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Regardless of the driver of transformation, your companys culture, leadership, and operating practices must continuously improve to meet the demands of a globally competitive, faster-paced, and technology-enabled world with increasing security and other operational risks.
If 2023 was the year of AI discovery and 2024 was that of AI experimentation, then 2025 will be the year that organisations seek to maximise AI-driven efficiencies and leverage AI for competitive advantage. Lack of oversight establishes a different kind of risk, with shadow IT posing significant security threats to organisations.
So, in keeping with the New Years spirit, we asked multiple CIOs about their professional resolutions for 2025. One of them is Katherine Wetmur, CIO for cyber, data, risk, and resilience at Morgan Stanley. She recognizes that the possibilities of AI grow by the day but so do the risks.
Its been a year of intense experimentation. Now, the big question is: What will it take to move from experimentation to adoption? We expect some organizations will make the AI pivot in 2025 out of the experimentation phase. Its crucial to keep moving forward on this journey.
Experienced CIOs know there is never a blank check for transformation and innovation investments, and they expect more pressure in 2025 to deliver business value from gen AI investments. As gen AI heads to Gartners trough of disillusionment , CIOs should consider how to realign their 2025 strategies and roadmaps.
Forrester Research this week unleashed a slate of predictions for 2025. 2025 will be about the pursuit of near-term, bottom-line gains while competing for declining consumer loyalty and digital-first business buyers,” Sharyn Leaver, Forrester chief research officer, wrote in a blog post Tuesday.
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. AI spending on the rise Two-thirds (67%) of projected AI spending in 2025 will come from enterprises embedding AI capabilities into core business operations, IDC claims.
While genAI has been a hot topic for the past couple of years, organizations have largely focused on experimentation. In 2025, thats going to change. Here are five keys to addressing these issues for AI success in 2025. What are the associated risks and costs, including operational, reputational, and competitive?
The time for experimentation and seeing what it can do was in 2023 and early 2024. I dont think anyone has any excuses going into 2025 not knowing broadly what these tools can do for them, Mason adds. Whats our risk tolerance, and what safeguards are necessary to ensure safe, secure, ethical use of AI?
The report underscores a growing commitment to AI-driven innovation, with 67% of business leaders predicting that gen AI will transform their organizations by 2025. The report suggested that the quality of organizational data remains a top obstacle, with 85% of respondents citing it as the most significant challenge for 2025.
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.” When it comes to security, though, agentic AI is a double-edged sword with too many risks to count, he says. “We That means the projects are evaluated for the amount of risk they involve.
In celebration of the 100th anniversary of the discovery of quantum mechanics, United Nations has declared 2025 as the International Year of Quantum Science and Technology. It will enhance risk management. The good is it will exponentially change the speed at which financial institutions can do market trading.
Gartner also recently predicted that 30% of current gen AI projects will be abandoned after proof-of-concept by 2025. Many of those gen AI projects will fail because of poor data quality, inadequate risk controls, unclear business value , or escalating costs , Gartner predicts.
Research from IDC predicts that we will move from the experimentation phase, the GenAI scramble that we saw in 2023 and 2024, and mature into the adoption phase in 2025/26 before moving into AI-fuelled businesses in 2027 and beyond. So what are the leaders doing differently? The SAS research project explores this in detail.
As organizations roll out AI applications and AI-enabled smartphones and devices, IT leaders may need to sell the benefits to employees or risk those investments falling short of business expectations. They need to have a culture of experimentation.” CIOs should be “change agents” who “embrace the art of the possible,” he says.
Rather than pull away from big iron in the AI era, Big Blue is leaning into it, with plans in 2025 to release its next-generation Z mainframe , with a Telum II processor and Spyre AI Accelerator Card, positioned to run large language models (LLMs) and machine learning models for fraud detection and other use cases. At least IBM believes so.
But if there are any stop signs ahead regarding risks and regulations around generative AI, most enterprise CIOs are blowing past them, with plans to deploy an abundance of gen AI applications within the next two years if not already. These three programs are already delivering value for the business.”
Data scientists at Bayer have developed several proofs of concept of generative AI models on the new platform that remain in discovery and evaluation phase for “efficacy,” McQueen says, adding that the models won’t be in production until 2025. The R&D pipeline is pretty highly confidential at this point,” he says. It’s additive.”
By 2025 nearly all data generated will be in real-time. A disruptive mindset creates an environment that embraces constant experimentation and change. People are not going to feel comfortable taking risks if they feel like their job is on the line. Poor data quality costs upwards of $3.1 trillion a year.
It’s aggressively deploying those to Azure data centers, which won’t require any changes by customers, and expects these investments to come closer to meeting demand by mid 2025. But experimentation to achieve significant results takes time. It’s also creating tools to help customers pick from a wide range of models, Wong adds.
.” When observing its potential impact within industry, McKinsey Global Institute estimates that in just the manufacturing sector, emerging technologies that use AI will by 2025 add as much as USD 3.7 It can also hamper scaling of ML processes, making results harder to reproduce and risking errors due to incorrect or incomplete data.
This shift from relational to graph approach has been well-documented by Gartner who advise that “using graph techniques at scale will form the foundation of modern data and analytics” and “graph technologies will be used in 80% of data and analytics innovations by 2025.”
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. Absent governance and trust, the risks are higher as organizations adopt increasingly sophisticated analytics.
People aren’t going back and decluttering because there’s no cost to that — except in your risk profile and your decreased search performance,” says Buckley. As the cost of data storage has fallen, many organizations are keeping unnecessary data, or cleaning up data that’s out of date or no longer useful after a migration or reorganization.
As ICSs develop plans to deliver around 30% more elective activity by 2024-2025 than before the pandemic, the need to retain clinical staff is paramount. Responding to COVID-19 as it mutates and continues to impact society. Resetting urgent care performance and delivery. Improving patient outcomes through a data-first approach.
At the 2025 World Government Summit in Dubai, Google & Alphabet CEO Sundar Pichai joined H.E. Discussing Waymo, Googles self-driving car initiative, Pichai highlighted its safety record and expansion plans, aiming to serve 10 new cities in 2025 and conduct international testing in Japan.
IDC, for instance, recommends the NIST AI Risk Management Framework as a suitable standard to help CIOs develop AI governance in house, as well as EU AI ACT provisions, says Trinidad, who cites best practices for some aspects of AI governance in “ IDC PeerScape: Practices for Securing AI Models and Applications.”
As a result, ITs investments in AI are up, with the percentage of the IT budget earmarked for AI projects nearly tripling from last year, according to the 2025 CIO Playbook from Lenovo and research firm IDC. Theyll accept that there is some risk in deferring a needed investment now for a potential problem in the future, he says.
This shift demands clear goal alignment, relentless cross-functional collaboration, and a culture where experimentation and data-driven decisions lead the way. CIOs should consider top-down digital KPIs or OKRs measuring growth, efficiency, customer satisfaction, quality, and risk reductions.
While EA leaders have long been positioned as key enablers of digital transformation, the rapidly shifting business landscape of 2025 presents new pressures. According to Gartners 2025 Leadership Vision for Enterprise Architecture , several key missteps are preventing EA from delivering the business impact it should.
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