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The EU has completed a very important initiative by approving one of the worlds first regulations on AI, in an anthropocentric function, protecting fundamental rights and guaranteeing innovation, Valentini continues. It is not easy to master this framework, and AI Pact can also help with the guidance provided by the AI Office.
In todays rapidly evolving business landscape, the role of the enterprise architect has become more crucial than ever, beyond the usual bridge between business and IT. In a world where business, strategy and technology must be tightly interconnected, the enterprise architect must take on multiple personas to address a wide range of concerns.
1] The limits of siloed AI implementations According to SS&C Blue Prism , an expert on AI and automation, the chief issue is that enterprises often implement AI in siloes. Without the necessary guardrails and governance, AI can be harmful. Automation takes care of end-to-end processes while also providing a detailed audit trail.
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.
For CIOs leading enterprise transformations, portfolio health isnt just an operational indicator its a real-time pulse on time-to-market and resilience in a digital-first economy. In todays digital-first economy, enterprise architecture must also evolve from a control function to an enablement platform.
Air Force technologist turned enterprise security visionary, Marc is leading a security transformation that is less about red tape and more about unleashing speed, agility, and resilience at scale. Marc offers a bold new blueprint for technology leaders navigating an era where cybersecurity must scale with innovation. A former U.S.
billion deal, highlighting the growing enterprise shift toward AI-driven automation to enhance IT operations and service management efficiency. After closing the deal, ServiceNow will work with Moveworks to expand its AI-driven platform and drive enterprise adoption in areas like customer relationship management, the company said.
On October 29, 2024, GitHub, the leading Copilot-powered developer platform, will launch GitHub Enterprise Cloud with data residency. This will enable enterprises to choose precisely where their data is stored — starting with the EU and expanding globally. As a by-product, it will support compliance.”
Enterprises have progressively adopted new waves of automation paradigms from simple scripts and bots to robotic process automation (RPA) and cloud-based automation platforms. This paper explores the emergence of agentic AI in the enterprise through three key themes: Core properties of a true agentic system. a complexity tradeoff).
This is particularly true with enterprise deployments as the capabilities of existing models, coupled with the complexities of many business workflows, led to slower progress than many expected. Michael Hobbs, founder of the isAI trust and compliance platform, agrees. I see this taking shape in 5 key areas.
The first is to foster a culture of agility, collaboration, and AI-driven innovation, driven in part by our new Office of AI. Were piloting Simbe Robotics Tally robots, which improve on-shelf availability, pricing accuracy, promotional compliance, and supply chain operations. Its a three-pronged effort.
Enterprise applications have become an integral part of modern businesses, helping them simplify operations, manage data, and streamline communication. However, as more organizations rely on these applications, the need for enterprise application security and compliance measures is becoming increasingly important.
Enterprise use of artificial intelligence comes with a wide range of risks in areas such as cybersecurity, data privacy, bias and discrimination, ethics, and regulatory compliance. If organizations dont already have a GRC plan in place for AI, they should prioritize it, says Jim Hundemer , CISO at enterprise software provider Kalderos.
AI, once viewed as a novel innovation, is now mainstream, impacting just about facet of the enterprise. Over the next 12 months, IT leaders can look forward to even more innovations, as well as some serious challenges. As 2025 dawns, CIOs face an IT landscape that differs significantly from just a year ago.
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.
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. This type of data mismanagement not only results in financial loss but can damage a brand’s reputation. Data breaches are not the only concern.
SLMs catch the eye of the enterprise Nicholas Colisto, CIO at Avery Dennison, credits the rise of agentic AI as one reason fueling greater interest in SLMs among CIOs today. Thats 100% accurate, says Patrick Buell, chief innovation officer at Hakkoda, an IBM company. Microsofts Phi, and Googles Gemma SLMs.
By Katerina Stroponiati The artificial intelligence landscape is shifting beneath our feet, and 2025 will bring fundamental changes to how enterprises deploy and optimize AI. Natural language interfaces are fundamentally restructuring how enterprises architect their AI systems, eliminating a translation layer.
Chinese AI startup, DeepSeek, has been facing scrutiny from governments and private entities worldwide but that hasnt stopped enterprises from investing in this OpenAI competitor. Enterprises are looking for cost-effective, open-weight AI alternatives as proprietary AI models remain costly and restricted.
The 2024 Enterprise AI Readiness Radar report from Infosys , a digital services and consulting firm, found that only 2% of companies were fully prepared to implement AI at scale and that, despite the hype , AI is three to five years away from becoming a reality for most firms. Is our AI strategy enterprise-wide?
An agentic era needs a platform that brings AI, data, and workflows together, and that should be an open, connected, enterprise-ready platform, said ServiceNows chief innovation officer Dave Wright in a press conference last week. We look at it as distributed intelligence across the enterprise.
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.
Technology has shifted from a back-office function to a core enabler of business growth, innovation, and competitive advantage. Senior business leaders and CIOs must navigate a complex web of competing priorities, such as managing stakeholder expectations, accelerating technological innovation, and maintaining operational efficiency.
AI, and gen AI in particular, are continuing to bombard the enterprise, but the gains to date havent been as big, nor come as quickly, as many business leaders hoped. Thats according to the fourth quarterly edition of Deloitte AI Institutes State of Generative AI in the Enterprise report released on Tuesday.
Following that, the completed code of practice will be presented to the European Commission for approval, with compliance assessments beginning in August 2025. Srinivasamurthy pointed out that key factors holding back enterprises from fully embracing AI include concerns about transparency and data security.
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.
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. Nutanix commissioned U.K.
Their top predictions include: Most enterprises fixated on AI ROI will scale back their efforts prematurely. The expectation for immediate returns on AI investments will see many enterprises scaling back their efforts sooner than they should,” Chaurasia and Maheshwari said.
In response, traders formed alliances, hired guards and even developed new paths to bypass high-risk areas just as modern enterprises must invest in cybersecurity strategies, encryption and redundancy to protect their valuable data from breaches and cyberattacks. Theft and counterfeiting also played a role.
AI and Machine Learning will drive innovation across the government, healthcare, and banking/financial services sectors, strongly focusing on generative AI and ethical regulation. Adopting multi-cloud and hybrid cloud solutions will enhance flexibility and compliance, deepening partnerships with global providers.
A cloud analytics migration project is a heavy lift for enterprises that dive in without adequate preparation. A cloud-first approach ensures better data security, compliance with regulations, and scalability for AI-driven innovation,” says Domingues. But this scenario is avoidable.
The growing role of FinOps in SaaS SaaS is now a vital component of the Cloud ecosystem, providing anything from specialist tools for security and analytics to enterprise apps like CRM systems. Another essential skill for managing the possible hazards of non-compliance and overuse is having a deep understanding of SaaS contracts.
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.
To maintain their competitive edge, organizations are constantly seeking ways to accelerate cloud adoption, streamline processes, and drive innovation. Readers will learn the key design decisions, benefits achieved, and lessons learned from Hearst’s innovative CCoE team. This post is co-written with Steven Craig from Hearst.
The study also found that IT leaders currently see AI as more of an employee productivity tool than a driver of innovation. Its an oversimplification to think of AI as purely a job replacement tool, says Brian Weiss, CTO at enterprise AI platform vendor Hyperscience.
For instance: Regulatory compliance, security and data privacy. With stringent laws like GDPR and PCI DSS, technology leaders must ensure serverless providers support compliance requirements. Maintaining and upgrading outdated systems can be resource-intensive and hinder innovation. Legacy infrastructure. Vendor lock-in.
The company’s innovative “cloud agnostic” strategy, supported by VMware’s increased capabilities post-acquisition, will promote growth for the clients, no matter if their workloads are on-premise or in a public cloud environment. The IBM and VMware relationship goes back two decades and includes our jointly funded innovation lab.
Thats why smart enterprise IT leaders are turning to AI-powered procurement platforms to streamline sourcing, optimize spending, and mitigate risk. AI in Action: AI-powered contract analysis streamlines compliance checks, flags potential risks, and helps you optimize spending by identifying cost-saving opportunities.
Cloud sovereignty is central to the European Unions quest for increased digital autonomy, with the aim of fostering innovation and supporting European businesses on their digital transformation journey. Innovation and Growth for European SMEs and Scale-Ups Of course, organizations at varying stages of digital transformation.
The answer informs how you integrate innovation into your operations and balance competing priorities to drive long-term success. Companies like Qualcomm have to plan and commit well in advance, estimating chip production cycles while simultaneously innovating at breakneck speed. A great example of this is the semiconductor industry.
Generative AI can revolutionize organizations by enabling the creation of innovative applications that offer enhanced customer and employee experiences. While LOBs drive their AI use cases, the central team governs guardrails, model risk management, data privacy, and compliance posture.
CIOs now list innovation as the most important trait they need to bring to their role, according to a 2024 survey by professional services firm Deloitte — ahead of delivering top-line value and serving as change agents, two endeavors that require innovation to facilitate.
Driven by the development community’s desire for more capabilities and controls when deploying applications, DevOps gained momentum in 2011 in the enterprise with a positive outlook from Gartner and in 2015 when the Scaled Agile Framework (SAFe) incorporated DevOps.
As enterprises at every stage of maturity strengthen their digital capabilities, the Chief Digital Officer has emerged as a strategic force within the executive suite. Instead, it has evolved into an indispensable leadership position encompassing digital innovation, organizational change, and business model reinvention.
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