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Primary among these is the need to ensure the data that will power their AI strategies is fit for purpose. Lack of oversight establishes a different kind of risk, with shadow IT posing significant security threats to organisations. Strong data strategies de-risk AI adoption, removing barriers to performance.
One of them is Katherine Wetmur, CIO for cyber, data, risk, and resilience at Morgan Stanley. Wetmur says Morgan Stanley has been using modern data science, AI, and machine learning for years to analyze data and activity, pinpoint risks, and initiate mitigation, noting that teams at the firm have earned patents in this space.
Welcome to your company’s new AI risk management nightmare. Before you give up on your dreams of releasing an AI chatbot, remember: no risk, no reward. The core idea of risk management is that you don’t win by saying “no” to everything. So, what do you do? I’ll share some ideas for mitigation.
It’s difficult to argue with David Collingridge’s influential thesis that attempting to predict the risks posed by new technologies is a fool’s errand. However, there is one class of AI risk that is generally knowable in advance. We ought to heed Collingridge’s warning that technology evolves in uncertain ways.
This whitepaper offers real strategies to manage risks and position your organization for success. IT leaders are experiencing rapid evolution in AI amid sustained investment uncertainty. As AI evolves, enhanced cybersecurity and hiring challenges grow.
The proof of concept (POC) has become a key facet of CIOs AI strategies, providing a low-stakes way to test AI use cases without full commitment. Moreover, Jason Andersen, a vice president and principal analyst for Moor Insights & Strategy, sees undemanding greenlighting of gen AI POCs contributing to the glut of failed experiments.
One of the world’s largest risk advisors and insurance brokers launched a digital transformation five years ago to better enable its clients to navigate the political, social, and economic waves rising in the digital information age.
This approach will help businesses maximize the benefits of agentic AI while mitigating risks and ensuring responsible deployment. With AI agents poised to take over significant portions of enterprise workflows, IT leaders will be faced with an increasingly complex challenge: managing them.
One of the world’s largest risk advisors and insurance brokers launched a digital transformation five years ago to better enable its clients to navigate the political, social, and economic waves rising in the digital information age.
Speaker: William Hord, Vice President of ERM Services
Your ERM program generally assesses and maintains detailed information related to strategy, operations, and the remediation plans needed to mitigate the impact on the organization. Organize ERM strategy, operations, and data. It is the tangents of this data that are vital to a successful change management process.
Rather than wait for a storm to hit, IT professionals map out options and build strategies to ensure business continuity. Following Broadcom’s late 2023 acquisition of VMware, numerous changes prompted customers and partners to reassess their strategies. Having a Plan B is table stakes for any IT team. It took about 18 months.
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.
Third, any commitment to a disruptive technology (including data-intensive and AI implementations) must start with a business strategy. I suggest that the simplest business strategy starts with answering three basic questions: What? It is important to realize that the usual “hype cycle” rules prevail in such cases as this.
We discussed already some of these cloud computing challenges when comparing cloud vs on premise BI strategies. Everywhere you turn these days, “the cloud” is being talked about. It’s a hot topic, and as technologies continue to evolve at a rapid pace, the scope of the cloud continues to expand.
How to make the right architectural choices given particular application patterns and risks. When it comes to the modern tech stack, one of the fastest changing areas is around containers, serverless, and choosing the ideal path to cloud native computing. Tradeoffs and key considerations for when to leverage Containers or Serverless.
A new area of digital transformation is under way in IT, say IT executives charged with unifying their tech strategy in 2025. That means IT veterans are now expected to support their organization’s strategies to embrace artificial intelligence, advanced cybersecurity methods, and automation to get ahead and stay ahead in their careers.
The time required to familiarize oneself with the requirements and consequences of the various laws and to develop and roll out your organizations strategies and solutions should also not be underestimated. Develop a compliance strategy Companies should first develop the strategic direction of the compliance organization.
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. This puts them at odds with legacy platforms, which are universally very deterministic. If you want to strike oil, you have to drill through the granite to get to it.
But the outage has also raised questions about enterprise cloud strategies and resurfaced debate about overly privileged software , as IT leaders look for takeaways from the disastrous event. It also highlights the downsides of concentration risk. What is concentration risk?
The primary goal for Eddingfield and his team was to improve change management processes and reduce the risk of failed changes by implementing collision detection and impact analysis. What if artificial intelligence (AI) could prevent 1,000 potential outages and improve IT service health and delivery by more than 75%?
For Kevin Torres, trying to modernize patient care while balancing considerable cybersecurity risks at MemorialCare, the integrated nonprofit health system based in Southern California, is a major challenge. They also had to retrofit some older solutions to ensure they didn’t expose the business to greater risks.
Despite AI’s potential to transform businesses, many senior technology leaders find themselves wrestling with unpredictable expenses, uneven productivity gains, and growing risks as AI adoption scales, Gartner said. This creates new risks around data privacy, security, and consistency, making it harder for CIOs to maintain control.
Amid that growth, a few key trends surfaced to impact CIOs’ cloud strategies, continuing to today: More flexible consumption models To increase spend within their ecosystems, hyperscalers marketed more flexible consumption programs to enable customers to increase their commitments, while mitigating consumption risk.
As gen AI heads to Gartners trough of disillusionment , CIOs should consider how to realign their 2025 strategies and roadmaps. The World Economic Forum shares some risks with AI agents , including improving transparency, establishing ethical guidelines, prioritizing data governance, improving security, and increasing education.
However, this perception of resilience must be backed up by robust, tested strategies that can withstand real-world threats. One major gap in the findings is that four in ten respondents admitted their organization had not reviewed its cyber resilience strategy in the last six months. India (67%) expressed the greatest concern.
This comprehensive strategy mainly aims to measure and forecast potential risks associated with AI development. OpenAI, the renowned artificial intelligence research organization, has recently announced the adoption of its new preparedness framework.
It is not just important to gather all the existing information, but to consider the preparation of data and utilize it in the proper way, has become an indispensable value in developing a successful business strategy. For example, you need to develop a sales strategy and increase revenue. Data Is Only As Good As The Questions You Ask.
As a business executive who has led ventures in areas such as space technology or data security and helped bridge research and industry, Ive seen first-hand how rapidly deep tech is moving from the lab into the heart of business strategy. The takeaway is clear: embrace deep tech now, or risk being left behind by those who do.
Artificial intelligence for IT operations (AIOps) solutions help manage the complexity of IT systems and drive outcomes like increasing system reliability and resilience, improving service uptime, and proactively detecting and/or preventing issues from happening in the first place. Beneath the surface, however, are some crucial gaps.
That spectrum of budget adjustments is being met by a range of strategies by IT leaders seeking to make the most of their 2025 IT spend. More than nine in 10 IT decision-makers project their budgets will increase in 2025, according to the Forrester 2025 Budget Planning Guide for Technology Executives. through 2027.
But shortsighted IT strategies, often pushed by CEOs seeking short-term gains, can saddle CIOs with increasing tech debt that can further undercut long-term outcomes and innovation. Two-thirds of CEOs surveyed by the IBM Institute for Business Value acknowledge raiding long-term IT projects to achieve short-term goals.
Tech supply chain risks South Korea’s semiconductor ecosystem, driven by industry leaders like Samsung and SK Hynix, is a cornerstone of global technology supply chains. Its dominance in critical areas like memory chips makes it indispensable to industries worldwide. It accounts for 60.5% and a NAND market share of 52.6%.
For CIOs, the event serves as a stark reminder of the inherent risks associated with over-reliance on a single vendor, particularly in the cloud. This has forced CIOs to question the resilience of their cloud environments and explore alternative strategies. Yes, they [enterprises] should revisit cloud strategies.
Moreover, these repatriations show how CIOs have a shrewder, more fluid cloud strategy today to ensure they don’t settle for less than what they want. And he has seen some respond by moving workloads from the cloud back to on-premises data centers, a move they feel gives them better control over costs and privacy standards.
CIOs perennially deal with technical debts risks, costs, and complexities. While the impacts of legacy systems can be quantified, technical debt is also often embedded in subtler ways across the IT ecosystem, making it hard to account for the full list of issues and risks.
In today’s fast-paced digital environment, enterprises increasingly leverage AI and analytics to strengthen their risk management strategies. A recent panel on the role of AI and analytics in risk management explored this transformational technology, focusing on how organizations can harness these tools for a more resilient future.
She is now CEO of 10Xresponsibletech, a consulting company focused on helping organizations design, integrate, and adopt business-aligned and responsible AI strategies. In a recent interview, Bhimani talked about the importance of thinking about ethical uses of AI and how it can benefit both humanity and individual organizations.
Maintaining, updating, and patching old systems is a complex challenge that increases the risk of operational downtime and security lapse. Indeed, more than 80% of organisations agree that scaling GenAI solutions for business growth is a crucial consideration in modernisation strategies. [2] The solutionGenAIis also the beneficiary.
Cybersecurity and systemic risk are two sides of the same coin. As we saw recently with the CrowdStrike outage, the interconnected nature of enterprises today brings with it great risk that can have a significant negative effect on any company’s finances. This should be no surprise since the global average cost of a data breach is $4.88
The coordination tax: LLM outputs are often evaluated by nontechnical stakeholders (legal, brand, support) not just for functionality, but for tone, appropriateness, and risk. The system is inconsistent, slow, hallucinatingand that amazing demo starts collecting digital dust. Whats worse: Inputs are rarely exactly the same.
Adding smarter AI also adds risk, of course. “At The big risk is you take the humans out of the loop when you let these into the wild.” According to Gartner, an agent doesn’t have to be an AI model. It can also be a software program or another computational entity — or a robot. And, yes, enterprises are already deploying them.
Cloud strategies are undergoing a sea change of late, with CIOs becoming more intentional about making the most of multiple clouds. A lot of ‘multicloud’ strategies were not actually multicloud. Today’s strategies are increasingly multicloud by intention,” she adds.
Research firm IDC projects worldwide spending on technology to support AI strategies will reach $337 billion in 2025 — and more than double to $749 billion by 2028. For the global risk advisor and insurance broker that includes use cases for drafting emails and documents, coding, translation, and client research.
However, embedding ESG into an enterprise data strategy doesnt have to start as a C-suite directive. Most data management conferences and forums focus on AI, governance and security, with little emphasis on ESG-related data strategies.
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