The transformation of workplaces over the past two years has led U.S. enterprises to create more flexible, collaborative work environments to better attract and retain employees, according to a new research report published today by Information Services Group (ISG) (Nasdaq: III), a leading global technology research and advisory firm. "Now they are defining business and operating models at companies facing rapid changes in work styles and environments." The 2022 ISG Provider Lens Future of Work -- Services and Solutions report for the U.S. finds many organizations in the U.S. are already successfully moving toward a modern workplace, while others have plans for digital workplace transformations to ensure business continuity and growth. Companies are focused on enhancing communication and employee well-being and managing cultural shifts among different generations of workers, ISG says. "U.S. enterprises want to design experiences that meet the expectations of employees for consistency of service, regardless of location or device, and ease of use," said Jim Kane, director, Collaboration and Experience at ISG. "Many enterprises are seeking service providers to help them develop workplace transformation strategies that cover a range of channels and ensure the service experience is secure."

When cloud and machine learning technologies are used together, it is called a cognitive cloud, which can be used to access cognitive computing applications. Cognitive Cloud uses various machine learning algorithms such as neural networks, pattern recognition, natural language processing, data mining, etc. to perform human-like actions. Applying Machine Learning Algorithms Using Cognitive Cloud Computing Cognitive computing is a specific type of technology that uses artificial intelligence and signal processing to reflect human actions. When large amounts of data are applied to certain algorithms, we can create machine learning (ML) models, and it becomes important to use the cloud for this. Furthermore, cloud computing processes large amounts of data for training machine learning models; thus, business intelligence becomes important for storing raw data.

Run a Google search on "bias in AI" and you'll find all kinds of stories about what can -- and does -- happen when systems become automated and the human element is removed. Of course, today, AI and machine learning are embedded into myriad different technologies, and while it no doubt plays a positive role, biased data is often problematic. As AI applications become more prevalent, channel firms can play a role in helping customers mitigate algorithm bias. Biased AI ranked the second biggest AI-related ethical concern associated with AI in Deloitte's 2018 "State of AI in the Enterprise" study, behind AI's power to help create and spread false information. "Today, algorithms are commonly used to help make many important decisions, such as granting credit, detecting crime, and assigning punishment," the report notes.

Successful artificial intelligence (AI) implementations rarely hinge on the unique innovation of a specific algorithm or data science technique. Those are important factors, but even more foundational to successful AI enablement are the core data operations and enabling platforms. These act as the fuel and chassis of the AI machine that a business must build and evolve for continued competitive advantage. Successful digital transformations focus on evolving and optimizing business operations through the better use of data assets combined with modern technologies such as machine learning (ML), AI, and robotics. These paradigm shifts result in the creation of new operating patterns rather than simply more efficient legacy operations. In this way, digital transformation represents enterprise operations in the way the business wants to be run, rather than the way it has been running due to technical and operational limitations and barriers constraining it.

Five technology trends are poised to transform the future of work beginning in 2020, DXC Technology announced as part of an annual forecast. The rapid adoption of emerging technologies such as artificial intelligence (AI) and machine learning (ML) coupled with trusted data ecosystems, empowered interconnected teams and tech-evangelist leaders promises to produce new levels of workforce efficiency, productivity and growth across enterprises. "In turn, CEOs will seek to identify and pursue ecosystem-centric business models and trading partners that deploy trusted and compliant data-sharing practices." "The notion of accelerated productivity will force enterprises to rethink their technology decisions and investments across the enterprise technology stack, which, in turn, will drive a sea change in how enterprises are led and structured, make informed decisions and engage employees and customers," said Dan Hushon, senior vice president and chief technology officer, DXC. "Tech-evangelist leaders will define new interactions between AI and people to create high-performing teams and shape digital strategies that unlock an organization's full potential – securely and confidently modernizing applications, optimizing data architectures and moving workloads to the cloud to produce new and better business outcomes."

SINGAPORE--(BUSINESS WIRE)--Oct 25, 2018--DXC Technology (NYSE: DXC), the world's leading independent, end-to-end IT services company, today announced the opening of the DXC Digital Innovation Lab in Singapore. Developed with the support of the Singapore Economic Development Board (EDB), the DXC Digital Innovation Lab Singapore is an advanced environment for the incubation of ideas, learning and innovative technology solutions developed by data scientists and enterprise solution experts. The lab will benefit DXC employees, clients and partners, as well as the technology and business communities of Singapore, the region and beyond. The DXC Digital Innovation Lab Singapore is an extension of DXC Labs, whose goal is to ensure that DXC masters the emerging technologies it needs in order to lead clients through accelerating digital transformation. At the innovation lab, digital specialists will explore novel technologies, develop prototypes and create reference architectures for rapid business deployment.

In 2018, we'll see an aggressive move to common IT platforms so companies can respond to market changes faster, be more productive and make better-informed decisions. These common platforms are rich in analytics, follow the information flow of the business and are simple enough that users can constantly change the business without writing (much) code. Moreover, they bring an operational and evergreen scale to traditionally bespoke enterprise IT. These common platforms -- from Amazon, Microsoft, Google and others -- provide very suitable if not substantially improved replacements for what used to be custom builds. "This is about the technology you need, not the technology you make," emphasizes Dan Hushon, CTO of DXC Technology.

In the 2013 movie Her, a virtual personal assistant named Samantha quickly evolves from merely competent to awesomely so. Rather than merely scheduling meetings, Samantha becomes a life coach, cajoling the main character, Theodore, a writer, to publish his letters and to move on with his divorce. That movie is science fiction, but those who are attuned to the rapid improvements in artificial intelligence say a version of Samantha (minus the later romantic attachment and singularity) is on the near horizon. For businesses, the promise of AI is that Samanthas will be embedded across all aspects of the organization. Such agents will analyze data, discover patterns over time and then make decisions based on predictive analysis.

Organizations that thrive on change use data and analytics as a competitive asset. They adapt quickly and predict trends by continuously curating and analyzing data and developing insights that drive new value. These organizations have a high "analytics IQ," and they will be the disruptors, not the disrupted, in the digital revolution. Those that successfully harvest vast troves of data can improve productivity; make faster and more accurate decisions; reduce costs; increase competitive advantage; discover new business models and innovations; and better engage customers, employees, and partners. IT has long played a critical role in helping organizations deliver better products and services, improve operations, better manage risks, and develop new business models to stay relevant.