Cloud, Edge, and AI: How to Maximize Their Integration
Edge computing represents a new evolutionary phase in digital transformation, and its technological capabilities have been significantly accelerated by AI. For some businesses, this convergence is already at the core of their operations. In the EU, the Dome project will help CIOs find certified cloud-edge-AI services. The market is booming: it could be worth $27 billion in 2024 and $270 billion by 2032.
The IT world is witnessing an increasingly close convergence of cloud, edge, and artificial intelligence. Data collection and processing at the edge, through connected devices, is an integral part of applications for Industry 4.0, as well as for precision agriculture, smart cities, logistics, and infrastructure. The vast world of IoT—which, in the industrial context, is more specifically known as IIoT (Industrial Internet of Things)—is closely tied to connectivity and the ability to process data locally, using artificial intelligence techniques, before sending the information to the cloud for further analysis to extract insights.
“Edge is the new battleground in the digital infrastructure arena, and its technological capabilities will be significantly accelerated and expanded by AI,” highlights Luis Fernandes, Senior Research Manager of European Infrastructure Strategies at IDC.
A clear example of how this cloud-edge-AI integration is strategic for businesses and competitiveness is the launch of the Dome project. Co-funded by the European Commission, this project aims to implement the Distributed Open Marketplace for cloud and edge services in the EU. It involves a consortium of around 40 European companies and organizations, led by the Italian company Engineering, which is developing a marketplace for certified cloud services (IaaS, PaaS, and SaaS), ensuring compliance with current and upcoming EU regulations.
The Dome marketplace opened this summer and is still expanding, already offering various services that CIOs and IT managers can explore. From 2025, services will be available for direct online purchase. Dome certifies cloud and edge services for compliance with EU standards, helping businesses and public administrations access verified offerings that meet European regulations.
Dome also focuses on integrating AI with cloud and edge, exploring partnerships with other initiatives to create a federated platform supporting AI services for companies and public entities. By ensuring certification and compliance, Dome facilitates the digital transformation and competitiveness of European cloud providers.
Cloud-Edge: Certified Services for EU Businesses
“The European cloud market is steadily growing in terms of volume, but the market share of European cloud providers is declining due to the dominance of large foreign providers, while the offerings from European providers remain highly fragmented,” explains Giuseppe Cafiso, Dome Project Manager and Senior Technical Manager for R&I Data & Analytics at Engineering. “This trend is concerning for the European Commission, which has initiated several strategies to support the development of the European cloud market.”
Dome fits into these strategies at the go-to-market stage, with the goal of enhancing the marketability of EU cloud operators.
In the cloud services landscape, Cafiso sees edge computing as a major opportunity for European providers, with the Dome marketplace poised to make a difference. EU operators can offer a much more extensive presence in the edge space than hyperscalers. Additionally, Dome certifies compliance: the EU has strict regulations for digital services offered in Europe (from GDPR to the European Cybersecurity Certification Scheme for Cloud Services, EUCS), and Dome ensures that the cloud services entering its marketplace meet these requirements, making it easier for CIOs.
“All European cloud providers are welcome—and even encouraged—to join, but they must present a set of certifications issued by industry bodies. Dome then verifies that these certificates are valid and properly applied to the proposed service. At that point, Dome issues a reusable digital certificate,” Cafiso adds.
The EU’s Dome Project Drives Innovation
Giuseppe Cafiso explains that Dome is essentially a catalog that federates local marketplaces. Dome’s marketplace federation strategy ensures that compliant services offered by various federated marketplaces are shared in a centralized catalog, allowing them to be replicated as commercial offerings across other federated marketplaces, starting with Dome’s central platform.
For each vendor, Dome conducts the same verification process for entry and publication in the marketplace, as the project is vendor-agnostic. This standardization ensures equal access and a level playing field for all providers.
“Many European operators still don’t sell their services online; the concept of online go-to-market for ICT services isn’t widespread in the EU,” Cafiso highlights. “Dome fills this gap. There are also many startups that bring innovation and can benefit from the support of an international marketplace like Dome, which offers a catalog and, soon, a complete infrastructure for online payments.”
The marketplace is already open, featuring a variety of services, including IaaS and solutions for smart agriculture, smart cities, and public administrations. As the catalog expands, it will attract even more market interest, further driving the growth and innovation of cloud-edge-AI integration in Europe.
Edge Computing at the Heart of Digital Evolution
“Edge is where data is generated and decisions are made,” writes Teresa Tung, Co-Lead of Accenture’s Data Practice. For example, it’s at the edge that autonomous vehicle automation happens, or where AI-driven orchestration operates in smart factories. According to Tung, businesses investing in edge as a driver of innovation—just as they did with cloud technologies in the past—are moving in the right direction to fully leverage AI’s potential. “Even if AI models are developed centrally, inference, and in some cases training, occurs at the edge,” Tung notes.
Connected edge devices—such as IoT objects or cameras—collect data, analyze it using AI algorithms, and derive trends and actionable insights that enable timely interventions. This data is then sent to cloud systems for further analysis, illustrating the growing integration of the cloud-edge-AI ecosystem.
“Today, the world is moving toward digital services that rely on cloud infrastructures. Many of these services, like connected factories, precision agriculture, and smart cities, also require edge processing, or ‘on-site’ data handling. At the same time, AI is a cornerstone of new digital services, and it depends heavily on cloud infrastructure,” emphasizes Giuseppe Cafiso. “Various vendors, like Engineering, are investing in this direction.”
“AI at the edge is still limited but growing, especially in use cases related to customer and employee experience,” adds Luis Fernandes of IDC. “For it to develop further, a scalable, standardized multivendor approach will be needed.” Fernandes also notes that IDC’s research, ‘IDC Syndicated Survey 2024: EMEA AI-Ready Infrastructure Survey 2024’, shows that 25-30% of edge adopters are using it extensively for workloads like customer and employee experience, process automation, and optimization. The key benefits identified by companies using edge include improved performance, productivity, and efficiency, followed closely by enhanced security, privacy, and compliance.
Cloud-Edge-AI Integration at the Heart of Business Operations
Fairconnect is a prime example of a company where cloud-edge-AI integration is the foundation of its business model. The company provides advanced technological services to insurance companies in Italy, France, and Germany. According to CEO and CIO Giovanni Maggiore, Fairconnect’s core business relies on data collection at the edge—whether from vehicles, homes, or smartphones, which he calls “the ultimate edge device for collecting relevant data.” Thanks to connected devices and edge data sent to the cloud, Fairconnect enables insurers to offer personalized insurance policies and actively manage emergencies and claims.
“The data managed by our systems is crucial for our insurance clients,” says Maggiore. “To ensure optimal performance, we’ve selected Cloudera, a cloud data management provider. We transfer data collected at the edge via connected IoT devices to Cloudera’s Hadoop-based cloud platform, which serves as an open data lakehouse. There, we perform analysis and processing using machine learning algorithms and other AI techniques.”
Fairconnect also develops its own proprietary firmware for connected devices, allowing intelligence to be distributed across devices and apps (on smartphones), leveraging the company’s edge computing capabilities. The data collected at the edge is filtered to eliminate unnecessary “noise” before being transferred to the cloud. This ensures that only relevant data is stored centrally, where Cloudera’s data management system and AI technologies come into play for further processing and insight extraction.
The Hybrid Cloud Model and Market Value
In this context, IDC research suggests that companies are increasingly opting for a hybrid cloud model. “Our data shows a growing preference for shared standard platforms over dedicated ones for most modern workloads, as well as the need for optimized systems to be deployed in specialized environments with privacy and security features, and custom power and cooling techniques,” notes Luis Fernandes. “All of this must be part of a broader hybrid cloud environment, as four out of five respondents prefer a hybrid approach for their IT infrastructure.”
Fairconnect, too, uses a hybrid cloud model. The company has a private cloud in colocation at an Equinix data center in Switzerland, but also leverages AWS’s public cloud for analytics and big data management with Cloudera technology, due to the massive data flows generated by its 800,000 active customers. This combination of open-source and proprietary software helps them meet their diverse needs.
“We’ve always used the open-source Hadoop stack for data analysis, but in recent years, as our business has grown, we’ve invested in enterprise distributions,” says CEO Giovanni Maggiore. “The public cloud gives us the scalability needed to align technology with business growth, offering a wealth of technological solutions that would be difficult to develop in-house. Hyperscaler providers also give us access to advanced technologies, from AI microchips to pre-trained generative AI models, lowering the barrier to adopting emerging technologies.”
Maggiore emphasizes that “any company focused on efficiently using its resources and managing multi-level data collection and processing can extract value from edge models. The more a business depends on data and delivering it to customers, the more it will experience cloud-edge-AI convergence. However, this also raises ethical challenges, particularly concerning data privacy and respecting those who generate the information.”
Respectful and proper data management is essential for the growth and widespread adoption of edge-IoT and AI-based solutions. According to Fortune Business Insights, the global edge AI market—which combines AI algorithms with local processing at the edge—was valued at $20.45 billion in 2023 and is expected to surpass $27 billion in 2024, reaching nearly $270 billion by 2032, with a compound annual growth rate (CAGR) of 33.3%. The industries expected to adopt these solutions the most include automotive, manufacturing, healthcare, energy, consumer goods, IT, and telecommunications. Europe, including Italy, is a significant part of this market, supported by Industry 4.0 policies.
Interview Source: Patricia Licata for CIO
