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In 2025, data management is no longer a backend operation. As enterprises scale their digital transformation journeys, they face the dual challenge of managing vast, complex datasets while maintaining agility and security. This article dives into five key data management trends that are set to define 2025.
How does a business stand out in a competitive market with AI? For others, it may simply be a matter of integrating AI into internal operations to improve decision-making and bolster security with stronger fraud detection. Above all, robust governance is essential. Data breaches are not the only concern.
You pull an open-source large language model (LLM) to train on your corporate data so that the marketing team can build better assets, and the customer service team can provide customer-facing chatbots. This means that the infrastructure needs to provide seamless data mobility and management across these systems.
Travel and expense management company Emburse saw multiple opportunities where it could benefit from gen AI. With security, many commercial providers use their customers data to train their models, says Ringdahl. It allows us to provide services in areas that arent covered, and check boxes on the security, privacy, and compliance side.
AI a primary driver in IT modernization and data mobility AI’s demand for data requires businesses to have a secure and accessible data strategy. Key challenges include designing and deploying AI infrastructure, with priorities such as data security (53%), resilience and uptime (52%), management at scale (51%), and automation (50%).
This organism is the cornerstone of a companys competitive advantage, necessitating careful and responsible nurturing and management. This article proposes a methodology for organizations to implement a modern data management function that can be tailored to meet their unique needs.
Most large businesses have a security team. But what, exactly, does that security team look like? And is it optimized in each of these respects to maximize the organization’s security posture? We learned, for example, that very few organizations have just a single security team. How is it structured? Most have several.
Become reinvention-ready CIOs must invest in becoming reinvention-ready, allowing their enterprise to adopt and adapt to rapid technological and market changes, says Andy Tay, global lead of Accenture Cloud First. Reinvention-ready companies are positioned to succeed in the long term, Tay observes. Are they still fit for purpose?
Gartner’s top predictions for 2025 are as follows: Through 2026, 20% of organizations will use AI to flatten their organizational structure, eliminating more than half of current middle management positions. In the near-term, security-related attacks of AI agents will be a new threat surface,” Plummer said.
A member of your organization’s security team reads about a new kind of security tool and brings it to the CISO’s attention, who decides that it’s a good investment. The CISO sees a new kind of security threat that requires a different security tool. A colleague recommends a security tool she says is indispensable.
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. Ensuring effective and secure AI implementations demands continuous adaptation and investment in robust, scalable data infrastructures.
The more strategic concern isn’t just the cost— it’s that technical debt is affecting companies’ abilities to create new business, and saps the means to respond to shifting market conditions. Market position (opportunity cost): “We’re six to eight months slower to market with new features than our competitors.”
Then in November, the company revealed its Azure AI Agent Service, a fully-managed service that lets enterprises build, deploy and scale agents quickly. Before that, though, ServiceNow announced its AI Agents offering in September, with the first use cases for customer service management and IT service management, available in November.
Often, technical leaders don’t devote sufficient time to communication, change management, and stakeholder management,” he observes. Hafez adds that most modernization projects typically fail due to a lack of a realistic expectations, defined requirements, and ineffective change management.
This volatility can make it hard for IT workers to decide where to focus their career development efforts, but there are at least some areas of stability in the market: despite all other changes in pay premiums, workers with AI skills and security certifications continued to reap rich rewards.
The security professional shortage Some 3.5 This drives up wages, making it both expensive to hire security professionals and difficult to retain them. Given the nature of their business, costs for security are baked into the business model. But you need to know what to look for in a cloud provider.
China follows the EU, with additional focus on national security In March 2024 the Peoples Republic of China (PRC) published a draft Artificial Intelligence Law, and a translated version became available in early May. Lastly, China’s AI regulations are focused on ensuring that AI systems do not pose any perceived threat to national security.
As organisations adjust to managing remote and hybrid teams, supporting digital transformation, and navigating an uncertain and volatile global economy, they face an ever-expanding landscape of vulnerabilities and increasing risk. The volume of security incidents has increased in the past year for 61% of organisations.
While poised to fortify the security posture of organizations, it has also changed the nature of cyberattacks. From prompt injections to poisoning training data, these critical vulnerabilities are ripe for exploitation, potentially leading to increased security risks for businesses deploying GenAI.
I am excited about the potential of generative AI, particularly in the security space, she says. The opportunity to further leverage AI to enhance our security infrastructure, address threats, and enable fraud detection is immense, she says. One of them is Katherine Wetmur, CIO for cyber, data, risk, and resilience at Morgan Stanley.
Nine of 10 CIOs surveyed by Gartner late last year expressed concerns that managing AI costs was limiting their ability to get value from AI. Divestitures can also help companies zero in on their potential and market relevance, the blog authors note. The sale allows the company to focus on AI-driven engineering, the company said.
CISOs can only know the performance and maturity of their security program by actively measuring it themselves; after all, to measure is to know. With proactive measurement, CISOs will confirm how well their security program performs, better understand its preparedness against relevant threats, and highlight gaps that require improvement.
CIOs have a long history of managing incidents and disasters through established IT practices, guided by frameworks such as ITIL for incident management and disaster recovery. However, as ecommerce has proliferated, security threats have increased, elevating cybersecurity to a board-level concern.
“PKI and cryptography have always been very low-level, in the weeds but foundational for security even though CIOs probably haven’t paid much attention to it,” says Christian Simko, VP of product marketing at low-code automation platform AppViewX. A single physical device can run hundreds of ephemeral workloads.
According to Richard Kulkarni, Country Manager for Quest, a lack of clarity concerning governance and policy around AI means that employees and teams are finding workarounds to access the technology. Lack of oversight establishes a different kind of risk, with shadow IT posing significant security threats to organisations.
One key reason is that CIOs and chief information security officers (CISOs) are not always aligned in how to enable productive, secure work. But in practice, IT and security teams often work separately, without common knowledge, data, goals, priorities, and practices. Ultimately you’re impacting top line revenue,” says Fulton.
What is a managed service provider? Managed service provider business model Managed service providers structure their business to offer technology services cheaper than what it would cost an enterprise to perform the work itself, at a higher level of quality, and with more flexibility and scalability.
Running AI on mainframes as a trend is still in its infancy, but the survey suggests many companies do not plan to give up their mainframes even as AI creates new computing needs, says Petra Goude, global practice leader for core enterprise and zCloud at global managed IT services company Kyndryl.
Prioritize data quality and security. For AI models to succeed, they must be fed high-quality data thats accurate, up-to-date, secure, and complies with privacy regulations such as the Colorado Privacy Act, California Consumer Privacy Act, or General Data Protection Regulation (GDPR). Increase adoption through change management.
Underpinning these initiatives is a slew of technology capabilities and strategies aimed at accelerating delivery cycles, such as establishing product management disciplines, building cloud architectures, developing devops capabilities, and fostering agile cultures. This dip delays when the business can start realizing the value delivered.
And he believes these tools not only streamline management and allow for more precise administration of resources, but also open up a range of possibilities to personalize the customer experience. In addition, Abril highlights specific benefits gained from applying new technologies. We want to have the best specialists in the field.
While hackers target companies of all sizes, a tech giant like SAP may have a bigger bull’s eye on its back because of the sensitive data it manages and the critical role its ERP applications play in global businesses. As a result, SAP is always evolving its security measures to stay ahead of cyber threats.
Companies should therefore already be taking concrete steps to implement the EU AI Act and the EU Data Act, explains Daniel Andernach , Associated Partner at MHP , an international management and IT consultancy. Well-founded specialist knowledge is necessary for truly effective, secure and legally compliant implementation.
As noted in the IDC FutureScape report “ Artificial Intelligence Will Reshape the IT Industry and the Way Businesses Operate ,” inadequate training in AI, cloud, data, security, and emerging tech fields will directly and negatively impact enterprise attempts to succeed in efforts that rely on such technologies.
Back then, Mastercard had around 3,500 employees and a $4 billion market cap. As more AI innovations come to market, financial institutions can leverage the technology for enhanced services, increased efficiency, and new ways to deliver and manage products. But it wasn’t the tech that made Mastercard what it is today.
By Chet Kapoor, Chairman & CEO at DataStax Along with the exciting possibilities of generative AI (genAI), there have been concerns around job (in)security and displacement. Instead of viewing it as a threat to job security, organizations can leverage genAI as a tool to empower their workforce and augment their capabilities.
The challenges don’t end once those requirements are met, as the project teams need to secure executive buy-in, which may be hindered by resistance to new technologies. A cloud-first approach ensures better data security, compliance with regulations, and scalability for AI-driven innovation,” says Domingues.
To drive change, a reworking of what defines CIO/IT success is needed, with a focus on strategic business goals, innovation, and market differentiation. The remaining five metrics, including uptime and availability, cost control, operational efficiency, compliance, and security, are deeply rooted in traditional IT priorities.
At a press conference held in Seoul on March 20, SAP CEO Christian Klein personally introduced the Korean market to SAPs AI-specific services, describing how SAPs AI vision can help Korean companies realize theirs. He added that to make AI more secure, only authorized people can access the data and only authorized AI use cases can use it.
From IT, to finance, marketing, engineering, and more, AI advances are causing enterprises to re-evaluate their traditional approaches to unlock the transformative potential of AI. The data privacy and security risks of AI applications themselves Not all AI applications are created equal. These are questions enterprises must answer.
However, without proper governance and oversight, this can lead to inconsistencies, security vulnerabilities, and technical debt. Knowledge management: GenAI helps organize and retrieve organizational knowledge, making it easier for IT professionals to access the information they need to solve problems and learn new skills.
A number of obstacles stand in the way of IT leaders looking to address their enterprise content management objectives, but two stand out: a proliferation of tools and an inability to effectively integrate them. The result: numerous content silos and point products that don’t talk to one another. “In
For ML and analytics, Tesoro purchases products on the market it considers best in class, and the applications are then customized through technological partners for the needs of the company’s site and app. “The I give directions and strategies to the supplier and the partner, and an internal project manager acts as a link.
According to IDC’s Worldwide AI and Generative AI Spending Guide (August 2024) , the global AI market is expected to surge from US$235 billion in 2024 to US$632 billion by 2028. Tencent Cloud stands to benefit, particularly in APAC, where market size is predicted to grow from US$45.4 billion in 2024 to over US$110 billion by 2028.
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