Being a supervisor--a manager, a team leader, whatever title that comes with the territory--isn't the same as it was just a few short years ago. This is especially true in contact, service, and communications centers. After years of enterprises planning for digital transformation and technology innovations that could turn the contact center into a more connected, omnichannel, omnipresent engagement hub, the COVID-19 pandemic accelerated that pathway to change. Carefully laid-out five-year plans were tossed out the window. Suddenly the teeming floors of contact centers were empty, with workers sent home armed with new laptops and headsets.

According to the 2021 Accenture Technology Vision report, the rise of the mirrored world is being driven by leaders who are building vast networks of interlinked intelligent twins that comprise living models of whole factories, product lifecycles, supply chains, ports and even cities. They are bringing together data and intelligence to both represent the physical world in a digital space and to address bigger challenges. The opportunities on offer in the mirrored world are a direct reflection of the extent to which businesses connect intelligent twins. Already, twins enable organizations to gather, visualize and contextualize data across projects and operations, using AI to run scenario modeling. But soon, leaders will have made data and intelligence the primary orchestrators of the business, increasing real-time agility at scale, overhauling their innovation processes and forming entirely new ecosystems and partnerships.

When businesspeople think of important corporate assets, they often start by picturing physical things such as office buildings, computers and printers. This is great news for you in your role as a chief financial officer (CFO). You have a creative opportunity to use all the income, expense, payment, invoice, cash flow, customer and other types of data to generate more valuable insights. These insights lead to more intelligent business decisions. Those include deeper understandings of your cash flows so you can plan where to make investments in the future.

Abstract--In the era of the Internet of information, we have gone through layering, cross-layer, and cross-system desi gn paradigms. Recently, the "curse of modeling" and "curse of d i-mensionality" of the cross-system design paradigm have res ulted in the popularity of using artificial intelligence (AI) to op timize the Internet of information. However, many significant rese arch challenges remain to be addressed for the AI approach, inclu ding the lack of high-quality training data due to privacy and resources constraints in this data-driven approach. T o add ress these challenges, we need to take a look at humans' cooperati on in a larger time scale. T o facilitate cooperation in modern h istory, we have built three major technologies: "grid of transporta tion", "grid of energy", and "the Internet of information". In this paper, we argue that the next cooperation paradigm could be the "Internet of intelligence (Intelligence-Net)", where intelligence can be easily obtained like energy and information, enabled by the recent advances in blockchain technology. We present so me recent advances in these areas, and discuss some open issues and challenges that need to be addressed in the future. The Internet has become one of the major foundations for our socioeconomic systems by enabling information exchan ge among people and machines.

At Build 2016, Microsoft CEO, Satya Nadella, outlined our approach for the new era of conversational intelligence, based on a belief that the most impactful data-driven solutions will go beyond analytics, and utilize the best of big data, cloud, and intelligence capabilities. Microsoft Azure Machine Learning, now part of Cortana Intelligence Suite, is democratizing data and intelligence. Its best-in-class algorithms and simple drag-and-drop interface let data scientists quickly and easily go from idea to deployment. Since Build, I have been working with Azure Machine Learning and the Azure Machine Learning Studio, and thinking about the opportunities for partners to add more value to business intelligence, reporting, SharePoint, and data engagements. This is really a new monetary stream for your customer where they can provide their IP and domain expertise as a service to their customers. In this age of technologies, business decision makers are looking for ways to bring in other sources of revenue.