Enterprises and service providers are facing a talent crunch that requires them to double down on employee engagement programs to attract and retain people with critical skill sets, says an expert with Information Services Group, a leading global technology research and advisory firm. "When employees are engaged in the corporate culture, have visibility to the executive team and are confident the company values their input, they are significantly less likely to leave. In talent landscape, this is a competitive advantage." Speaking at the All Day DevOps virtual event today, Ola Chowning, partner, ISG Digital Strategy and Solutions, said companies need to engage employees and ensure they are noticed, recognized, heard and valued to improve retention. Chowning made her comments during a 30-minute online presentation, "Skill Shift 2022 – From Deep to Wide, Hard To Soft," her fifth consecutive appearance at the annual event, the largest of its kind in the industry.

Mala Anand, author of this opinion piece, is president of intelligent enterprise solutions and industries at SAP. The rising concern about how AI systems can embody ethical judgments and moral values are prompting the right questions. Too often, however, the answer seems to be to blame the technology or the technologists. Delegating responsibility is not the answer. Creating ethical and effective AI applications requires engagement from the entire C-suite.

I have a confession: AI ethics makes my brain hurt. The issues and questions are that big. Never mind corporate behavior; people, governments, policies and global geopolitics will all evolve differently depending on how we answer those questions. My brain is hurting right now. But if you're a marketer planning to use AI, you're going to hurt a lot more than your brain if you don't start examining the ethical questions.

When a text arrives from an Uber driver, a password message from Netflix, or an SMS regarding an Airbnb booking, these were created by developers using a communications platform called Twilio. Founded in 2008 by its chief executive, Jeff Lawson, Twilio was given a "unicorn" billion dollar valuation by private investors, even before its IPO in 2016. The 800-strong business services more than 40,000 clients, although the bulk of its revenue is servicing the needs of its fellow San Francisco tech giants. Mr Lawson believes that the firm has often succeeded against the odds, particularly when raising money amidst the chaos of the financial crisis. "We pitched to a slew of venture capitalist firms to raise money before launching. One meeting happened on the day Lehman Brothers collapsed. You can bet that didn't go well," he says.

This piece was coauthored with Megan Beck, Chief Insights Officer at OpenMatters, and Steven Cracknell, advisor to OpenMatters. For most of the history of business, leaders and organizations have focused on the physical--extracting, manufacturing, and selling goods. Today, technology has advanced to enable companies to trade on the intangible, but ideas and relationships are much harder to measure and manage than production and inventory, which has left many leadership teams without a compass. Luckily, machine learning and big data analytics are helping executives close the gap and manage the intangible. Data science used to be expensive and academic, yet today technology is enabling organizations to (1) gather and (2) analyze more data than ever.

Our work focused on how, in the coming age where big data and machine learning algorithms enable you to learn and infer stuff about individuals that are profoundly invasive, marketers – and companies in general – will need to openly explore where their ethical boundaries lay. Before we get into it, I have a confession: AI ethics makes my brain hurt. The issues and questions are that big. Never mind corporate behavior; people, governments, policies and global geopolitics will all evolve differently depending on how we answer those questions. My brain is hurting right now. But if you're a marketer planning to use AI, you're going to hurt a lot more than your brain if you don't start examining the ethical questions.

Real-world social networks are dynamic in nature. Companies continue to collaborate, align strategically, acquire, and merge over time, and receive positive/negative impact from other companies. Consequently, their performance changes with time. If one can understand what types of network changes affect a company's value, he/she can predict the future value of the company, grasp industry innovations, and make business more successful. However, it often requires continuous records of relational changes, which are often difficult to track for companies, and the models of mining longitudinal network are quite complicated. In this study, we developed algorithms and a system to infer large-scale evolutionary company networks from public news during 1981--2009. Then, based on how networks change over time, as well as the financial information of the companies, we predicted company profit growth. This is the first study of longitudinal network-mining-based company performance analysis in the literature.