How can security, traceability and operational continuity be reconciled? What tools and methodologies can be used to control access without slowing down field teams or service providers? With securing access to industrial control systems no longer just a best practice but a regulatory requirement (NIS2 directive, IEC 62443 and ISO/IEC 27001 standards), critical infrastructure operators and industrial companies must implement robust, traceable access policies tailored to the specificities of OT environments.

Cloud, AI, 5G, IoT, robotics… Digital transformation is spreading to all sectors, but it relies on a very real physical foundation: the raw materials and electronic components that are essential for manufacturing equipment and infrastructure. However, these critical resources are under increasing pressure from geopolitical crises, shortages and tensions in supply chains, dependence on non-European suppliers, and environmental and ethical issues. So how can we build a digital sourcing system that is both sovereign, to secure our technological autonomy, and responsible, to meet sustainability and transparency requirements? What industrial, regulatory and technological strategies can enable partial relocation, better recycling, or a more sober and circular design of digital and technological projects?

Artificial intelligence is shaking up jobs, including digital ones. With some tasks being automated and powerful models helping with decision-making, what’s happening to technical skills (from coding to business engineering) in companies? How can engineers, developers, IT specialists – and even managers – evolve and develop new skills in order to understand how algorithms work, how they are implemented, how their quality can be controlled, how to ensure they are ethical and that they meet needs, etc.? How should organisations rethink training, recruitment and career paths? Between the promise of efficiency and the risk of disengagement, a balance must be struck between humans and machines, fundamental knowledge and augmented tools.

Faced with climate challenges, pressure on resources and the need for cities to adapt, regions are seeking solutions that are effective, sustainable and economical. What if artificial intelligence – in its frugal form, with low data and energy consumption – became a concrete lever for action for the ecological transition? In September 2024, eight new winners of the call for frugal AI demonstration projects for the ecological transition of regions (France 2030) joined the four regions already certified. How are these local authorities, water managers and planners using frugal AI approaches to optimise urban planning, better anticipate water needs and guide greening strategies? These innovative and concrete projects show that it is possible to combine digital sobriety, operational efficiency and territorial intelligence.

With cyberattacks on the rise and increasingly targeting smaller organisations, SMEs/SMIs and local authorities are now seen as the weak links in cybersecurity. Limited resources, heterogeneous infrastructure and a lack of awareness mean that these players are highly vulnerable, despite performing functions that are essential to the economy and everyday life. However, there is a clear mismatch between the specific needs of these organisations and the current offering in terms of cybersecurity. In this context, what responsibilities do public authorities, cybersecurity service providers and contractors have? How can we build a more accessible, clearer and better tailored cybersecurity offering that takes into account their constraints, in order to rethink cybersecurity that is trustworthy and adapted to the realities on the ground?

Against a backdrop of trade wars (US-China) and military conflicts (Ukraine-Russia), ever-increasing threats and increasingly well-orchestrated attacks, and in an almost monopolistic cyber-economic landscape, can Europe today create the conditions for effective, sovereign cyber-security? Despite highly advanced technologies, increasing funding and a favourable regulatory environment, the European cyber sector faces a number of challenges if it is to create champions capable of scaling up quickly. These include, first and foremost, legal harmonisation at EU level and changes to the rules on competition and public procurement – the creation of a Buy European Act – to provide European cyber companies with orders and contracts. Without doing without American solutions, or copying their model, can we develop a form of sovereignty or strategic autonomy in cyber matters?

In a world where robotics is becoming increasingly autonomous, precise and responsive, connected sensors and imagers are becoming the eyes, ears and nerves of intelligent machines. Thanks to the IoT, robots no longer simply perform tasks: they perceive their environment, adapt to it in real time and optimise their performance. How is the convergence of smart sensors, embedded vision, connectivity and edge computing power enabling robotics to become more agile, more economical and better integrated into industrial, agricultural and urban environments? What are the latest advances in robotic perception? How can data reliability be guaranteed in complex environments? And what technical and ethical challenges will these new capabilities pose?

Faced with the limitations of the linear ‘extract, produce, dispose’ model, new economic paradigms are emerging: the functional economy (selling a service rather than a good) and cooperation, the circular economy, pooling, reuse and simplicity. In this profound transformation of business models, digital technologies are no longer just tools for optimisation: they are becoming catalysts for systemic change. Smart sensors, digital platforms, blockchain, AI, predictive maintenance and other technologies are enabling us to rethink value in terms of usage, sustainability (keeping things in working order) and impact, rather than ownership. Which sectors and industries are leading the way? How can technological innovation be combined with changing business models? What obstacles (economic, cultural, regulatory) still need to be overcome?

At a time when the ecological transition is forcing us to rethink our digital habits, sobriety is becoming imperative. Bucking the trend, cybersecurity systems are based on increasingly heavy architectures: multiple logs, redundant infrastructure, intensive encryption, real-time monitoring, long-term storage, etc. While these practices are essential to ensuring system security, they also generate a growing environmental footprint that is often overlooked in digital sobriety assessments. So how can we reconcile digital security with the demand for sobriety? Is it possible to secure systems in other ways, with less complexity, less data and a smaller footprint? Event log reduction and intelligent governance, selective encryption, Zero Trust and Edge computing architectures, security data retention periods, and the sharing of cyber tools at sectoral or regional level: what approaches can reduce environmental impact without exposing organisations to risk?

What if virtual worlds became intelligent? The convergence of virtual reality and artificial intelligence is ushering in a new era of immersive interactions that are more natural, adaptive and personalised than ever before. Thanks to AI, virtual environments no longer simply simulate: they react, learn, anticipate and adjust in real time to the behaviour, emotions and preferences of each user. VR environments generated or dynamically modulated by AI, intelligent and responsive non-player characters (conversational agents, virtual companions, behaviour simulators), real-time processing, data collection and analysis in immersive environments, embedded AI: the challenges are numerous. And so are the questions: what data should be captured, what biases should be addressed, and what user control should be provided? Whether in training, healthcare, industry, design or entertainment, the convergence of AI and VR promises intelligent and deeply personalised immersion.

Artificial intelligence is at the heart of economic, industrial and societal transformations. But at a time of climate change and pressure on resources, a paradox arises: AI, which is both energy- and data-intensive, is also presented as a lever for optimising consumption, improving efficiency and driving the energy transition. In this context, is AI a credible ally for energy efficiency, or will it accelerate energy demand? Can it really contribute to decarbonisation without exacerbating the problem it claims to solve? The energy impact of developing AI models, the role of frugal AI and its limitations, regulatory frameworks and methodologies for assessing the real footprint of AI solutions, the responsibility of designers, users and decision-makers in balancing performance and impact, and the uses of AI in different sectors (network management, construction, mobility, industry) are at the heart of the strategic challenges surrounding the place that AI can (or must) occupy in a sustainable future.

Connected objects, sensors, networks, platforms: behind the operational benefits of IoT projects lies an environmental footprint that is still poorly understood, from component manufacturing to data exploitation. How can we design objects that are less energy-intensive, more sustainable and easier to repair? How can environmental criteria be integrated from the specification phase onwards? What tools and benchmarks should be used to measure, compare and decide? And how can these approaches be reconciled with the economic and technological constraints of the market? Eco-design and life cycle assessment (LCA) are two key approaches and concrete levers for reducing the environmental impact of IoT systems.

With the new European Machinery Regulation set to come into force in January 2027, cybersecurity is becoming a regulatory requirement for manufacturers, integrators and operators of industrial equipment. Designed to address the growing risks associated with the digitisation of machines and the interconnection of systems, this regulation imposes new IT security requirements from the design stage and throughout the entire life cycle of equipment. This new legal framework has concrete consequences for industrial players. What cyber requirements must be incorporated into design and conformity assessment? How can a ‘cybersecurity by design’ approach be implemented that is compatible with industrial processes? Find out how to prepare for secure and long-lasting compliance of your equipment and facilities.

Faced with ecological, social and economic challenges, the smart city can no longer be reduced to an accumulation of technologies. While high-tech solutions (sensors, AI, data platforms, digital twins) promise optimised management of urban services, they are not enough to guarantee more resilient, inclusive and sustainable territories. Conversely, low-tech approaches (simplicity, reuse, citizen participation, living solutions) provide concrete and accessible answers, but sometimes struggle to integrate with complex digital systems. So how can low tech be integrated into interconnected urban systems? What criteria should be used to decide between technological innovation and frugal solutions? What impact will this have on governance, the design of public services and citizen participation? The balance between high tech and low tech must be struck in the service of real uses and local needs in order to design a smart, fair, frugal and liveable city.

The Zero-Trust model is emerging as a strategic response to modern threats, based on a simple principle: never trust, always verify. But between stated ambitions and the reality of existing information systems, integrating Zero-Trust remains a major challenge for businesses and public institutions alike. How can you assess your organisation’s readiness for this paradigm shift? How can you integrate Zero Trust principles into an existing IT system without rebuilding everything? Which technological building blocks should you use (identity, micro-segmentation, supervision, IAM, SASE)? What governance should you put in place to align security, business and IT? There are many technical, organisational and operational challenges associated with implementing Zero Trust in complex, often heterogeneous and interconnected environments.

When faced with a cyberattack, every minute counts. Beyond technical emergency measures, the relationship with law enforcement agencies becomes a key lever for an effective, coordinated response that complies with legal obligations. However, many organisations still approach this cooperation in a rush, without a clear framework or advance strategy. When and how should you alert the public prosecutor’s office, the police or the specialised gendarmerie? What information should be shared, in what form, and with what guarantees of confidentiality? How can you balance the requirements of the investigation, business recovery and crisis communication? Clarifying the legal, operational and organisational issues related to cyber crisis management in conjunction with the relevant authorities enables collaboration based on trust, responsiveness and compliance.

Space is no longer just a playground for state agencies: it is becoming a territory of economic opportunity where private giants, ambitious start-ups and emerging powers meet. Extraction of lunar or asteroidal resources, satellite constellations, orbital logistics, space tourism… The industrialisation of space is underway, driven by massive private investment and a global race for technological competitiveness. But behind this craze for ‘New Space’ lie strategic and structural questions. What business models are viable in the medium term? What infrastructures need to be developed to support a sustainable space value chain? How can we manage the risks – legal, environmental, geopolitical – in a space where the rules are still vague? In short, will space be the scene of a techno-economic Wild West, or will it become the next great industrial revolution of our time?

Following an initial session at SIDO 2024 devoted to the emergence of generative design and its impact on design and engineering (the role of designers and engineers, understanding programming and algorithmic principles, and collaborative approaches to technology), the speakers will continue the dialogue in season 2. We will see how AI ‘hallucinations’ are not necessarily seen as a flaw, but rather as a driver of creativity, where every error, every bias and every deviation is an opportunity to redefine our conceptions of what is possible. What if the digital unconscious became the new frontier of creation?

Cybersecurity is now a strategic issue for all organisations. But you still need the right talent to implement it. Against a backdrop of growing threats, companies are facing a chronic shortage of skilled professionals, exacerbated by increasing regulatory requirements, the diversification of cyber professions and the global war for talent. What profiles are really in demand today, and what skills do they require? How can you attract and retain talent in a highly competitive field? What role do work-study programmes, retraining, hybrid career paths and self-taught skills play? How can you rethink your recruitment criteria in the face of rapidly evolving technologies and threats? Discover practical insights to adapt your practices, open up the skills pool and build strong, sustainable cyber teams.