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research firm Vanson Bourne to survey 650 global IT, DevOps, and Platform Engineering decision-makers on their enterprise AI strategy. The Nutanix State of Enterprise AI Report highlights AI adoption, challenges, and the future of this transformative technology. AI applications rely heavily on secure data, models, and infrastructure.
But in conflict with CEO fears, 90% of IT leaders are confident their IT infrastructure is best in class. Still, IT leaders have their own concerns: Only 39% feel their IT infrastructure is ready to manage future risks and disruptive forces. No one wants to be Blockbuster when Netflix is on the horizon, he says.
Artificial intelligence is an early stage technology and the hype around it is palpable, but IT leaders need to take many challenges into consideration before making major commitments for their enterprises. With AI and data proliferating everywhere in the enterprise, AI and data are no longer centralized assets that IT directly controls.
The Middle East is rapidly evolving into a global hub for technological innovation, with 2025 set to be a pivotal year in the regions digital landscape. AI and machine learning are poised to drive innovation across multiple sectors, particularly government, healthcare, and finance.
The first is to foster a culture of agility, collaboration, and AI-driven innovation, driven in part by our new Office of AI. And third, systems consolidation and modernization focuses on building a cloud-based, scalable infrastructure for integration speed, security, flexibility, and growth.
Always on the cusp of technology innovation, the financial services industry (FSI) is once again poised for wholesale transformation, this time with Generative AI. GenAI-powered financial services use cases Across the sector, GenAI is empowering innovation and enabling new work patterns.
Ambitious businesses are already eyeing the next leap forward in AI technology fuelled by the growing imperative to deliver business success driven by digital innovation. 1] The next horizon for savvy enterprises seeking to automate at hitherto unseen levels of scale in 2025 is agentic AI. Its about every component working together.
Security risks can hold modernization back When modernizing IT infrastructure and applications, unforeseen issues such as security breaches and vulnerabilities are a major concern for organizations. Enterprises can appease these concerns by working closely with a trusted partner throughout the modernization journey.
The foundational tenet remains the same: Untrusted data is unusable data and the risks associated with making business-critical decisions are profound whether your organization plans to make them with AI or enterprise analytics. Like most, your enterprise business decision-makers very likely make decisions informed by analytics.
This involves the integration of digital technologies into its planning and operations like adopting cloud computing to sustain and scale infrastructure seamlessly, using AI to improve user experience through natural language communication, enhancing data analytics for data-driven decision making and building closed-loop automated systems using IoT.
Broadcom and Google Clouds continued commitment to solving our customers most pressing challenges stems from our joint goal to enable every organizations ability to digitally transform through data-powered innovation with the highly secure and cyber-resilient infrastructure, platform, industry solutions and expertise.
On a good day, this disconnect can lead to missed opportunities, slower decision-making and limited innovation. They are instrumental in navigating the complex intersection of technology and business, driving innovation, and accelerating decision-making in ways traditional leadership roles have struggled to do.
Savvy IT leaders, Leaver said, will use that boost to shore up fundamentals by buttressing infrastructure, streamlining operations, and upskilling employees. “As Their top predictions include: Most enterprises fixated on AI ROI will scale back their efforts prematurely.
Global professional services firm Marsh McLennan has roughly 40 gen AI applications in production , and CIO Paul Beswick expects the number to soar as demonstrated efficiencies and profit-making innovations sell the C-suite. Enterprises are also choosing cloud for AI to leverage the ecosystem of partnerships,” McCarthy notes.
Sevita is dedicated to providing adults, children, and their families innovative services and support designed to lead to growth and independence despite physical, intellectual, or behavioral challenges. You ’re building an enterprise data platform for the first time in Sevita’s history. What’s driving this investment?
That’s great, because a strong IT environment is necessary to take advantage of the latest innovations and business opportunities. On the other hand, there are also many cases of enterprises hanging onto obsolete systems that have long-since exceeded their original ROI. Technology continues to advance at a furious pace.
These new regions are a testament to Oracles confidence in the regions ability to drive innovation, especially as both countries ramp up their efforts to become global leaders in AI and cloud computing. Whats Next?
The next phase of this transformation requires an intelligent data infrastructure that can bring AI closer to enterprise data. The challenges of integrating data with AI workflows When I speak with our customers, the challenges they talk about involve integrating their data and their enterprise AI workflows.
It’s a position many CIOs find themselves in, as Guan noted that, according to an Accenture survey, fewer than 10% of enterprises have gen AI models in production. “What’s Next for GenAI in Business” panel at last week’s Big.AI@MIT It’s time for them to actually relook at their existing enterprise architecture for data and AI,” Guan said.
In a global economy where innovators increasingly win big, too many enterprises are stymied by legacy application systems. 2] The myriad potential of GenAI enables enterprises to simplify coding and facilitate more intelligent and automated system operations. The foundation of the solution is also important.
From customer service chatbots to marketing teams analyzing call center data, the majority of enterprises—about 90% according to recent data —have begun exploring AI. Today, enterprises are leveraging various types of AI to achieve their goals. To succeed, Operational AI requires a modern data architecture.
Simultaneously, the monolithic IT organization was deconstructed into subgroups providing PC, cloud, infrastructure, security, and data services to the larger enterprise with associated solution leaders closely aligned to core business functions.
The world must reshape its technology infrastructure to ensure artificial intelligence makes good on its potential as a transformative moment in digital innovation. John Gallant, CIO.coms Enterprise Consulting Director and Vito Mabrucco, NTT Corp. John Gallant, CIO.coms Enterprise Consulting Director and Vito Mabrucco, NTT Corp.
With the right AI investments marking the difference between laggards and innovative companies, deploying AI at scale has become an essential strategy in today’s business landscape. This development is due to traditional IT infrastructures being increasingly unable to meet the ever-demanding requirements of AI.
At the Mobile World Congress (MWC) 2025, Huawei has positioned itself at the forefront of technological innovation, showcasing its latest advancements in 5G, artificial intelligence, and cloud computing. The company unveiled its next-generation 5G infrastructure, promising faster speeds, lower latency, and greater efficiency.
The intersection of AI, software, and data management is set to revolutionize healthcare and will serve as a critical driver of medical innovation and improved patient outcomes. This improves system reliability and ensures that healthcare infrastructure remains robust and efficient.
Many are reframing how to manage infrastructure, especially as demand for AI and cloud-native innovation escalates,” Carter said. operator of 28 hotel and casino properties across the US, was negotiating a fresh enterprise agreement with VMware prior to its acquisition, reported The Register.
PM Ramdas, CTO & Head Cyber Security, Reliance Group adds, Organizations need complete visibility into security tool decisions that protect enterpriseinfrastructure. Nantha Ram notes that since the advent of AI, the C-Suite is motivated to incorporate AI-driven innovation seamlessly to not hamper cybersecurity resilience efforts.
With AI agents poised to take over significant portions of enterprise workflows, IT leaders will be faced with an increasingly complex challenge: managing them. If I am a large enterprise, I probably will not build all of my agents in one place and be vendor-locked, but I probably dont want 30 platforms.
CIOs often have a love-hate relationship with enterprise architecture. On the one hand, enterprise architects play a key role in selecting platforms, developing technical capabilities, and driving standards.
It has become a strategic cornerstone for shaping innovation, efficiency and compliance. As enterprises scale their digital transformation journeys, they face the dual challenge of managing vast, complex datasets while maintaining agility and security. In 2025, data management is no longer a backend operation.
Server equipment, power infrastructure, networking gear, and software licenses need to be upgraded and replaced periodically. In addition, enterprise IT must build its infrastructure to manage a maximum load. This could take weeks or, more likely, several months to accomplish.
With serverless components, there is no need to manage infrastructure, and the inbuilt tracing, logging, monitoring and debugging make it easy to run these workloads in production and maintain service levels. Legacy infrastructure. Maintaining and upgrading outdated systems can be resource-intensive and hinder innovation.
By eliminating time-consuming tasks such as data entry, document processing, and report generation, AI allows teams to focus on higher-value, strategic initiatives that fuel innovation. As AI usage spreads, data frequently moves between different infrastructures, making it harder to keep track of and protect.
Focused on digitization and innovation and closely aligned with lines of business, some 40% of IT leaders surveyed in CIO.com’s State of the CIO Study 2024 characterize themselves as transformational, while a quarter (23%) consider themselves functional: still optimizing, modernizing, and securing existing technology infrastructure.
Old rule: Stay in your lane New rule: Collaborate across the enterprise The CIO domain was once confined to the IT department. Its crossing product, engineering, and into the business, says Erik Brown, an AI and innovation leader in the technology and experience practice at digital services firm West Monroe.
FinOps, which was first created to maximise the use of Infrastructure as a Service (IaaS) and Platform as a Service (PaaS) models, is currently broadening its scope to include Software as a Service (SaaS). With more and more businesses moving to the Cloud, FinOps is becoming a vital framework for efficiently controlling Cloud expenses.
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.
Darren Adcock, product manager at Redcentric responsible for the company’s privately owned Infrastructure-as-a-Service offering, the Redcentric Cloud, has strong beliefs about what differentiates a cloud vendor from a cloud partner.
While data and analytics were not entirely new to the company, there was no enterprise-wide approach. As a result, we embarked on this journey to create a cohesive enterprise data strategy. Transforming business through enterprise data Graham Construction recently received a CIO Canada Award for our enterprise data project.
“We’re an IT company that’s very integrated into the business in terms of applications, and we put innovation at the center. The rise of the cloud continues Global enterprise spend on cloud infrastructure and storage products for cloud deployments grew nearly 40% year-over-year in Q1 of 2024 to $33 billion, according to IDC estimates.
A cloud analytics migration project is a heavy lift for enterprises that dive in without adequate preparation. Traditional systems often can’t support the demands of real-time processing and AI workloads,” notes Michael Morris, Vice President, Cloud, CloudOps, and Infrastructure, at SAS. But this scenario is avoidable.
As enterprises continue to grow their applications, environments, and infrastructure, it has become difficult to keep pace with technology trends, best practices, and programming standards. This post covers how to integrate Amazon Q Business into your enterprise setup.
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.
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