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AI adoption is ubiquitous but nascent Enthusiasm for AI is strong, with 90% of organizations prioritizing it. 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.
At Gitex Global 2024, Core42, a leading provider of sovereign cloud and AI infrastructure under the G42 umbrella, signed a landmark agreement with semiconductor giant AMD. Collaborations between public and private organizations will be vital for the UAE to deliver on its ambitious digital agenda.
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. Step 2: Understanding competitors Competitive analysis IT leaders must understand the competitive landscape to position their organization for success.
When addressed properly , application and platform modernization drives immense value and positions organizations ahead of their competition, says Anindeep Kar, a consultant with technology research and advisory firm ISG. Is your organization overdue for an IT systems update? Here are seven signs it may be time to modernize.
Many organizations are dipping their toes into machine learning and artificial intelligence (AI). However, for most organizations embarking on this transformational journey, the results remain to be seen. And for those who are already underway, scaling their results across their organizations is completely uncharted waters.
Many are reframing how to manage infrastructure, especially as demand for AI and cloud-native innovation escalates,” Carter said. While Boyd Gaming switched from VMware to Nutanix, others choose to run two hypervisors for resilience against threats and scalability, Carter explained.
A modern data and artificial intelligence (AI) platform running on scalable processors can handle diverse analytics workloads and speed data retrieval, delivering deeper insights to empower strategic decision-making. Intel’s cloud-optimized hardware accelerates AI workloads, while SAS provides scalable, AI-driven solutions.
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.
To address this consideration and enhance your use of batch inference, we’ve developed a scalable solution using AWS Lambda and Amazon DynamoDB. The power of batch inference Organizations can use batch inference to process large volumes of data asynchronously, making it ideal for scenarios where real-time results are not critical.
To fully benefit from AI, organizations must take bold steps to accelerate the time to value for these applications. Adopting Operational AI Organizations looking to adopt Operational AI must consider three core implementation pillars: people, process, and technology. This is where Operational AI comes into play.
growth this year, with data center spending increasing by nearly 35% in 2024 in anticipation of generative AI infrastructure needs. This spending on AI infrastructure may be confusing to investors, who won’t see a direct line to increased sales because much of the hyperscaler AI investment will focus on internal uses, he says.
In a recent interview with Jyoti Lalchandani, IDCs Group Vice President and Regional Managing Director for the Middle East, Turkey, and Africa (META), we explore the key trends and technologies that will shape the future of the Middle East and the challenges organizations will face in their digital transformation journey.
With advanced technologies like AI transforming the business landscape, IT organizations are struggling to find the right talent to keep pace. The problem isnt just the shortage of qualified candidates; its the lack of alignment between the skills available in the workforce and the skills organizations need.
The software and services an organization chooses to fuel the enterprise can make or break its overall success. And part of that success comes from investing in talented IT pros who have the skills necessary to work with your organizations preferred technology platforms, from the database to the cloud.
Add to this the escalating costs of maintaining legacy systems, which often act as bottlenecks for scalability. The latter option had emerged as a compelling solution, offering the promise of enhanced agility, reduced operational costs, and seamless scalability. Scalability. Legacy infrastructure. Scalability.
AI practitioners and industry leaders discussed these trends, shared best practices, and provided real-world use cases during EXLs recent virtual event, AI in Action: Driving the Shift to Scalable AI. And its modular architecture distributes tasks across multiple agents in parallel, increasing the speed and scalability of migrations.
Much of this data must adhere to regulations for organizations to remain compliant, which is why they are often housed in a secure mainframe. The mainframe also often holds the most current and complete view of transactions within an organization. Four key challenges prevent them from doing so: 1.
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. Without these critical elements in place, organizations risk stumbling over hurdles that could derail their AI ambitions.
Besides, there has been a significant rise in SAP S/4HANA and cloud adoption, reflecting a broader shift toward scalable and efficient IT infrastructure, according to a report by Germanys largest SAP user group, DSAG. Larger companies, in particular, are leading the charge as they leverage cloud solutions to modernize their operations.
It represents a strategic push by countries or regions to ensure they retain control over their AI capabilities, align them with national values, and mitigate dependence on foreign organizations. This is essential for strategic autonomy or reliance on potentially biased or insecure AI models developed elsewhere.
In a survey from September 2023, 53% of CIOs admitted that their organizations had plans to develop the position of head of AI. According to Foundrys 2025 State of the CIO survey, 14% of organizations now employ CAIOs, with 40% of those reporting directly to the CEO and 24% to the CIO.
A platform-based approach to AI emphasizes building a scalable, reusable foundation that evolves with the organization, rather than developing costly, siloed solutions for individual use cases,” said Guan, supporting the notion that establishing standards to test outcomes of models is necessary. “A
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Much like finance, HR, and sales functions, organizations aim to streamline cloud operations to address resource limitations and standardize services. AI models rely on vast datasets across various locations, demanding AI-ready infrastructure that’s easy to implement across core and edge.
In this article, discover how HPE GreenLake for EHR can help healthcare organizations simplify and overcome common challenges to achieve a more cost-effective, scalable, and sustainable solution. Business resiliency, including greater access to consumption-based infrastructure, disaster recovery, and business continuity services.
CIOs are responsible for much more than IT infrastructure; they must drive the adoption of innovative technology and partner closely with their data scientists and engineers to make AI a reality–all while keeping costs down and being cyber-resilient. For CIOs, building an AI-enabled organization at scale can be challenging.
study suggests that while sub-Saharan Africa has the potential to increase (even triple) its agricultural output and overall contribution to the economy, the sector remains untapped largely due to lack of access to quality farm inputs, up to par infrastructure like warehousing and market. A McKinsey and Co.
Thats why, like it or not, legacy system modernization is a challenge the typical organization must face sooner or later. In general, it means any IT system or infrastructure solution that an organization no longer considers the ideal fit for its needs, but which it still depends on because the platform hosts critical workloads.
Today, tools like Databricks and Snowflake have simplified the process, making it accessible for organizations of all sizes to extract meaningful insights. Scalability and Flexibility: The Double-Edged Sword of Pay-As-You-Go Models Pay-as-you-go pricing models are a game-changer for businesses. The result?
Today, tools like Databricks and Snowflake have simplified the process, making it accessible for organizations of all sizes to extract meaningful insights. Scalability and Flexibility: The Double-Edged Sword of Pay-As-You-Go Models Pay-as-you-go pricing models are a game-changer for businesses. The result?
His first order of business was to create a singular technology organization called MMTech to unify the IT orgs of the company’s four business lines. Re-platforming to reduce friction Marsh McLennan had been running several strategic data centers globally, with some workloads on the cloud that had sprung up organically.
Once a strictly tech role managing an organizations internal needs, the CIO role has seen a massive tectonic shift. With technology rapidly shaping business outcomes, and the tech infrastructure supporting every aspect of business, CIOs much deservedly now occupy a seat at the table. IndiaMART is a tech-first organization.
A key point shared during the summit was how the Kingdoms organizations are increasingly investing in AI. The companys ability to provide scalable, high-performance solutions is helping businesses leverage AI for growth and transformation, whether that means improving operations or offering better customer service. Whats Next?
The tech industry quickly realized that AIs success actually depended not on software applications, but on the infrastructure powering it all specifically semiconductor chips and data centers. Suddenly, infrastructure appears to be king again. Enterprises can no longer treat networks as just infrastructure. on average.
Containers offer speed, agility, and scalability, fueling a significant shift in IT strategies. However, the reality for many organizations is that virtual machines (VMs) continue to play a critical role, especially when it comes to legacy or stateful applications.
But because of the expansive nature of its capabilities, many organizations are often paralyzed by the sheer breadth of possibilities. That’s especially true in the healthcare sector, where the dazzling future GenAI is trying to usher in is often limited by the shortcomings inside an organization’s legacy infrastructure.
Leveraging Infrastructure as Code (IaC) solutions allow for programmatic resource management, while automation and real-time monitoring are essential to maintaining consistency and minimizing operational risks. These components form how businesses can scale, optimize and secure their cloud infrastructure.
In todays dynamic digital landscape, multi-cloud strategies have become vital for organizations aiming to leverage the best of both cloud and on-premises environments. A prominent public health organization integrated data from multiple regional health entities within a hybrid multi-cloud environment (AWS, Azure, and on-premise).
As regulators demand more tangible evidence of security controls and compliance, organizations must fundamentally transform how they approach risk shifting from reactive gatekeeping to proactive enablement. 2025 Banking Regulatory Outlook, Deloitte The stakes are clear.
This organization, renowned for its commitment to children’s health, faced challenges in scaling its outreach efforts and enhancing patient experiences. However, their existing infrastructure posed significant limitations. Here’s how Perficient helped revolutionize their approach using Salesforce solutions.
His first order of business was to create a singular technology organization called MMTech to unify the IT orgs of the company’s four business lines. Re-platforming to reduce friction Marsh McLellan had been running several strategic data centers globally, with some workloads on the cloud that had sprung up organically.
As organizations expand globally, securing data at rest and in transit becomes even more complex. These providers operate within strict compliance boundaries, enabling organizations to host sensitive data in-country while leveraging robust encryption, zero-trust architectures, and continuous monitoring and auditing capabilities.
With products powered by Precision AI, your organization gains comprehensive asset visibility, risk assessment, vulnerability prioritization, virtual patching and seamless threat prevention, all without downtime. This approach not only reduces risks but also enhances the overall resilience of OT infrastructures. –
Its no longer a buzzword, Infrastructure as Code (IaC) is becoming crucial to building scalable, secure, and reliable operations for any organization leveraging the cloud. When combined with Terraform , HCP essentially becomes an effortless method of using the cloud to adopt and administer crucial infrastructure components.
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