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How Connected Data Ecosystems Are Unlocking New Business Growth

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Cloud data ecosystems are the way forward for both industrial enterprises and the technology providers that support them, says Rónán de Hooge, Executive Vice President, Cloud Platform Business, AVEVA. An industrial environment where machines anticipate their own maintenance needs, supply chains innovate in response to real-time demand and resource shifts, and industries operate with unparalleled efficiency and minimal waste—all orchestrated by human experts?

That vision is fast becoming a reality as industries organize in response to the evolving business landscape. Disrupted supply chains, resource scarcity, changing customer needs and increasing regulation are all now commonplace in our integrated, digital-first economy. Success in this challenging environment depends on collaboration. When suppliers, distributors and other chain partners share business information, insights and best practices, they can create combined value that exceeds what each can achieve individually.

Businesses aren’t just connected to each other—they’re interdependent. In industry and elsewhere, the future of business increasingly relies on a connected data ecosystem. Data ecosystems represent the next wave of digital transformation. They leverage a trusted network of technologies to connect people with data from industrial operators and their partners.

With industrial data ecosystems, companies gain access to new capabilities or expertise they may not have in-house. More importantly, a unified view across the value chain, enables companies to discover crucial new insights and leverage broader expertise that enhance their abilities amid a changing business environment. When this industrial intelligence is unified and shared in the cloud, every value chain participant – including partners, regulators and customers – can visualize routes to better efficiency, productivity and sustainability.

Data is the bedrock of growth for the industrial enterprise

Businesses everywhere are now using connected data ecosystems with customers, suppliers, partners and operators. Such integrated networks may even straddle two or more formerly separate sectors. In all cases, they carry value for each player within the ecosystem, including for technology developers.

At the core of this collaboration is data. Industrial organizations now collect data in greater quantities and from a wider variety of sources than ever before. Too often, however, this strategic asset remains siloed at the point of collection because of technology, security and governance barriers, rendering it inaccessible to even internal departments.

Sharing data across an organization—as well as with external partners—gives every player within the ecosystem a contextual understanding of how to optimize their role in the value chain. Industrial organizations are therefore catalyzing digital transformation to create seamless collaboration across the lifecycle and unlock greater value and sustainability gains for all stakeholders.

Around the world, many players are already leveraging these platform services to drive positive outcomes on several fronts:

  • Drive efficiency through collaboration: Sharing data from a single source of truth empowers experts—regardless of location or technical background—to make better decisions faster.
  • Achieve environmental, social and governance (ESG) targets: Viewing unified value chain data in context helps surface the interdependent areas where sustainability action can have the greatest impact, such as greater circularity, improved efficiency, reduced emissions and better regulatory compliance.
  • Enhance individual and joint innovation: The competitive advantages gained from secure data-sharing communities strengthen trusted supplier and partner relationships. By adding context to real-time data, companies can expedite R&D, innovate together and mutually enhance competitive advantages.
  • Improve decision-making: Seamlessly connecting diverse data sources and extensible applications within an ecosystem gives businesses richer and more complete insights that can reduce operational costs and improve revenue outcomes.
  • Transform business for faster revenue: An industrial data ecosystem delivers value within hours instead of days or weeks. Accordingly, companies can achieve faster adoption, expand their market reach, and leverage economies of scale—all while reducing costs through lower software investments upfront and lower ongoing IT and maintenance expenses.
connected data ecosystems

How ecosystem building works for technology companies

As industries begin strategizing for the outcomes enumerated above, data ecosystems are helping them meet their needs. This kind of ecosystem thinking also supports innovation for technology providers and developer partners.

Such digital platforms bring together a multitude of complementary solutions and applications that can be tailored to specific business needs. At their core, such an industry data community is a network of interconnected software applications, services, and platforms that integrate seamlessly to enhance process efficiencies while uncovering new value for end customers.

With an open and neutral platform, partners can expedite the development of emerging technologies and services, driving agility and value for customers. The ability to securely share specific data streams within a standardized format and with granular control supports the development of new applications and value-added services – without compromising intellectual property.

This adaptability is a game-changer at a time of increasing cross-domain innovation, when developments in one field, such as artificial intelligence, can support progress in another area. Connected data ecosystems provide the advantages developers need in an ever-evolving industrial landscape.

Industry appetite and the flywheel effect

Different industrial sectors have either already added to, or are accelerating, their investment in connected data ecosystems. The vast majority (90%) of respondents in IDC’s 2023 Future of Industry Ecosystems global survey said they plan to maintain or accelerate their investment into such data ecosystems this year and next. Principal motivations included increasing business agility, better process automation, improved systems integration, and increased data-sharing with partners, including for ESG reasons.

The survey interviewed 1,288 C-suite and business line executives decisionmakers across energy, construction, process manufacturing, government and other industries around the world. Overall, the appeal of the connected data ecosystem could lie in its ability to accelerate the flywheel effect, a concept familiar to engineers.

With the flywheel effect, small wins accumulate over time to create a momentum that keeps the business growing. Likewise, within the kind of integrated data community described here, every player can expect to be able to recalibrate for resilience in real-time, driving incremental gains for all stakeholders on a continuous basis.

Whether for industrial enterprises, technology companies or developers, the whole truly then becomes worth more than the sum of its parts. The value of connected data ecosystems—and the potential exponential growth they promise—will be the foundation of our sustainable future.

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Intel Core Series 3 Extends AI-Ready Performance to Value and Edge Computing Segments

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Intel has introduced its latest Intel Core Series 3 mobile processors, aimed at expanding advanced computing capabilities to value buyers, commercial users, and essential edge deployments.

The launch reflects a broader shift in the industry, where performance, efficiency, and AI readiness are no longer confined to premium systems but are increasingly expected across all tiers of computing.

Built on the architectural foundations of Intel’s newer Core platforms and leveraging advanced process technology, the Core Series 3 processors are designed to deliver a balanced combination of performance, battery efficiency, and scalability. The focus is on enabling reliable, everyday computing while supporting emerging workloads, including AI-driven applications.

Driving Value-Oriented Performance

Intel positions Core Series 3 as a significant upgrade path for users operating on older systems. Compared to five-year-old PCs, the new processors deliver up to 47% improvement in single-thread performance and up to 41% gains in multi-thread workloads. GPU-based AI performance also sees notable enhancements, enabling improved responsiveness in modern applications.

This performance uplift is complemented by a strong emphasis on efficiency, with reduced processor power consumption and optimisations aimed at extending battery life for mobile systems.

AI Capability Moves to the Mainstream

One of the key differentiators of the Core Series 3 platform is the introduction of hybrid AI-ready architecture within the value segment. With support for up to 40 platform TOPS, Intel is enabling a new class of systems capable of handling AI workloads at the device level.

The platform also integrates modern connectivity standards, including Thunderbolt 4, Wi-Fi 7, and Bluetooth 6, ensuring compatibility with next-generation peripherals and networks.

Expanding into Essential Edge Deployments

Beyond traditional laptops, Intel is positioning Core Series 3 as a scalable solution for edge computing environments. The processors are designed to support a wide range of applications, including robotics, smart buildings, retail systems, and industrial deployments.

By combining AI acceleration with energy efficiency, the platform aims to deliver the performance required for real-time processing while maintaining operational reliability in diverse environments.

Ecosystem and Availability

Intel expects broad adoption across the ecosystem, with more than 70 designs from OEM partners set to launch across multiple form factors. Consumer and commercial systems powered by Core Series 3 are rolling out through 2026, while edge-focused deployments are expected from Q2 onwards.

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62% OF SAUDI LEADERS ARE FAILING TO USE THEIR DATA EFFECTIVELY, NEW CLOUDERA REPORT FINDS

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Cloudera, the only company bringing AI to data anywhere, today released its latest global survey, The Data Readiness Index: Understanding the Foundations for Successful AI, examining how prepared enterprises are to support AI at scale. Surveying more than 300 IT leaders in the EMEA region, including strong insights from Saudi Arabia, the report finds that while AI adoption is growing, most organizations still lack the data foundation needed for success.

The findings highlight a sharp contrast in how effectively organizations track their data. Nearly 9 in 10 EMEA  IT leaders claim complete visibility into where all their data resides, compared to just 32% of respondents in Saudi Arabia. Furthermore, 62% of Saudi respondents cite data access restrictions as a major roadblock to effective data use.

This gap highlights an emerging ‘AI readiness illusion’: the belief that organizations are prepared to scale AI even as critical data challenges remain unresolved.

“Enterprises aren’t struggling to adopt AI, they’re struggling to operationalize it beyond experiments,” said Sergio Gago, Chief Technology Officer at Cloudera. “AI is only as effective as the data that fuels it. Without seamless access to all their data, organizations limit the accuracy, trust, and business value that AI can deliver. You can’t do AI without data.”

AI Adoption is High, but ROI Remains Elusive

While AI is now deeply embedded across the enterprise, achieving consistent returns on investment remains difficult due to a sharp geographical divide in implementation hurdles. Across EMEA, the struggle is largely centered on the inputs, with data quality issues (18%) and cost overruns (16%) cited as the primary causes of lackluster ROI. However, Saudi Arabia presents a different challenge focused on execution. In the Kingdom, weak integration into workflows is the overwhelming barrier at 29%, nearly doubling the concern over data quality, which sits at 15%.

These regional nuances are further tangled by significant infrastructure limitations. Around 65% of respondents in KSA report that performance constraints have hindered operational initiatives, highlighting the immense difficulty of scaling AI across fragmented environments.

Bridging The Data Gap

At the core of these challenges is a significant disconnect between data optimism and operational reality.

The report highlights that 95% of KSA respondents are highly confident in their data, but only 32% of that data is currently fully governed. While this outpaces the broader EMEA region, where only 26% of data is governed despite 91% confidence, it highlights a critical execution gap that organizations are now racing to fill.

The Kingdom is uniquely positioned to bridge this divide with 100% of Saudi respondents ready to adopt new governance frameworks, and 79% being extremely willing to transform their operations. This regional commitment suggests that Saudi Arabia’s proactive approach will likely outpace its peers in the race toward AI and digital maturity.

Strategic Alignment and the Accountability Gap

While leadership in both the EMEA and KSA regions understands the necessity of data infrastructure, the execution and accountability frameworks are worlds apart. More than 90% of EMEA respondents report a well-defined data strategy tied directly to business objectives, while only over half  (53%) of Saudi Arabian respondents feel the same level of alignment.

Accountability and internal culture further widen this divide. In EMEA, 69% of leaders hold the CIO or CTO chiefly responsible for data readiness, whereas in Saudi Arabia, only 35% place ultimate responsibility on this role, indicating a more emerging ownership structure.

Beyond accountability and alignment, respondents in Saudi Arabia face a unique internal hurdle: 50% struggle with insufficient data literacy, while nearly a third (32%) cite a lack of executive sponsorship.

Data Readiness Will Define the Next Phase of Enterprise AI

As enterprise AI shifts from experimentation to execution, data readiness is emerging as the defining factor separating leaders from laggards.

Organizations able to fully access and govern all their data, wherever it resides, are far better equipped to deliver trusted, scalable AI. Notably, every respondent in the report indicated their organization is willing to adapt existing frameworks to support true data readiness.

As enterprises confront the limits of the AI readiness illusion, the path forward is clear: unlocking AI’s full value will require more than ambition; it will demand genuine data readiness. Those that close this gap will be best positioned to drive lasting impact and lead the next era of intelligent business.

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OPTRO LAUNCHES AI-POWERED GRC CAPABILITIES FOR THE MODERN ENTERPRISE WITH AI GOVERNANCE, CYBER RISK, AND CONTINUOUS CONTROL MONITORING

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Optro, the leading AI-powered GRC platform empowering enterprises to transform risk into opportunity, has announced several product capabilities to boost the effectiveness of customers’ risk management programs and enable them to innovate with AI confidently and responsibly. These capabilities follow shortly after the company changed its name to reflect what its AI-powered GRC platform enables: a single, coherent view across infosec, compliance, risk, and audit.

“Cyber risk now moves at machine speed, and legacy GRC tools can no longer keep up,” said Happy Wang, Chief Product and Technology Officer at Optro. “By leveraging AI to predict cyber risk, surface real-time insights, and accelerate mitigation, we help organizations shift from reactive reporting to proactive risk defense—building a true system of action that is ready for the AI era.”

Optro’s latest Risk Intelligence report found that AI governance program maturity is advancing, but unevenly. AI adoption continues to outpace AI governance, with 85 percent of organizations reporting they have integrated AI into their core operations or deployed it across multiple functions, while only a quarter report comprehensive visibility into employee AI use. At the same time, only 34 percent of organizations report their AI governance program is strategic and continuously improving. As these challenges become increasingly prevalent across industries, Optro has released the following product capabilities to help customers turn clarity into action:

  • Unified AI Governance: Serves as the essential orchestration layer for AI governance. By bridging the gap between policies & frameworks, your AI tech stack, and human oversight, this capability enables a unified, automated approach. We ensure that AI risks are visible, compliance is streamlined, and governance policies are enforceable across your entire organization.
  • Cyber Risk: Vulnerability Risk Monitoring: Provides a clear narrative of how a specific vulnerability affects an organization’s security posture and bottom line. This AI-powered functionality enables customers to understand the true business impact of a vulnerability. Included with IT and Cyber Risk Management (formerly IT Risk Management), it’s a paradigm shift in how organizations defend their digital perimeter.
  • Continuous Control Monitoring: With AI-driven recommendations for the controls best suited for automation, and a library of ready-to-use monitor templates, teams can bypass manual setup to start monitoring controls immediately. This capability helps customers reduce manual effort, improve consistency, and gain more timely visibility into control performance. By automating evidence collection and surfacing potential issues earlier, teams can address gaps more efficiently and move toward a more continuous approach to assurance.
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