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
From AI models that boost sales to robots that slash production costs, advanced technologies are transforming both top-line growth and bottom-line efficiency. Business leaders dont need to be technology experts to grasp this shift; they need vision and urgency. Crucially, the time and cost to implement AI have fallen.
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. We ought to heed Collingridge’s warning that technology evolves in uncertain ways. We ought to heed Collingridge’s warning that technology evolves in uncertain ways.
CIOs are under increasing pressure to deliver meaningful returns from generative AI initiatives, yet spiraling costs and complex governance challenges are undermining their efforts, according to Gartner. hours per week by integrating generative AI into their workflows, these benefits are not felt equally across the workforce.
3) Cloud Computing Benefits. It’s a hot topic, and as technologies continue to evolve at a rapid pace, the scope of the cloud continues to expand. More and more CRM, marketing, and finance-related tools use SaaS business intelligence and technology, and even Adobe’s Creative Suite has adopted the model. Table of Contents.
Speaker: Shreya Rajpal, Co-Founder and CEO at Guardrails AI & Travis Addair, Co-Founder and CTO at Predibase
However, productionizing LLMs comes with a unique set of challenges such as model brittleness, total cost of ownership, data governance and privacy, and the need for consistent, accurate outputs. Large Language Models (LLMs) such as ChatGPT offer unprecedented potential for complex enterprise applications.
Hes leveraging his vendor relationships to keep pace with emerging as well as tried-and-true technologies and practices. 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.
As a consequence, these businesses experience increased operational costs and find it difficult to scale or integrate modern technologies. 1] Retaining outdated technology may seem like a cautious approach but there are mounting inherent dangers. The foundation of the solution is also important.
Taking too long on AI projects Extracting value from AI is a key CEO priority today , and many IT leaders have in turn reshaped their IT agendas to emphasize projects centered on the technology. AI technology is changing so fast that projects taking more than a month can end up built on out-of-date technology, he says.
Agentic AI, the more focused alternative to general-purpose generative AI, is gaining momentum in the enterprise, with Forrester having named it a top emerging technology for 2025 in June. The technology is in its early days, and several questions remain open chief among them, how AI agents will be priced.
Speaker: Donna Laquidara-Carr, PhD, LEED AP, Industry Insights Research Director at Dodge Construction Network
In today’s construction market, owners, construction managers, and contractors must navigate increasing challenges, from cost management to project delays. Fortunately, digital tools now offer valuable insights to help mitigate these risks. That’s where data-driven construction comes in.
To fully benefit from AI, organizations must take bold steps to accelerate the time to value for these applications. Adopting Operational AI Organizations looking to adopt Operational AI must consider three core implementation pillars: people, process, and technology. This is where Operational AI comes into play.
One of the greatest things about working in technology is the surprise advancements that take the industry by storm. A bleeding-edge technology is one that takes the industry by storm because it creates a significant paradigm shift into how things currently work with the potential to majorly impact the industry itself.
While the ROI of any given AI project remains uncertain , one thing is becoming clear: CIOs will be spending a whole lot more on the technology in the years ahead. 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.
CIOs were given significant budgets to improve productivity, cost savings, and competitive advantages with gen AI. CIOs feeling the pressure will likely seek more pragmatic AI applications, platform simplifications, and risk management practices that have short-term benefits while becoming force multipliers to longer-term financial returns.
Despite these limitations and concerns among CIOs over AI costs, real progress has been made this year and we can expect to see this grow further in 2025. Assuming a technology can capture these risks will fail like many knowledge management solutions did in the 90s by trying to achieve the impossible.
Taiwan Semiconductor Manufacturing Company (TSMC) has said it is unlikely to equip its new US plant in Arizona with its most advanced chip technology ahead of its Taiwan factories, raising concerns about supply-chain hurdles for tech companies. Delays in accessing modern technology may postpone those launch dates.
It also highlights the downsides of concentration risk. What is concentration risk? Looking to the future, IT leaders must bring stronger focus on “concentration risk”and how these supply chain risks can be better managed. Unfortunately, the complexity of multiple vendors can lead to incidents and new risks.
Travel and expense management company Emburse saw multiple opportunities where it could benefit from gen AI. Both types of gen AI have their benefits, says Ken Ringdahl, the companys CTO. Another benefit is that with open source, Emburse can do additional model training. You get more control over your costs.
Organizations that deploy AI to eliminate middle management human workers will be able to capitalize on reduced labor costs in the short-term and long-term benefits savings,” Gartner stated. “AI New security and risk solutions will be necessary as AI agents significantly increase the already invisible attack surface at enterprises.
Research from Gartner, for example, shows that approximately 30% of generative AI (GenAI) will not make it past the proof-of-concept phase by the end of 2025, due to factors including poor data quality, inadequate risk controls, and escalating costs. [1] AI in action The benefits of this approach are clear to see.
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.
But alongside its promise of significant rewards also comes significant costs and often unclear ROI. For CIOs tasked with managing IT budgets while driving technological innovation, balancing these costs against the benefits of GenAI is essential.
Those customers should be evaluating if, when and how they will tap into the benefits that AI and GenAI can provide to improve operational and financial performance. With a perception of limited or no benefit, not taking any action can appear attractive and may be the right choice.
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.
While CIOs understand the crushing weight of technical debt — now costing US companies $2.41 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. You’re not alone.
Typically, the technology will show there are many variations in how a process unfolds and the context in which those permutations occur. The results can be used to uncover the source of bottlenecks, delays, unseen risks and unnecessary workloads that, in turn, allows organizations to institute improvements.
If expectations around the cost and speed of deployment are unrealistically high, milestones are missed, and doubt over potential benefits soon takes root. The right tools and technologies can keep a project on track, avoiding any gap between expected and realized benefits. But this scenario is avoidable.
Developing and deploying successful AI can be an expensive process with a high risk of failure. How can CIOs deliver accurate, trustworthy AI without the energy costs and carbon footprint of a small city? Train overnight when data center demand is low for better performance and lower costs.
Even beyond customer contact, bankers see generative AI as a key transformative technology for their company. Many banking executives said regulatory challenges, lack of operational flexibility, and outdated technologies were the biggest obstacles to their organization’s digital transformation over the past 12 months.
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 shift not only reduces the chances of human error but also elevates the quality of outputs across various departments, which reflects a broader trend of harnessing technology to drive meaningful transformation in the workplace. Enterprises that adopt RPA report reductions in process cycle times and operational costs.
“It wasn’t just a single measurement of particulates,” says Chris Mattmann, NASA JPL’s former chief technology and innovation officer. “It The previous state-of-the-art sensors cost tens of thousands of dollars, adds Mattmann, who’s now the chief data and AI officer at UCLA. “The Adding smarter AI also adds risk, of course. “At
Set clear, measurable metrics around what you want to improve with generative AI, including the pain points and the opportunities, says Shaown Nandi, director of technology at AWS. That gives CIOs breathing room, but not unlimited tether, to prove the value of their gen AI investments.
The answer can be found in the theory of economic rents, and in particular, in the kinds of rents that are collected by companies during different stages of the technology business cycle. But this kind of virtuous rising tide rent, which benefits everyone, doesn’t last. What Is Economic Rent? They start to collect robber baron rents.
If exploited, a single mainframe code vulnerability can allow a hacker to bypass security controls and corrupt a system, all while covering their tracks—all of which come at a high cost to the company. What steps can be taken to minimize the risk of hackers penetrating the mainframe? Mainframes are under more pressure than ever before.
GRC certifications validate the skills, knowledge, and abilities IT professionals have to manage governance, risk, and compliance (GRC) in the enterprise. Enter the need for competent governance, risk and compliance (GRC) professionals. What are GRC certifications? Why are GRC certifications important?
AI Benefits and Stakeholders. AI is a field where value, in the form of outcomes and their resulting benefits, is created by machines exhibiting the ability to learn and “understand,” and to use the knowledge learned to carry out tasks or achieve goals. AI-generated benefits can be realized by defining and achieving appropriate goals.
But many enterprises have yet to start reaping the full benefits that AIOps solutions provide. An increasingly complex technology landscape makes it more difficult to resolve issues. Understanding the root cause of issues is one situational benefit of AIOps.
In 2024, squeezed by the rising cost of living, inflationary impact, and interest rates, they are now grappling with declining consumer spending and confidence. However, successful AI implementation requires more than cutting-edge technology. The disruption isnt in the technology itself but in how it can transform buying behaviours.
As with any new technology, however, security must be designed into the adoption of AI in order to minimize potential risks. The combination of new technology with a short window makes security even more difficult than with traditional applications.
In todays fast-paced digital landscape, organizations are under constant pressure to adopt new technologies quickly, manage costs effectively, and maintain robust security and compliance standards. Procuring through AWS Marketplace has a number of benefits.
Intelligent new services and infrastructure can optimize cost and performance, but the rapidly evolving technology environment also introduces complexity. Business transformation is a journey Great modern enterprises are only as good as their technology, which must keep pace with changing business demands.
As CIOs seek to achieve economies of scale in the cloud, a risk inherent in many of their strategies is taking on greater importance of late: consolidating on too few if not just a single major cloud vendor. This is the kind of risk that may increasingly keep CIOs up at night in the year ahead.
So for all its vaunted benefits to efficiency, gen AI doesn’t always reduce workloads. These technologies can produce more content that everyone needs to consume and be aware of,” says Anita Woolley, professor at Carnegie Mellon University. And we’re at risk of being burned out.”
We organize all of the trending information in your field so you don't have to. Join 42,000+ 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