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Analyst reaction to Thursday’s release by the US Department of Homeland Security (DHS) of a framework designed to ensure safe and secure deployment of AI in critical infrastructure is decidedly mixed. Where did it come from? The question, he said, is why the industry needs to do so.
The majority (91%) of respondents agree that long-term IT infrastructure modernization is essential to support AI workloads, with 85% planning to increase investment in this area within the next 1-3 years. While early adopters lead, most enterprises understand the need for infrastructure modernization to support AI.
Du, one of the largest telecommunications operators in the Middle East, is deploying Oracle Alloy to offer cloud and sovereign AI services to business, government, and public sector organizations in the UAE. In particular, AI’s integration into government services will streamline and improve efficiencies across multiple sectors.
The evolution of cloud-first strategies, real-time integration and AI-driven automation has set a new benchmark for data systems and heightened concerns over data privacy, regulatory compliance and ethical AI governance demand advanced solutions that are both robust and adaptive.
Machine learning operations (MLOps) is the technical response to that issue, helping companies to manage, monitor, deploy, and govern their models from a central hub. How to determine the benefits of an MLOps infrastructure. Download the report to find out: How enterprises in various industries are using MLOps capabilities.
Spending on compute and storage infrastructure for cloud deployments has surged to unprecedented heights, with 115.3% billion, highlighting the dominance of cloud infrastructure over non-cloud systems as enterprises accelerate their investments in AI and high-performance computing (HPC) projects, IDC said in a report. billion.
Indeed, many of the same governments that are actively developing broad, risk-based, AI regulatory frameworks have concurrently established AI safety institutes to conduct research and facilitate a technical approach to increasing AI system resilience. That series is available on Palo Alto Networks LIVEcommunity blog page.
If you manage transportation systems, you face fragmented tools and siloed approaches among government agencies, private operators and vendors. Modern transportation networks must address three pivotal security questions: Do you have comprehensive visibility into devices on your ITS network to safeguard critical infrastructure?
AI and machine learning are poised to drive innovation across multiple sectors, particularly government, healthcare, and finance. Data sovereignty and the development of local cloud infrastructure will remain top priorities in the region, driven by national strategies aimed at ensuring data security and compliance.
Some will grab the low-hanging fruit offered by SaaS vendors such as Salesforce and ServiceNow , while others will go deep into laying the enterprise infrastructure for a major corporate pivot to AI. Enterprises are also choosing cloud for AI to leverage the ecosystem of partnerships,” McCarthy notes.
Each interaction amplifies the potential for errors, breaches, or misuse, underscoring the critical need for a strong governance framework to mitigate these risks. Above all, robust governance is essential. As AI usage spreads, data frequently moves between different infrastructures, making it harder to keep track of and protect.
In today’s fast-evolving business landscape, environmental, social and governance (ESG) criteria have become fundamental to corporate responsibility and long-term success. CIOs manage IT infrastructure and foster cross-functional collaboration, driving alignment between technological innovation and sustainability goals.
critical infrastructure. Recent activity from the state-sponsored group Volt Typhoon, from the People’s Republic of China (PRC), has prompted federal agencies — including the Cybersecurity and Infrastructure Security Agency (CISA) and international partners — to issue urgent warnings and advisories.
This solution can serve as a valuable reference for other organizations looking to scale their cloud governance and enable their CCoE teams to drive greater impact. The challenge: Enabling self-service cloud governance at scale Hearst undertook a comprehensive governance transformation for their Amazon Web Services (AWS) infrastructure.
Savvy IT leaders, Leaver said, will use that boost to shore up fundamentals by buttressing infrastructure, streamlining operations, and upskilling employees. “As 40% of highly regulated enterprises will combine data and AI governance. That, in turn, will put pressure on technology infrastructure and ops professionals.
With the rise of digital technologies, from smart cities to advanced cloud infrastructure, the Kingdom recognizes that protecting its digital landscape is paramount to safeguarding its economic future and national security. The Kingdoms Vision 2030 is also a driving force behind its cybersecurity efforts.
Yet, as transformative as GenAI can be, unlocking its full potential requires more than enthusiasm—it demands a strong foundation in data management, infrastructure flexibility, and governance. Trusted, Governed Data The output of any GenAI tool is entirely reliant on the data it’s given.
Generative AI is a major investment and requires a substantial commitment in infrastructure and talent, Manry says. Do we have the data, talent, and governance in place to succeed beyond the sandbox? They need to have the data, talent, and governance in place to scale AI across the organization, he says.
AI and Machine Learning will drive innovation across the government, healthcare, and banking/financial services sectors, strongly focusing on generative AI and ethical regulation. Data sovereignty and local cloud infrastructure will remain priorities, supported by national cloud strategies, particularly in the GCC.
Agentic AI systems require more sophisticated monitoring, security, and governance mechanisms due to their autonomous nature and complex decision-making processes. Building trust through human-in-the-loop validation and clear governance structures is essential to establishing strict protocols that guide safer agent-driven decisions.
The Machines Can See summit will address the role of AI in sustainability and safety, exploring its applications in environmental conservation and public infrastructure. AI is at the core of this vision, driving smart governance, efficient resource management, and enhanced quality of life for residents and visitors alike.
In today’s rapidly evolving technological landscape, the role of the CIO has transcended simply managing IT infrastructure to becoming a pivotal player in enabling business strategy. Governance and metrics Establishing a governance structure ensures clear oversight and accountability for the execution of strategic initiatives.
The next phase of this transformation requires an intelligent data infrastructure that can bring AI closer to enterprise data. As the next generation of AI training and fine-tuning workloads takes shape, limits to existing infrastructure will risk slowing innovation. What does the next generation of AI workloads need?
China-linked actors also displayed a growing focus on cloud environments for data collection and an improved resilience to disruptive actions against their operations by researchers, law enforcement, and government agencies. In addition to telecom operators, the group has also targeted professional services firms.
infrastructure and AI-powered applications. Dr. Ömer Fatih Sayan, Türkiye’s Deputy Minister of Transport and Infrastructure, gave the event a powerful message on the nation’s commitment to innovation. 5G, together with AI, will fuel unparalleled growth, as AI depends on robust 5G infrastructure to realize its full potential,” he added.
CIOs who bring real credibility to the conversation understand that AI is an output of a well architected, well managed, scalable set of data platforms, an operating model, and a governance model. CIOs must be able to turn data into value, Doyle agrees. What of the Great CIO Migration?
The world must reshape its technology infrastructure to ensure artificial intelligence makes good on its potential as a transformative moment in digital innovation. Speaking of NTTs AI Charter, Mabrucco said NTT was looking to take a leadership role in AI governance and ethics.
With generative AI on the rise and modalities such as machine learning being integrated at a rapid pace, it was only a matter of time before a position responsible for its deployment and governance became widespread. Then in 2024, the White House published a mandate for government agencies to appoint a CAIO.
There are two main considerations associated with the fundamentals of sovereign AI: 1) Control of the algorithms and the data on the basis of which the AI is trained and developed; and 2) the sovereignty of the infrastructure on which the AI resides and operates.
Since many early AI wins drive productivity improvements and efficiencies, CIOs should look for opportunities where real cost savings can drive further innovation and infrastructure investments.
CIOs need to revamp their infrastructure not only to render a tremendous amount of data through a new set of interfaces, but also to handle all the new data produced by gen AI in patterns never seen before. A knowledge layer can be built on top of the data infrastructure to provide context and minimize hallucinations.
The council will be responsible for developing and implementing policies and strategies related to research, infrastructure and investments in artificial intelligence and advanced technology in Abu Dhabi. Launching the Dubai.AI Launching the Dubai.AI
The rise of AI, particularly generative AI and AI/ML, adds further complexity with challenges around data privacy, sovereignty, and governance. AI models rely on vast datasets across various locations, demanding AI-ready infrastructure that’s easy to implement across core and edge.
German software giant SAP is under investigation by US officials for allegedly conspiring to overcharge the US government for its technology products over the course of a decade. The investigation centers on more than $2 billion worth of SAP technology purchased by US government agencies since 2014.
The recent announcements about new cloud regions in the Middle East are set to further empower businesses, government entities, and individuals to fully embrace the digital future. The UAEs goal of becoming a global leader in AI is rapidly taking shape, with Oracles solutions empowering the government to rethink and reinvent its operations.
This development is due to traditional IT infrastructures being increasingly unable to meet the ever-demanding requirements of AI. This is done through its broad portfolio of AI-optimized infrastructure, products, and services. Behind the Dell AI Factory How does the Dell AI Factory support businesses’ growing AI ambitions?
Be it in the energy industry, e-government services, manufacturing, or logistics, the fourth industrial revolution is having a profound impact. All around the world, cities are eager to digitize government services and enhance overall digital access for its citizens. Digitalization is everywhere.
This success is a testament to the growing availability of venture capital, a dynamic entrepreneurial ecosystem, and government support for innovation-driven ventures. As Saudi Arabia continues to invest in infrastructure, education, and research, the deep tech startup ecosystem is expected to grow even more robust in the coming years.
In a world where software defines competitive advantage, traditional approaches to enterprise architecture focused on control, standards and governance are failing to deliver the speed and resilience businesses require. Like a citys need for reliable infrastructure and well-maintained services. Shawn McCarthy 2. Shawn McCarthy 3.
Securing these technologies is paramount in a region where digital infrastructure is critical to national development. Malik emphasized that compliance is not just an add-on for Huawei but a core part of their comprehensive assurance mechanism.
So even if we have AI systems that can use initially inputted data to create new data sets, we want to make sure there’s governance around that, and people are really involved in that process. And we need to create governance models that can be integrated across functions. What’s the benefit to them and to their organizations?
In todays fast-paced digital landscape, the cloud has emerged as a cornerstone of modern business infrastructure, offering unparalleled scalability, agility, and cost-efficiency. WALK: Establish a strong cloud technical framework and governance model After finalizing the cloud provider, how does a business start in the cloud?
However, the biggest challenge for most organizations in adopting Operational AI is outdated or inadequate data infrastructure. Ensuring effective and secure AI implementations demands continuous adaptation and investment in robust, scalable data infrastructures. To succeed, Operational AI requires a modern data architecture.
ADIB-Egypt has announced plans to invest 1 billion EGP in technological infrastructure and digital transformation by 2025. The investment in digital infrastructure is not just an extension of these efforts, but a strategic move to drive efficiency, innovation, and customer satisfaction to new heights.
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