Artificial Intelligence in Workforce Management Systems

May 21, 2019

Artificial intelligence (AI) was formally founded as an academic discipline at a conference in 1956, long before workforce management (WFM) systems became a staple in the contact center. In the years since, AI initiatives and enthusiasm have ebbed and flowed, but there’s been a recent surge in interest and investment due to advancements in computing power, an explosion of data collection and the business need to seek increased productivity and profitability through technology.

Spotlight

Hitachi Data Systems

Digital transformation improves enterprises’ cost-efficiency, time to market, customer experience, and revenue through better data management. Hitachi Data Systems uses data to power the digital enterprise.

OTHER WHITEPAPERS
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Embedding AI-powered Analytics Into Your Application

whitePaper | September 28, 2022

Your customers need more than dashboards. They need instant, actionable insights and analytics. And you need to offer more than basic analytics to futureproof your application. Learn how embedding AI-powered analytics gives you a sustainable competitive advantage. Download the complete guide today.

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AI Test Drive clears the way for business case validation

whitePaper | August 26, 2022

Evolving data centers into intelligent hubs for digitized business processes poses numerous challenges for IT managers. Many organizations are already adopting hybrid IT concepts to make their data center operations more flexible. However, they also have to keep an eye on new requirements such as IoT, AI, blockchain, container technology as well as data security, legal regulations and climate change. How can all this be seamlessly integrated and managed? And, what will matter next for the data center of the future?

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Maximising theAI opportunity

whitePaper | November 1, 2019

Artificial Intelligence is becoming an ever more important part of our lives. Many of us are already familiar with its everyday applications, such as decluttering our inboxes with spam filters or receiving personalised shopping recommendations. Yet, whether it is powering a new generation of self-driving cars, guarding us against fraud or helping doctors better diagnose health conditions, AI’s transformational abilities are being felt in increasingly ubiquitous and innovative ways.

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Democratizing AI: Transforming Your Operating Model to Support AI Adoption

whitePaper | May 20, 2021

AI has become a strategic imperative. Early adopters are achieving massive returns, while others risk falling behind. Yet, with AI knowledge and resources scarce, most companies cannot copy the FAANG approach. Even if their vast resources were more readily available, it’s hard to reboot an organization without disrupting the bottom line. Most executives need to work with the resources available — their existing people, processes, and technology.

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HFS Enterprise AI Services Top 10

whitePaper | January 12, 2020

“The services market for artificial intelligence technologies is rapidly maturing on the back of several years of learning and a realization—delivering AI is unlike delivering any other technology thus far. Delivering on the promise of AI calls for far more collaboration between service providers, tech vendors, and enterprise clients.” The biggest differentiator in enterprise AI services, as described by most of the customer leaders, is the quality of people—not just the quantity available for a specific skill. Domain understanding and data engineering capabilities are top priorities. A culture of innovation, experimentation, collaboration, and co creation with customers is the key winning formula here.”

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Getting Started with Data Acquisition Systems

whitePaper | August 6, 2020

The purpose of any data acquisition system is to gather useful measurement data for characterization, monitoring, or control. The specific parameters of your application will dictate the resolution, accuracy, channel count, and speed requirements of a data acquisition system. A wide assortment of data acquisition components and solutions is available on the market, including low-cost USB modules, benchtop data loggers, and large channel systems. Before you start your search for a data acquisition solution, carefully analyze your application requirements to understand how much capability and performance you need to purchase.

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Spotlight

Hitachi Data Systems

Digital transformation improves enterprises’ cost-efficiency, time to market, customer experience, and revenue through better data management. Hitachi Data Systems uses data to power the digital enterprise.

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