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). In addition to using cloud for storage, many modern data architectures make use of cloud computing to analyze and manage data.
The core of their problem is applying AI technology to the data they already have, whether in the cloud, on their premises, or more likely both. This means that the infrastructure needs to provide seamless data mobility and management across these systems. Imagine that you’re a data engineer.
The UK government has introduced an AI assurance platform, offering British businesses a centralized resource for guidance on identifying and managing potential risks associated with AI, as part of efforts to build trust in AI systems. This tool aims to help companies make informed decisions as they develop and implement AI technologies.
New advancements in GenAI technology are set to create more transformative opportunities for tech-savvy enterprises and organisations. The technology can operate autonomously, make decisions based on real-time analysis and, critically, execute on decisions. Smart agents are part of a full stack of technologies and services.
As digital transformation advances at a rapid pace, Digital Adoption Platforms (DAPs) have become essential tools for enhancing user experiences and redefining product management strategies. 📆 August 15, 2024 at 11:00 am PT, 2:00 pm ET, 7:00 pm GMT Use Product Management Today’s webinars to earn professional development hours!
AI is at the core of this vision, driving smart governance, efficient resource management, and enhanced quality of life for residents and visitors alike. In the UAE, 91% of consumers know GenAI and 34% use these technologies. Positioning the country at the forefront of AI development.
Laying the foundations for generative AI requires a business-wide approach to data-driven decision-making that empowers the entire workforce to take full advantage of the technology while offering confidence and assurance to the business that it is safe and secure to embark on this journey.
According to a recent survey by Foundry , nearly all respondents (97%) reported that their organization is impacted by digital friction, defined as the unnecessary effort an employee must exert to use data or technology for work. Managed, on the other hand, it can boost operations, efficiency, and resiliency. The good news?
Some did manage to scale agile and leverage frameworks to create process standards and improve IT practices. As SaaS and other technology companies began to abandon traditional project management, product-based IT became a bold shift to business value. But many enterprises stopped their agile transformations at this layer.
Today, many B2B companies use ABM teams or technologies to make sales. Watch this webinar with Rachael Foster, Director of Account-Based Experience at ZoomInfo, and Dan Dolph, Manager of Account-Based Experience at ZoomInfo. Account-based marketing (ABM) is a key strategy for driving sustainable growth.
The technology is relatively new, but all the major players are already on board. Then in November, the company revealed its Azure AI Agent Service, a fully-managed service that lets enterprises build, deploy and scale agents quickly. Weve developed our own agentic AI for code management, says Charles Clancy, CTO at Mitre.
To keep ahead of the curve, CIOs should continuously evaluate their business and technology strategies, adjusting them as necessary to address rapidly evolving technology, business, and economic practices. Over the next 12 months, IT leaders can look forward to even more innovations, as well as some serious challenges.
Courage and the ability to manage risk In the past, implementing bold technological ideas required substantial financial investment. Effective IT leadership now demands not only the courage to innovate but also a profound understanding of change management principles. Gen AI isn’t a simple plug-and-play solution.
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. CIOs should create proofs of concept that test how costs will scale, not just how the technology works.”
Speaker: Aindra Misra, Sr. Staff Product Manager of Data & AI at BILL (Previously PM Lead at Twitter/X)
Delve into the distinctive roles and responsibilities of a Platform PM compared to other Product Managers. Explore the array of tools and technologies driving data transformation across different stages and states, from source to destination. Anticipated future use cases as we project into 2024 and beyond.
It says our job as technology leaders can help educate our audience on what is possible and what it will take to get to their goal. The implications of the ongoing misperception about the data management needs of AI are huge, Armstrong adds. Gen AI uses huge amounts of energy compared to some other AI tools, he notes.
To overcome those challenges and successfully scale AI enterprise-wide, organizations must create a modern data architecture leveraging a mix of technologies, capabilities, and approaches including data lakehouses, data fabric, and data mesh. Before we go further, let’s quickly define what we mean by each of these terms.
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.
Aligning ESG and technological innovation At the core of this transformation is the CIO, a pivotal player whose role has expanded beyond managingtechnological innovation to overseeing how these innovations contribute to ESG goals. It provides CIOs a roadmap to align these technologies with their organizations’ ESG goals.
Omni-channel retailing puts even greater importance on the ability to manage and integrate data effectively across the enterprise. What excites me is the critical role technology plays in enabling this. What are some technology solutions that are driving your growth? How did you achieve this integration?
Another example of the model in action is in our Non-Emergency Medical Transportation (NEMT) service line, which has enabled us to put technology in the hands of our clients to manage their own experiences. In my next CIO role, I inherited an enablement team, which really was product management as we know it now.
As the technology subsists on data, customer trust and their confidential information are at stake—and enterprises cannot afford to overlook its pitfalls. While it may sound simplistic, the first step towards managing high-quality data and right-sizing AI is defining the GenAI use cases for your business.
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. Most importantly, position technical debt management not as a cost center, but as an investment in business agility and competitive advantage. Double down on automation through AI.
In this engaging and witty talk, industry expert Conrado Morlan will explore how artificial intelligence can transform the daily tasks of product managers into streamlined, efficient processes. The Future of Product Management 🔮 How to continuously integrate AI into your work to stay ahead of emerging trends and technologies.
A number of issues contribute to the problem, including a highly distributed workforce, siloed technology systems, the massive growth in data, and more. AI and related technologies, such as machine learning (ML), enable content management systems to take away much of that classification work from users. “AI
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. By 2029, 10% of global boards will use AI guidance to challenge executive decisions that are material to their business.
We’re in publishing, but it’s the accompanying services that differentiate us on the market; the technology component is what gives value to our business.” Much of this growth is driven by investments in AI technologies, and IDC also expects cloud infrastructure spend to increase 26% compared to 2023.
In fact, gen AI isn’t currently among the implemented technologies at Euronics because Tesoro doesn’t see use cases functional to the retail activity. “IT I give directions and strategies to the supplier and the partner, and an internal project manager acts as a link. IT must be at the service of the business,” he says.
However, investing in new technology isn’t always easy, and commonly, it’s difficult to show the ROI of data quality efforts. Download this eBook and gain an understanding of the impact of data management on your company’s ROI. The digital age has brought about increased investment in data quality solutions.
Data silos, lack of standardization, and uncertainty over compliance with privacy regulations can limit accessibility and compromise data quality, but modern data management can overcome those challenges. Some of the key applications of modern data management are to assess quality, identify gaps, and organize data for AI model building.
Technology has shifted from a back-office function to a core enabler of business growth, innovation, and competitive advantage. 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.
The bigplayers,such as OTAs [Online Travel Agencies], are advancing in their adoption of new technologies, taking advantage of AI andbig datatools,while other actors are in earlier stages of integration, he says. In addition, Abril highlights specific benefits gained from applying new technologies.
Agentic AI was the big breakthrough technology for gen AI last year, and this year, enterprises will deploy these systems at scale. If all your technology is buried and not exposed through the right set of APIs, and through a flexible set of microservices, itll be hard to deliver agentic experiences. Not all of that is gen AI, though.
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.
Generative AI is likely to confuse the capital investor as much as any technology ever has,” he adds. In many cases, CIOs and other IT leaders have moved past the peak expectations about what gen AI can do for their organizations and are headed into more realistic ideas about the future of the technology, Lovelock adds.
Technology continues to advance at a furious pace. When addressed properly , application and platform modernization drives immense value and positions organizations ahead of their competition, says Anindeep Kar, a consultant with technology research and advisory firm ISG.
Adopting Operational AI Organizations looking to adopt Operational AI must consider three core implementation pillars: people, process, and technology. 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.
In an era where technology reshapes entire industries, I’ve had the privilege of leading Mastercard on an extraordinary journey. When I think about the technology we started working with early in my career and look at what we’ve been able to do since, it truly is amazing, a global transformation led by and driven through technology.
Once the province of the data warehouse team, data management has increasingly become a C-suite priority, with data quality seen as key for both customer experience and business performance. A golden dataset of questions paired with a gold standard response can help you quickly benchmark new models as the technology improves.
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.
The Middle East is rapidly evolving into a global hub for technological innovation, with 2025 set to be a pivotal year in the regions digital landscape. Looking ahead to 2025, Lalchandani identifies several technological trends that will define the Middle Easts digital landscape.
This is frustrating for technology providers who have made big bets on AI. A recent survey conducted by Censuswide on behalf of Red Hat polled 609 IT managers across the United Kingdom and other major markets. AI continues to shape cloud strategies, but AI implementation is going slower than most predicted. What’s going on?
But because Article was growing so quickly, managing one of the largest student housing portfolios in the US, it needed to be more intentional about operational efficiency. There are a lot of moving parts acrossour properties, says Erica White, the companys SVP of technology and strategic innovation.
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