This paper introduces transformer-based language models to the literature measuring corporate culture from text documents. We compile a unique data set of employee reviews that were labeled by human evaluators with respect to the information the reviews reveal about the firms' corporate culture. Using this data set, we fine-tune state-of-the-art transformer-based language models to perform the same classification task. In out-of-sample predictions, our language models classify 17 to 30 percentage points more of employee reviews in line with human evaluators than traditional approaches of text classification. We make our models publicly available.

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.

As artificial intelligence matures and expands within enterprises, leaders across industries are struggling to get everyone on board. At the same time, they must manage customer and employee relationships amid shifting expectations in an era of digital transformation. The latest ideas from MIT Sloan Management Review consider how to overcome the barriers of AI implementation and go all in on putting AI tools into production. Leaders will also learn how to know what customers want, how to avoid a toxic workplace, and how to run effective brainstorming sessions. AI-powered decision-making tools have the potential to increase efficiency, improve service quality, reduce costs, and boost revenue.

Many of today's business challenges revolve around two core topics: navigating digital transformation and retaining talent. The latest insights from MIT Sloan Management Review focus on looking past common misconceptions about digital initiatives, setting the right KPIs for digital transformation success, and changing corporate culture and business operations so employees are more likely to stay. Just as today's business leaders should rethink common assumptions about the world of work and re-examine customer expectations, they may also need a new mindset about driving change. MIT Sloan senior lecturer George Westerman identifies four managerial assumptions about digital transformation that prevent enterprises from reaching their true potential. This emphasizes digital but not transformation -- the more difficult (and more important) element to address.

Artificial intelligence is definitely one of the most divisive technologies of our time. Some people see it as the key to unlocking new levels of human potential, while others view it as a tool for Replacing humans in the workforce. Despite these concerns, businesses have been eagerly adopting AI into their operations. Many experts believe that this is because AI can actually improve corporate culture in some very significant ways. The article discusses how artificial intelligence is reshaping the culture in the corporate world.

Contrary to press-propagated blames on rapid industry changes, unforeseen circumstances and uncontrollable crises, most business failures boil down to poor corporate culture. Interestingly, how corporate culture is perceived has changed just as rapidly as industries have evolved in recent times. In the 20th and early 21st centuries, assessment of corporate culture focused almost entirely on how businesses treated their customers. For instance, the dent in Blackberry's culture was caused by the company prioritizing its smartphone technology over customers' needs. Meanwhile, how customers interact with technology was changing. More recently, corporate culture has more to do with how companies manage communication internally than with their public relations.

More than 40% of all employees were thinking about leaving their jobs at the beginning of 2021, and as the year went on, workers quit in unprecedented numbers.1 Between April and September 2021, more than 24 million American employees left their jobs, an all-time record.2 As the Great Resignation rolls on, business leaders are struggling to make sense of the factors driving the mass exodus. More importantly, they are looking for ways to hold on to valued employees. To better understand the sources of the Great Resignation and help leaders respond effectively, we analyzed 34 million online employee profiles to identify U.S. workers who left their employer for any reason (including quitting, retiring, or being laid off) between April and September 2021.3 The data, from Revelio Labs, where one of us (Ben) is the CEO, enabled us to estimate company-level attrition rates for the Culture 500, a sample of large, mainly for-profit companies that together employ nearly one-quarter of the private-sector workforce in the United States.4 Monthly research-based updates on what the future of work means for your workplace, teams, and culture. While resignation rates are high on average, they are not uniform across companies.

You could become your own worst enemy. CEOs and other managers are increasingly under the microscope as some investors use artificial intelligence to learn and analyze their language patterns and tone, opening up a new frontier of opportunities to slip up. In late 2020, according to language pattern software specialist Evan Schnidman, some executives in the IT industry were playing down the possibility of semiconductor chip shortages while discussing supply-chain disruptions. All was fine, they said. Yet the tone of their speech showed high levels of uncertainty, according to an algorithmic analysis designed to spot hidden clues in -- ideally unscripted -- spoken words. "We found that IT sector executives' tone was inconsistent with the positive textual sentiment of their remarks," said Schnidman, who advises two fintech companies behind the analysis.

Natural language processing (NLP) increasingly popular Investors seek edge in world of'unstructured data' But CEOs are cottoning on, with more speech scripted Investors seek edge in world of'unstructured data' LONDON, Oct 20 (Reuters) - Executives, beware! You could become your own worst enemy. CEOs and other managers are increasingly under the microscope as some investors use artificial intelligence to learn and analyse their language patterns and tone, opening up a new frontier of opportunities to slip up. In late 2020, according to language pattern software specialist Evan Schnidman, some executives in the IT industry were playing down the possibility of semiconductor chip shortages while discussing supply-chain disruptions. All was fine, they said.

LONDON (Reuters) - Executives, beware! You could become your own worst enemy. CEOs and other managers are increasingly under the microscope as some investors use artificial intelligence to learn and analyse their language patterns and tone, opening up a new frontier of opportunities to slip up. In late 2020, according to language pattern software specialist Evan Schnidman, some executives in the IT industry were playing down the possibility of semiconductor chip shortages while discussing supply-chain disruptions. All was fine, they said.