Improving Hybrid Work Communications With Contextual, Sentiment, and Multilingual AI

Good communication is critical to effective collaboration, but with hybrid work setups, employees can face communication overload. Constant notifications, back-to-back meetings, and dozens of digital tools can be a huge productivity killer and demotivator.

According to a Howspace global survey of several hundred global companies across 31 countries, over 25% feel overwhelmed with more meetings and messages. Respondents ranged from executives, consultants, and employees at large organizations to micro-companies across several industries.

How can we create more engagement and a sense of belonging throughout the whole company without overwhelming people? How can we efficiently break down borders between colleagues and co-collaborate with the best talent in the world, regardless of common language? AI is emerging to help remote workers communicate effectively with customers and their office-based colleagues.

Facilitating communication with artificial intelligence

Hybrid working solutions need to facilitate messaging, collaboration, employee unification, regardless of the employees’ location and engagement. Companies are increasingly investing in a growing range of technologies and services to facilitate hybrid work, and new technologies are an integral part of a more holistic approach to work. Communication between different departments within the same organization has long been challenging because of information silos.

One answer is multilingual AI. AI can be programmed and coded to speak its own language and can understand and convert different human languages into its own machine language. This means that the AI doesn’t translate from Swedish to English, it translates it into machine language.

For example, a comment about "strong leadership" goes into a same basket with "vahva johtaminen", "starke Führung", "starkt ledarskap", "сильное руководство", "liderazgo fuerte" and "強有 的領導". This means we can train a machine in an English dataset and do predictions in French. This makes it possible to use different languages in one chat and benefit from AI functionality.

Understanding the meaning beyond words

Traditionally, machines are terrible at empathy. Empathy is a human quality that we cannot replace, but trained AI is still able to grasp and understand the meanings beyond the words themselves. Known as semantic AI, a semantic machine can, for example, categorize "audio issues", "background noise" and "too low volume" into the same basket. This becomes useful when categorizing content and finding different ideas.

With sentiment analysis, workers are able to get an idea about the tone of voice of the dialogue. This could potentially see that workplace disputes and quarries are reduced as the AI is able to better interpret the emotions and sentiments behind a piece of text when the recipient is unable to speak the same common language as the sender. Like its multilingual counterpart, sentiment-based AI is language agnostic, making it perfect for cross-border organizations. Additionally, contextual data, once popular before cookies emerged as an advertiser’s most efficient way to target internet users, not surprisingly, takes context into account when analyzing communications.

Get a quick glimpse of the discussion

Artificial intelligence can help leaders and colleagues understand and obtain a lot of information in a more digestible way. When an organization uses several communication channels to disseminate valuable information, they only increase the chances that their employees will be operating without a full understanding of the big picture or feel unheard and excluded. 20% of Howspace’s global survey respondents do not feel that leadership is taking action based on their feedback for how, where, and when they’d like to work.

Imagine you ask people about how they feel today. Instead of reading 300 people's comments, you could simply view these feelings in a word cloud that updates real-time. Using AI to generate word clouds can help reduce overall noise and bring up important keywords from the conversation within seconds, automatically generating suggestions and conclusions with the option to transparently share the results with others.

The value of this is simple: you can get a simple 7-word answer to your question, everybody's voice is heard, as well as you’ve managed to facilitate and understand more insights about your colleagues and workforce. Perhaps this leads to new ways of working or the chance to improve overall feelings of satisfaction and balance at work.

Clarity in decision making

Properly leveraged, artificial intelligence has the power to create more diversity in conversations, ensuring that every voice is heard and thereby further democratizing the feedback process, while still not overwhelming leaders and colleagues with big data sets that require hours of difficult data crunching to extract the information.

Howspace’s AI is no "generic AI". Howspace’s AI is the emergence of multiple specific machine learning models working together. It's not built for recognizing human faces in images, but it's pretty good at dealing with organizational dialogue. It was built for that purpose by a team with over 20 years of organizational culture and leadership development experience.

A blend of contextual, sentiment, and multilingual AI is able to better facilitate communications internally and externally, allowing employees and leaders to facilitate new ways of working and thinking within their organizations. Not only can AI enable all of this, but it can do it at a fraction of the cost and time it would ordinarily take. The hybrid model is here to stay, and artificial intelligence will revolutionize the way in which we communicate with each other.