Two experts predict AI will change the way companies see themselves

However, in the same survey, even more respondents (84%) said their company's culture is not where it needs to be. Once again, the data supports their intuition. Large American employers have an average culture rating of 3.6 out of 5 on Glassdoor, a website where workers can rate their employers. Few people would be thrilled to eat at a restaurant with such a rating or ride with an Uber driver. Similarly, few employees will enjoy spending 40 hours each week in an average culture.

Building and maintaining a healthy company culture can be even more difficult in organizations where employees work remotely. Ongoing research shows that companies whose employees are most engaged with remote work score lower than their peers on culture, particularly learning and development opportunities, and honest communication. Ta.

Leaders can't improve what they can't measure. Unfortunately, engagement surveys, the most common tool for assessing company culture, have significant limitations. When faced with a long list of questions, employees go on autopilot and assign the same or similar score to every question. Employers who ask a large number of multiple-choice questions, like many employers, may only be able to glean a few reliable insights due to a limited number of respondents. Even if the employee addresses the question, the score provides little hint on how to improve things. And what if it doesn't include topics that employees really want to discuss?

Recent advances in AI, particularly large-scale language models (LLMs), are allowing leaders, for the first time, to glean nuanced insights about a company's culture from the way employees talk about their company in their own words. Rather than answering a series of questions with her 5-point rating, employees can now easily explain what is and isn't working within the organization and make suggestions on how to improve it. . AI does this heavy lifting and provides more detailed comment classification and sentiment evaluation.

Freed from the shackles of traditional surveys, organizations can use AI to collect and process employee feedback from a variety of sources. The amount of feedback available is staggering. The combination of free text from internal surveys, performance feedback provided to managers, online employer reviews, and other sources equates to tens of thousands of pages of data each year for large companies. Until recently, organizations had to rely on crude tools like word clouds and search keywords to glean insights from this trove of information.

With more and more detailed measurements brought to you by AI, business owners can more quickly and easily assess whether their companies are living the values ​​they consider “core” and reduce workforce attrition. You can identify the most important cultural factors that drive everything from innovation to diagnose harmful issues. After finding important patterns, leaders can analyze subcultures within the organization and plot progress over time to get more nuanced context and employee recommendations on how to improve the culture. can.

Take Amazon, which aims to become the world's best employer. We used our AI platform to analyze tens of thousands of employee reviews for leading e-commerce companies. This shows that Amazon is successfully implementing many of its leadership principles such as “customer obsession” and “inventing and simplifying.” But the company's culture also contributes to employee burnout, particularly among software engineers, who are twice as likely to complain about burnout compared to warehouse workers or drivers. It is said to be expensive. Raw employee feedback helps Amazon reduce the stress on its engineers, including fixing a performance review process widely seen as brutal and minimizing disruptions in the middle of the night when technical employees are on call. It shows how this can be alleviated.

Even the largest companies will take time to implement AI. But cultural analysis is one of the few areas where AI can be employed right now because it leverages one of its greatest strengths today: understanding natural language at scale.

This does not mean that leaders should blindly trust the work of an LLM. This tool requires safeguards to prevent weaknesses such as fabricated answers due to hallucinations. Models should assess elements of culture based on solid evidence rather than the latest management fads. Leaders need to take a broad view of culture and measure not only the factors that influence employee satisfaction, but also the topics that shape the company's ability to adapt to market changes and avoid unethical or illegal behavior. there is.

Leaders who deploy AI for cultural insights can use it to improve employee well-being, reduce the likelihood of reputational damage, and ultimately increase profits. While not the only piece of the “successful culture” puzzle, measurement is critical. Culture has always been an enigma at the heart of organizational performance, no doubt important but puzzling. AI can be used to make meaningful advances in decoding. that.

Don Sul is a professor at the MIT Sloan School of Management and co-founder of CultureX, a research and AI company. Charlie Salle is the co-founder of CultureX.