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
Let’s review a case study and see how we can start to realize benefits now. Agentic AI design: A case study When you start doing agentic AI design you need to break down the tasks, identify the roles and map those to specific functionality that an agent will perform. Do you know what the user agent does in this scenario?
An AI-powered transcription tool widely used in the medical field, has been found to hallucinate text, posing potential risks to patient safety, according to a recent academic study. In a separate study, researchers found that AI models used to help programmers were also prone to hallucinations.
A recent study by management consultancy Horvth shows that delays in planned go-live dates are the rule rather than the exception. Significant migration deficiencies According to the study, projects are taking an average 30% longer than originally planned. This also reflects the responses of the study participants.
The average large enterprise lost $104 million to digital inefficiencies in 2024, driven by productivity losses connected to employee IT frustrations and hundreds of ghost apps flying under the radar, according to a new study. Meanwhile, many enterprise employees turn to unauthorized apps and software to do their jobs, the study says.
In its 2020 Embedded BI Market Study, Dresner Advisory Services continues to identify the importance of embedded analytics in technologies and initiatives strategic to businessintelligence. Which sophisticated analytics capabilities can give your application a competitive edge?
In the face of shrinking budgets and rising customer expectations, banks are increasingly relying on AI, according to a recent study by consulting firm Publicis Sapiens. According to the study, the biggest focus in the next three years will be on AI-supported data analysis, followed by the use of gen AI for internal use.
Downtime cost large enterprises an average of $200 million annually, cutting 9% from yearly profits, according to a study commissioned by Splunk. For the study, titled “The Hidden Costs of Downtime,” Oxford Economics quizzed executives from Global 2000 companies about the causes and costs of downtime in IT systems.
According to a recent Salesforce study, 62% of large enterprises are not well-positioned to achieve this harmony, with 80% grappling with data silos and 72% facing the complexities of overly interdependent systems. However, a significant challenge persists: harmonizing data systems to fully harness the power of AI.
That’s according to a new study of enterprise cloud usage by 451 Research, which also looked at what enterprises are running across multiple public clouds, and how they measure strategy success. The study also asked enterprises what key outcomes they expected from a multicloud management platform.
Case study number 2: Grinds partnership with Google to embrace GenAI Grind, a specialty coffee retailer based in the U.K., Grinds experience exemplifies how businesses can effectively adopt AI technologies to boost productivity and innovation.
According to Suda, Gartner researchers found over the course of a six-month study that the addition of gen AI to places like the help desk boosted productivity. Studies show that increased AI use is linked to the erosion of critical thinking skills. He concludes: Gen AI is a teacher, not a doer.
A study by Microsoft and Carnegie Mellon University found that professionals who rely heavily on AI tools engage in less independent reasoning over time. Used improperly, technologies can and do result in the deterioration of cognitive faculties that ought to be preserved, the study said of generative AI.
In the panel the experts agreed that AI has a massive opportunity outside the health system, with AI they can study people before they have a disease, by studying their food habits, for example. Using that data and running AI on top will prevent early disease in the future.
Generative AI is increasingly being put into production, survey author Randy Bean and Tom Davenport, professor of IT and management at Babson College, observed in this year s study. Only 29% are still just experimenting with generative AI, versus 70% in the 2024 study. Early-stage production has also increased, from 25% to 47%.
Such a review was carried out by Harvard Business Publishing in its 2024 Global Leadership Development Study, which identifies a number of changes in relation to current core curricula. Analyzing current training programs for leaders is a good barometer to see how effective responses to change are against the needs of companies.
Introducing businessintelligence required a great deal of change management work, because from a data use that wasnt very sophisticated and organized, and very do-it-yourself, we moved to a consistent and verified data warehouse, he says. Digital transformation must not be an imposition, but a convinced and unanimous choice.
The decline in stable SAP budgets and the rise in reduced spending could indicate cost-cutting measures, migration delays, or consolidation of SAP systems, Jens Hungershausen, DSAG Chairman of the Board said in the study. Larger companies, in particular, are leading the charge as they leverage cloud solutions to modernize their operations.
In this post, we’ll touch on three such case studies. From insurance to banking to healthcare, organizations of all stripes are upgrading their aging content management systems with modern, advanced systems that introduce new capabilities, flexibility, and cloud-based scalability.
Also at the event we’ll be diving into successful AI case studies, learning how to use emerging technologies to drive efficiency and innovation, discussing IT leadership, and looking at the latest IDC research on the evolving open source ecosystem. You must be present to win, so register now to join us.
Leveraging technology for business At IndiaMART, business stakeholders reflect on bifurcating problem solving between tech intervention and business solutions. By centering the customers in every process, we identify key customer problems and re-engineer existing processes using technology to better them.
For example, a study conducted by MyPerfectResume found that as many as 81% of recruiters admit to posting fake job offers. The authors of the study interpret the intentions of these practices in a similar way to Ng: building a talent pool, testing markets, or improving the company’s image.
Focused on digitization and innovation and closely aligned with lines of business, some 40% of IT leaders surveyed in CIO.com’s State of the CIO Study 2024 characterize themselves as transformational, while a quarter (23%) consider themselves functional: still optimizing, modernizing, and securing existing technology infrastructure.
According to the study, more organisations are moving away from hiring people who are highly skilled in a single area of expertise towards hiring people who can contribute across a range of functional areas.
IT budgets are seeing modest increases, according to recent survey data, with businesses looking to invest their IT dollars in artificial intelligence, data analytics, networking and more. and Canada in the first half of 2024 for its annual Computer Economics IT Spending and Staffing Benchmarks 2024/2025 study.
According to the Foundry Cloud Computing Study 2024 , 63% of enterprise CIOs were accelerating their cloud migrations, up from 57% in 2023. Specifically, CIOs worry about controlling costs (51%) and how much costs will add up in the long term (49%), according to the Foundry study. Which can be true if your efforts end with migration.
The company employs over 800 lawyers globally who study local laws and regulations, helping Huawei prepare technical and regulatory baselines tailored to specific regions. “We not only collaborate with industry bodies and organizations but also work closely with local entities to ensure adherence to regulations.”
However, only around a third of them actively measure both, according to a recent study by revenue intelligence leader Gong, which surveyed over 500 IT leaders and CIOs across the US and UK. CIOs are under pressure to validate AI investments and assure CFOs of a clear path of implementation that will ensure ROI.
In the NTT DATA study, 39% of those surveyed say they now have significant investments in gen AI, with the percentage rising to 61% within the next two years. Spending still increasing Even with mixed results in the past year, many companies are planning to increase their gen AI spending in 2025 and beyond.
However, research demonstrates that more executives, like Schumacher, recognize the connection between AI and business innovation. A June 2023 study by IBM found that 43% of executives use generative AI to inform strategic decisions, accessing real-time data and unique insights. Most AI hype has focused on large language models (LLMs).
He recommends building a user feedback loop and carefully studying satisfaction metrics. System obsolescence also leads to difficulties integrating with newer technologies as well as a lack of vendor support, he adds. It’s all about keeping your finger on the pulse of your IT ecosystem Galbraith says.
Generative and agentic artificial intelligence (AI) have captured the imagination of IT leaders, but there is a significant gap between enthusiasm and implementation maturity for IT operations and service management, according to a new survey from BMC Software and Dimensional Research.
Some studies tout major productivity increases , while others dispute those results. AI agents take over the world Over the long term, Walsh predicts that AI coding agents will increasingly take over the programming tasks at many organizations, although human expertise and creativity will still be needed to fine-tune the code.
The study identified a variety of obstacles standing in the way of digital transformation: Lack of strategies and an oversupply of technological solutions: Many companies are aware of the need for digital transformation, but do not have a clear strategy and are overwhelmed by the multitude of technological options.
Many developers say AI coding assistants make them more productive, but a recent study set forth to measure their output and found no significant gains. Use of GitHub Copilot also introduced 41% more bugs, according to the study from Uplevel, a company providing insights from coding and collaboration data.
This is significant, as major US toolmakers have responded to the restrictions by ramping up efforts to expand manufacturing outside the US, according to a recent report by Gregory Allen, an AI expert at the Center for Strategic and International Studies (CSIS).
While open-source software has long had a clear definition, it was only last week that the Open Source Initiative (OSI) finally published its definition of what open-source AI is: a model that can be used, studied, modified, and shared by anyone without permission.
“South Korea is a semiconductor superpower, especially in memory chips and camera sensor chips, accounting recently for some 18% of the world’s total semiconductor production capacity,” said Sujai Shivakumar, an expert at the Center for Strategic and International Studies (CSIS). “It It accounts for 60.5% and a NAND market share of 52.6%.
According to a study from Rocket Software and Foundry , 76% of IT decision-makers say challenges around accessing mainframe data and contextual metadata are a barrier to mainframe data usage, while 64% view integrating mainframe data with cloud data sources as the primary challenge.
Device spending, which will be more than double the size of data center spending, will largely be driven by replacements for the laptops, mobile phones, tablets and other hardware purchased during the work-from-home, study-from-home, entertain-at-home era of 2020 and 2021, Lovelock says.
However, there are also challenges: one study showed that models tend to recognize their own answers and rate them better than those of others. At the same time, he is studyingbusiness informatics at the University of Hamburg. This approach enables new possibilities that go beyond classic metrics.
For example, GenAI must be seen as a core element of the business strategy itself. For now, 51% say this strategic alignment has not been fully achieved, according to NTT DATAs study. [3] Data readiness and governance are critical to success and must be addressed in tandem with business process transformation. 3] Preparation.
How can business leaders balance these two conflicting considerations? Enter GenBI, the new generation of businessintelligence GenBI aims to resolve this dilemma by marrying GenAI and businessintelligence (BI). This raises the serious risk that an LLM could reveal sensitive proprietary business information.
At the same time, studies have shown that more working hours do not necessarily lead to better productivity but to worse productivity. If we are not in a position to work hard, then who will work hard? Murthys proposal has previously been criticized for posing serious health risks and a lack of work-life balance.
To regularly train models needed for use cases specific to their business, CIOs need to establish pipelines of AI-ready data, incorporating new methods for collecting, cleansing, and cataloguing enterprise information. Further Gartner research conducted recently of data management leaders suggests that most organizations arent there yet.
We organize all of the trending information in your field so you don't have to. Join 83,000+ 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