machinelearning
A number of obstacles stand in the way of IT leaders looking to address their enterprise content management objectives, but two stand out: a proliferation of tools and an inability to effectively integrate them. Coupled with the rapid rate of content growth, it’s little wonder that a Forrester survey shows 42% of enterprises report having large amounts of critical content effectively hidden in information silos across the organization. The solution involves choosing a content management platform upon which you can add the specific tools you need with the assurance they are well-integrated with...
CIO
Intelligent document processing (IDP) is changing the dynamic of a longstanding enterprise content management problem: dealing with unstructured content. By applying artificial intelligence capabilities, IDP enables companies to automate the processing of virtually any type of content, from paper, emails and PDFs to forms, images, and Word documents. Gartner estimates unstructured content makes up 80% to 90% of all new data and is growing three times faster than structured data. The ability to effectively wrangle all that data can have a profound, positive impact on numerous document-intensive...
CIO
Enterprise content management (ECM) systems have long given employees easy access to whatever content they need to do their jobs. As explained in a previous post, with the advent of AI-based tools and intelligent document processing (IDP) systems, ECM tools can now go further by automating many processes that were once completely manual. Potential use cases spread across vertical industries that are steeped in document-intensive processes, including healthcare, financial services, banking, and insurance. They also extend to back-office functions that all companies engage in, such as accounts r...
CIO
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. In this post, we’ll touch on three such case studies. Global insurance companyA large insurance company adopted a cloud-based document management system to enable paperless operations around the world and simplify regulatory compliance. The organization had some tactical document management systems, but they were siloed and based on slow, outdated technology. Plus, all ...
CIO
Integrating artificial intelligence (AI) into enterprise edge ecosystems is a strategic imperative. AI at the edge delivers unprecedented speed, efficiency, and agility that impacts business outcomes by enhancing operational efficiency, reducing latency, and unlocking new avenues for innovation. But success at the edge demands a unified, simplified way to deploy, manage, and scale locations without ready access to IT staff. Dell NativeEdge is ready to help you reach your edge AI goals. AI has rapidly become an enterprise imperative, providing efficiency gains, real-time insights, and new level...
CIO
The promise of the smarter city Smart cities offer the promise of a thriving urban ecosystem that seamlessly blends technology, systems, and people to optimize everything from traffic flow to energy consumption. Public services in smart cities operating at peak efficiency, deliver convenient access to accurate information, resources, and community engagement essentials. Residents’ movements become effortless throughout the smart city, relying on optimized and efficient public transportation, connected vehicles, and intelligent adaptive traffic management. Behind the scenes, data augmented with...
CIO
The cloud computing revolution brought with it many innovations, but also lessons about the pitfalls of rapidly adopting new technologies without a well-planned strategy. Today, IT leaders are at a similar crossroads with the rise of generative AI. As organizations build their AI factories today in this new era, IT leaders have an opportunity to learn from their cloud-first sins of the past and strategically build in a way that prioritizes security, governance, and cost efficiencies over the long term, avoiding errors that might need to be corrected down the line. The cloud retrospective: A le...
CIO
With the rapid evolution of digital technologies over the past decade, IT is finding its “hero” status, enabling organizations to navigate the many twists and turns. And, like most things in life, when you do things well, you’re asked to do more of it. This means CIOs are increasingly viewed as responsible not only for traditional IT roles such as managing IT departments and infrastructure but also driving innovation—the kind that fuels business growth (80% of business executives agree, according to a Deloitte survey). GenAI is one of those innovations. AI, of course, isn’t new. IT teams have ...
CIO
Agents come in many forms, many of which respond to prompts humans issue through text or speech. Yet as organizations figure out how generative AI fits into their plans, IT leaders would do well to pay close attention to one emerging category: multiagent systems. In such systems, multiple agents execute tasks intended to achieve an overarching goal, such as automating payroll, HR processes, and even software development, based on text, images, audio, and video from large language models (LLMs). Eighty-two percent of leaders surveyed by Capgemini said they expect to integrate them into their bu...
CIO
A long-held opinion about AI capabilities is that bigger and more are better. Bigger models, with more data, invariably equal better AI experiences. Today’s market reality is starkly different. It turns out companies adopting generative AI today don’t need models with 1 trillion parameters or even hundreds of billions of parameters frontier LLMs are trained on. Instead, many organizations are adopting small language models (SLMs) customized to handle specific tasks. Such model sizes range from one hundred million to one hundred billion parameters; many can run on PCs or even smartphones. Who k...
CIO
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