This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
Data architecture definition Data architecture describes the structure of an organizations logical and physical data assets, and data management resources, according to The Open Group Architecture Framework (TOGAF). Ensure security and access controls. An organizations data architecture is the purview of data architects. Cloud storage.
Some challenges include data infrastructure that allows scaling and optimizing for AI; data management to inform AI workflows where data lives and how it can be used; and associated data services that help data scientists protect AI workflows and keep their models clean.
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. CIOs are an ambitious lot. Were embracing innovation, he explains.
The implications of the ongoing misperception about the data management needs of AI are huge, Armstrong adds. Business leaders may be confident that their organizations data is ready for AI, but IT workers tell a much different story, with most spending hours each day massaging the data into shape. Thats where the friction arises.
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.
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.
This award-winning access management project uses automation to streamline access requests and curb security risks. Access management is crucial in the legal world because cases depend on financial records, medical records, emails, and other personal information.
Chief among these is United ChatGPT for secure employee experimental use and an external-facing LLM that better informs customers about flight delays, known as Every Flight Has a Story, that has already boosted customer satisfaction by 6%, Birnbaum notes. People hear the specifics, and they understand it and their blood pressure goes down.
This means that new approaches are needed to manage and protect data access and govern AI inputs and outputs and safely deliver AI value. More than 90% of CIOs said that managing cost limits their ability to get value from AI for their enterprise, according to a Gartner survey of over 300 CIOs in June and July 2024.
Suppliers were often hand-delivering paper invoices to the cooperative’s local offices, which were processed and paid out manually with no centralized invoice management. Working with SAP, the cooperative picked SAP Ariba Central Invoice Management with its inbound process for SAP S/4HANA Cloud public edition to create just what was needed.
In addition, because they require access to multiple data sources, there are data integration hurdles and added complexities of ensuring security and compliance. All of this creates new challenges, on top of those already posed by the gen AI itself. Plus, unlike traditional automations, agentic systems are non-deterministic.
As organizations look to modernize IT systems, including the mainframe, there’s a critical need to do so without sacrificing security or falling out of compliance. With the stakes so high, IT leaders need to ensure their modernization strategies are inclusive of mainframe security. PCI DSS v4.0).
IT managers are often responsible for not just overseeing an organization’s IT infrastructure but its IT teams as well. To succeed, you need to understand the fundamentals of security, data storage, hardware, software, networking, and IT management frameworks — and how they all work together to deliver business value.
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. In our fast-changing digital world, it’s essential to sync IT strategies with business objectives for lasting success.
To address the misalignment of those business units, MMTech developed a core platform with built-in governance and robust security services on which to build and run applications quickly. I want to provide an easy and secure outlet that’s genuinely production-ready and scalable. The biggest challenge is data.
Sameer Purao, who joined Celanese as CIO and CDO in 2021, is keeping the team and company focused by making change management a core competency of his team, and ensuring a focus on value, agility, and purpose. At the same time, the company is undergoing a massive digital transformation.
The company also plans to increase spending on cybersecurity tools and personnel, he adds, and it will focus more resources on advanced analytics, data management, and storage solutions. The rapid accumulation of data requires more sophisticated data management and analytics solutions, driving up costs in storage and processing,” he says.
And finally, Security First that revolves around an automation concept and dedicated SOC. Norma’s IT security efforts and transformation projects are paying off as the company hasn’t recorded any damaging security incidents for 10 years. And IT security was increased by switching to single sign-on (SSO) for all relevant apps.
To address the misalignment of those business units, MMTech developed a core platform with built-in governance and robust security services on which to build and run applications quickly. I want to provide an easy and secure outlet that’s genuinely production-ready and scalable. The biggest challenge is data.
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.
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.
These areas are considerable issues, but what about data, security, culture, and addressing areas where past shortcuts are fast becoming todays liabilities? This will free them to bring their skills and creativity to higher-value activities such as enhancing data security and delivering innovative solutions for customers.
Theyre actively investing in innovation while proactively leveraging the cloud to manage technical debt by providing the tools, platforms, and strategies to modernize outdated systems and streamline operations. As 2025 dawns, CIOs face an IT landscape that differs significantly from just a year ago. Are they still fit for purpose?
Top impacts of digital friction included: increased costs (41%)increased frustration while conducting work (34%) increased security risk (31%) decreased efficiency (30%) lack of data for quality decision-making (30%) are top impacts. Managed, on the other hand, it can boost operations, efficiency, and resiliency.
In IT service and operations (ServiceOps), AI agents are providing assistance for in-context insights, incident response, change risk prediction, and vulnerability management. However, the diversity and velocity of data utilized by AI pose significant challenges for data security and compliance.
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. Take cybersecurity, for example.
This requires greater flexibility in systems to better manage data storage and ensure quality is maintained as data is fed into new AI models. As data is moved between environments, fed into ML models, or leveraged in advanced analytics, considerations around things like security and compliance are top of mind for many.
Governance and human challenges further complicate AI rollouts Another formidable challenge is the governance and data management complexity brought on by the decentralization of AI capabilities. This creates new risks around data privacy, security, and consistency, making it harder for CIOs to maintain control.
The awareness gained in the process often leads to a grounding, also in management: Those who like to talk very loudly about AI, for example, quickly become very quiet again after taking a look at their existing IT infrastructure. Only in this way can companies manage the enormous amounts of data at all.
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.
The first step of the manager’s team was instead to hire a UX designer to not only design the interface and experience for the end user, but also carry out tests to bring qualitative and quantitative evidence on site and app performance to direct the business. IT must be at the service of the business,” he says.
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.
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.
In this role, Brady oversees the front-to-back IT organization, data and analytics, enterprise security, enterprise risk, and an intelligent automation center of excellence, all while managing back-office operations, contact center services, and KeyBanks corporate real estate portfolio. So, I thought, banking would be stable.
Retailers plan to focus on improving supply chain planning, warehouse/inventory management, and integration between supply chain planning and execution during the coming year to meet these challenges. Reducing security complexity by adopting more comprehensive solutions like secure access service edge (SASE). IDC, June 2024).
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.
In today’s enterprise environments, security and networking teams may be siloed for a variety of reasons. Yet there’s now widespread agreement that the drawbacks of siloed security and networking operations far outweigh any historical advantages. Plus, enhanced security outcomes lead to impressive reputational dividends.
Suboptimal integration strategies are partly to blame, and on top of this, companies often don’t have security architecture that can handle both people and AI agents working on IT systems. So it’s essential to show the ROI to your business from the management of these costs. Instead, show how leading companies manage it strategically.
But when managed the right way, it can substantially boost the value of IT resources, while minimizing the risks stemming from migrating away from outdated IT platforms. At the same time, however, the business may have so much riding on legacy technology that it cant afford not to maintain and update it. Legacy platform is a relative term.
Today, security teams worldwide are under immense pressure. Today’s cybercriminals are leveraging advanced techniques to breach security perimeters – ransomware attacks are more targeted, phishing campaigns are increasingly sophisticated, and attackers are exploiting new vulnerabilities.
Call it survival instincts: Risks that can disrupt an organization from staying true to its mission and accomplishing its goals must constantly be surfaced, assessed, and either mitigated or managed. While security risks are daunting, therapists remind us to avoid overly stressing out in areas outside our control.
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%).
These details are from the Check Point 2024 Cyber Security Report , which paints a combination of grim prospects and optimism. This technology is gaining popularity as it provides organizations several benefits, including simplifying network management, enhanced application performance, and operational cost savings.
People : To implement a successful Operational AI strategy, an organization needs a dedicated ML platform team to manage the tools and processes required to operationalize AI models. Ensuring effective and secure AI implementations demands continuous adaptation and investment in robust, scalable data infrastructures.
We organize all of the trending information in your field so you don't have to. Join 11,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content