Have a conversation with anyone about how the changing nature of technology is affecting our world, and artificial intelligence (AI) will invariably come up. It has the potential to change all industries in ways we’ve never experienced. The promise of AI is that it will make our lives better, with more lower-level tasks being automated, freeing us up to focus on higher-level endeavors. Automation promises to complete tasks with more efficiency than humans do, and can continually improve through machine learning.
It’s time to move your supply chain into the realm of super-intelligent.
This special report is for anyone looking to enhance their supply chain operations by utilizing the latest in technological advances such as artificial intelligence (AI), machine learning and the Internet of Things (IoT). With smart use of these tools, businesses can anticipate problems and develop solutions before they occur.
Forward-thinking leaders are using this disruption to optimize their supply chains and push the quality of their findings to a whole new level.
In it, you’ll learn:
• The markers of a truly cognitive supply chain
• The crucial role of location intelligence in supply chain optimization
• The impact increased visibility has on every area of your supply chain, including asset, inventory, fleet and energy management
As businesses start to experiment with true artificial intelligence, safe delivery of AI demands a new risk and control framework. This report, designed for anyone tasked with the safe delivery of AI, proposes an effective solution.
Read the report to find out:
• the risks associated with AI and the challenge of managing them
• a 17-category Risk & Controls framework for AI
• in-depth details for key categories, including security management, business continuity and knowledge management
• an essential glossary of AI terms.
Connected Intelligence in Insurance
Insurance as we know it is transforming dramatically, thanks to capabilities brought about by new technologies such as machine learning and artificial intelligence (AI).
Download this IDC Analyst Infobrief to learn about how the new breed of insurers are becoming more personalized, more predictive, and more real-time than ever.
What you will learn:
The insurance industry's global digital trends, supported by data and analysis
What capabilities will make the insurers of the future become disruptors in their industry
Notable leaders based on IDC Financial Insights research and their respective use cases
Essential guidance from IDC
TIBCO® Connected Intelligence for Smart Factory Insights
By processing real-time data from machine sensors using artificial intelligence and machine learning, it's possible to predict critical events and take preventive action to avoid problems. TIBCO helps manufacturers around the world predict issues with greater accuracy, reduce downtime, increase quality, and improve yield.
Mountains of data promise valuable insights and innovation for businesses that rethink and redesign their system architectures. But companies that don’t re-architect might find themselves scrambling just to keep from being buried in the avalanche of data.
The problem is not just in storing raw data, though. For businesses to stay competitive, they need to quickly and cost-effectively access and process all that data for business insights, research, artificial intelligence (AI), and other uses. Both memory and storage are required to enable this level of processing, and companies struggle to balance high costs against limited capacities and performance constraints.
The challenge is even more daunting because different types of memory and storage are required for different workloads. Furthermore, multiple technologies might be used together to achieve the optimal tradeoff in cost versus performance.
Intel is addressing these challenges with new memory and storage technologies that emp
Organizations in the global industrial products industry face significant challenges: cost pressures, increased regulations, disruptive technologies and the increasingly costly delivery of raw resources. High volatility in commodity prices has put severe pressure on company margins and can quickly expose inefficient operations.
Every commercial organization wants to grow. THrough its unlimited processing power Artificial Intelligence (AI) has the power to make that growth a reality. However, established workflows and processes often hamper the application of true AI, so how do organizations get started on digital transformation without disrupting their existing operations?
Intelligent content holds the key to digital transformation. But what do we mean by intelligent content? How does it all aid digital transformation? How do you take your first steps forward for building an intelligent formation for AI? What are the misconceptions around AI-led transformations?
This paper provides you with the answers.
Component Content Management: A New Paradigm in Intelligent Content Services
While technology has changed the world, the way that companies manage information has inherently stayed the same. The advent of near-ubiquitous connectivity among applications and machines has resulted in a data deluge that will fundamentally alter the landscape of content management. From mobile devices to intelligent machines, the volume and sophistication of data have surpassed the ability of humans to manage it with outdated methods of collection, processing, storage, and analysis. The opportunity afforded by the advent of artificial intelligence (AI) has stimulated the market to search for a better way to capture, classify, and analyze this data in its journey to digital transformation (DX). The paradigm of document-based information management has proven to be a challenge in finding, reusing, protecting, and extracting value from data in real time. Legacy systems may struggle with fragmented information
AI is fundamentally reshaping business as we know it. It drives innovation, efficiency, productivity, new operational models, and entirely new revenue opportunities. It is no wonder, then, that enterprises of all sizes are keen to adopt this transformative technology.
When embarking on the AI journey, however, it is critical to understand that data is the heart of any effective AI algorithm. So, for any enterprise looking to harness the promise of AI, the first question to ask is quite simply, “is my data ready?”
This technology brief simplifies the path to AI by offering actionable steps to data readiness.
Data management doesn’t come easier than this. Thanks to machine learning, artificial intelligence and the power of the cloud just about anyone can gain insight of their data. Easy to install, just tell the service level what you want and it does the rest. Oracle Autonomous Database self-repairs, patches automatically and counters threats with artificial intelligence. Autonomous for Dummies? We think its pretty smart.
A indústria de petróleo está sendo transformado de maneira dinâmica graças ao poder de conexão da Internet, aos avanços nos sensores conectados remotamente e às possibilidades que o machine learning e a inteligência artificial (IA) oferecem.
À medida que a busca por hidrocarbonetos e fontes alternativas de energia se estende a ambientes mais profundos e hostis, operadores, empresas de serviços e proprietários de ativos estão aproveitando os avanços tecnológicos para garantir que seus funcionários estejam mais seguros, seus campos sejam mais produtivos e seus ativos operem com eficiência máxima.
Os bancos em todo o mundo estão apostando muito em inteligência artificial e machine learning para lhes dar a vantagem tecnológica necessária para obter serviços bancários em tempo real, personalizados e preditivos. Um marco ajudará a diferenciar os primeiros ganhadores e fornecerá vantagens contínuas em inteligência.
Faça o download deste IDC Analyst Infobrief para saber como os melhores bancos do mundo estão se tornando mais pessoais, preditivos e mais em tempo real do que nunca.
O que você conhecerá:
• 8 tendências que refletem o nível de preparação do banco para a inteligência conectada
• 9 armadilhas para evitar e 9 maneiras de pular os obstáculos
• Os elementos básicos pessoais, preditivos e em tempo real da IA e ML para os bancos
• Líderes de destaque com base na pesquisa da IDC Financial Insights e em seus respectivos casos de uso
• Orientação essencial do IDC para os bancos líderes
La industria petrolera se está transformando de manera dinámica gracias el poder de conexión del Internet, los avances en sensores remotos conectados, y las posibilidades que ofrece el machine learning y la inteligencia artificial (IA).
A medida que la búsqueda de hidrocarburos y fuentes de energías alternativas se amplía a entornos más profundos y hostiles, los operadores, las compañías de servicios y los propietarios de los recursos están aprovechando los avances tecnológicos para garantizar que sus empleados estén más seguros, sus campos sean más productivos y sus activos fijos estén operando a su máximo nivel de eficiencia.
Los bancos de todo el mundo están apostando fuertemente a la inteligencia artificial y el machine learning a fin de obtener la ventaja tecnológica que necesitan para ofrecer servicios bancarios más personalizados, predictivos y en tiempo real. Un marco ayudará a diferenciar a los primeros ganadores y ofrecerles ventajas continuas en inteligencia.
Descargue este IDC Analyst Infobrief que le permitirá conocer cómo los mejores bancos del mundo se están volviendo más personales, más predictivos, y más en tiempo real que nunca.
Lo que usted conocerá:
• Las ocho tendencias que reflejan el nivel de preparación de los bancos para la inteligencia conectada
• Los nueve obstáculos que evitar y las nueve formas de salvar las brechas
• Los elementos básicos personales, predictivos y de tiempo real de la IA y el ML para los bancos
• Los líderes destacados de acuerdo con la investigación de IDC Financial Insights y sus respectivos casos de uso
• Una guía esencial de IDC para los bancos líderes
Servicios Financieros es una industria en la que la innovación siempre está presente. Los modelos de negocio transformadores como las casas de bolsa de bajo costo, los productos de inversión innovadores como los fondos de inversión cotizados, y las regulaciones estrictas como Gramm-Leach-Bliley son algunos ejemplos. Otros ejemplos incluyen:
• Las nuevas firmas fintech, como la reciente inversión de nueve mil millones de dólares hecha en Ant Financial Services Group, y un sinnúmero de otras empresas emergentes similares apoyadas con capital de riesgo, están apuntando a segmentos bien establecidos de la industria de servicios financieros.
• Servicios de gestores automatizados potenciados por la inteligencia artificial y el machine learning que apoyan a los asesores financieros y a los gestores de carteras
• Las regulaciones y las leyes para el manejo de riesgos que cambian constantemente, como GDPR, Basilea III y Open Banking, y que transforman la manera en que se interactúa con los
On average, enterprises processed over 200,000 spend transactions last quarter. Finance teams that use artificial intelligence in their spend audit reviewed 100 percent of transactions, versus 2-10 percent of expense reports and 5-10 percent of invoices for teams that didn’t.
On average, enterprises processed over 200,000 spend transactions last quarter. Finance teams that
use artificial intelligence in their spend audit reviewed 100 percent of transactions, versus 2-10 percent
of expense reports and 5-10 percent of invoices for teams that didn’t.
Are you interested in how artificial intelligence (AI) might impact your contact center?
The hype cycle for AI is nearing its peak. But before you rush to deploy an AI tool, let’s separate fact from fiction. What are the practical benefits of AI today? What kind of challenges arise from automation? What are the underlying technologies at play?
In this e-book, we will answer these questions and more. We will examine AI from a pragmatic lens and offer suggestions to minimize costs and maximize returns.
You cannot accurately predict what your customer will want next. Artificial intelligence can.
WHY SHOULD THE TARGET AUDIENCE CARE?
By 2020, businesses that use AI and related technologies like machine learning and deep learning to uncover new insights will take $1.2 trillion each year from competitors that don't. (Source: Forrester.)
At any moment, anywhere in the world, on any kind of device, a prospect or customer is raising her hand and saying, "I'm your best opportunity. Don't ignore me." She's telling you that by every action she's taken and every interaction you've had up to that point. You can consider each bit of data you've collected across her journey a meaningful expression of intent. And with that, you will know how to give her an experience that's above her expectations and beyond her imagination.
You need many different technologies in your marketing stack to manage personalization, but AI makes them all work together seamlessly.
Knowledge workers today have a rich portfolio of team collaboration tools to help them get their jobs done, starting with email and encompassing texting, file sharing, online chat and message boards, social media and video conferencing. Yet collaboration across these tools can be a frustrating experience, due to the complexity of the technology and lack of integration. The good news: the application of emerging technologies and artificial intelligence (AI) enables more people to connect when and how they need to. And that makes for more productive teams.
Artificial intelligence (AI) and machine learning (ML) are emerging technologies that will transform organizations faster than ever before. In the digital transformation era, success will be based on using analytics to discover the insights locked in the massive volume of data being generated today. Historically, these insights were discovered through manually intensive data analytics—but the amount of data continues to grow, as does the complexity of data. AI and ML are the latest tools for data scientists, enabling them to refine the data into value faster.
As digital business evolves, however, we’re finding that the best form of security and enablement will likely remove any real responsibility from users. They will not be required to carry tokens, recall passwords or execute on any security routines. Leveraging machine learning, artificial intelligence, device identity and other technologies will make security stronger, yet far more transparent. From a security standpoint, this will lead to better outcomes for enterprises in terms of breach prevention and data protection. Just as important, however, it will enable authorized users in new ways. They will be able to access the networks, data and collaboration tools they need without friction, saving time and frustration. More time drives increased employee productivity and frictionless access to critical data leads to business agility. Leveraging cloud, mobile and Internet of Things (IoT) infrastructures, enterprises will be able to transform key metrics such as productivity, profitabilit