How Can Emotion AI Be Used in Business?

The question of how artificial intelligence (AI) is being used to change the world as we know it, from social applications to use in business, isn’t a new topic of discussion. It’s been greatly debated ever since it became clear that AI would be not only a plotline in futuristic films, but very much part of our reality.

Of course, AI has always been shrouded in fear, most of which pertains to wild ideas about flying cars and robots taking over the world. But, what about the more mundane, less “Hollywood” potential for AI?

That is, what about the applications of AI in business?

There are plenty of applications of artificial intelligence in business, from automated data entry and processing to client management systems, all of which have already proven to be incredibly helpful with regard to improving business processes and operating systems.

However, there’s another subset of AI that’s taking the world by storm, and now, it’s making its way into the world of business.

We’re talking about emotion AI.

What Is Emotion AI? 

Emotion AI refers to the subset of AI that deals specifically with interacting with human emotions by means of advanced computing and artificial intelligence technologies.

Essentially, it aims to be able to read human emotions in order to react appropriately, allowing computers to move beyond mere assessments of facts to start interpreting the subjectivities of emotions.

Emotion AI is able to read emotions, and subsequently react to them, through things like text computer vision, voice, and biometric sensing. At least, that’s the idea. Ambitions pertaining to this technology extend into potentially detecting emotion within specific contexts, creating a world of possibilities.

However, emotion AI is working towards achieving an incredibly complex objective, not only in terms of developing the technology but in even understanding human emotion well enough to be able to teach a computer how to detect it.

Emotions are subjective, both in terms of why they arise as well as how they’re interpreted, so teaching artificial intelligence how to deal with it is significantly more challenging than just writing out straightforward code.

Thus, many experts assert that the future of emotion AI is very much up in the air, with a lot of work still to be done not only in attempting to understand emotion and how to translate that understanding for machine learning, but also in terms of cultural, social, ethical and legal considerations.

Can Emotion AI Be Used in Business?

Experts may agree that emotion AI isn’t quite developed enough to completely change the landscape of businesses just yet, however, that doesn’t mean that it’s having no effect at all. Or, at the very least, that it’s not worth seriously considering how emotion AI has the potential to influence business.

The idea is that emotion AI has the potential to drastically improve a variety of existing offerings, including things customer service AI chatbots or sales reps.

If these AI-powered bots are able to identify and react to emotions effectively, they’ll be far more effective. For instance, they’ll be able to detect frustration and anger in a message from a customer and react in a way that won’t further exacerbate a deteriorating situation. This has the potential to be very helpful in improving customer service and satisfaction by means of automation.

That’s just one specific example of how emotion AI can help improve business operations and even current AI technology, but how is emotion AI tech able to do what it’s intended to do?

Some of the techniques used to detect and react to human emotion by means of AI include:

• Coding of Facial Expressions
• Voice Analytics
• Analysis By Means of Wearables
• Large Language Models
• Sentiment Analysis of Language
• Tracking of Eye Movement
• Analysis of Gestures and Internal Physiology

By means of these techniques and more, the intention is that emotion AI will be able to function in a multimodal capacity, attempting to detect human emotion in interactions in a far more advanced way than ever before. In fact, some experts have compared it to a more complex version of sentiment analysis due to its multimodal capacity.

The future is still pretty wide open in terms of how emotion AI may be used in the world of business, but there are some pretty significant areas in which developers are already aiming to implement it, including:

• Marketing and Advertising: Advanced emotion AI can be used to implement emotion-based marketing techniques by means of analysing consumers’ emotional responses to advertisements and marketing campaigns. It could also contribute to the personalisation of advertising that targets individuals by enhancing the understanding of specific customers.

• Customer Service: Emotional analysis in call centres will help bots provide automated responses to interact with customers in a way that considers their emotional state and replies appropriately. This will provide a far more personalised and empathetic customer experience, ultimately improving customer satisfaction.

• Employee Wellbeing: Although the idea of monitoring employees’ interactions is controversial, it does have the potential to be able to keep track of how employees are doing and feeling by means of tracking interactions via tone of voice in email and more. It could provide a service like giving HR early warnings of unhappy staff, but it’s not surprising that many people are concerned about this potential feature.

• Product Development: Emotion AI can be used in product testing to analyse users’ experiences with specific products and to detect an honest response. It may do so by means of facial expressions or physiological responses, for instance, providing developers with an indication of what people enjoy and what they don’t, and in some cases, why.

• Content Creation: Part of making content that is successful is ensuring that it’s engaging and resonates with users. Emotion AI tech can help content creators figure out what kind of content resonates with their audience by analysing users’ emotional responses, ensuring that future content takes this into account, and posting things that are most likely to evoke positive responses as per previous patterns.

• Sales Optimisation: Similar to the way emotion AI can be used in marketing, it can also be incredibly effective in converting interest into real sales. This tech can help analyse potential customers’ responses to things like adverts or sales pitches so that sales strategies can be tweaked for future purposes in order to be as successful as possible. There’s also a great deal of potential for emotion AI tech to be used in CRM (customer relationship management) software.

• Recruitment: Emotion AI can help conduct emotionally intelligent interviews that take specific candidates’ needs and personalities into consideration.

• Fraud Detection: With emotion AI technology integrated into software, it can be used to detect fraud within systems by picking up on abnormal behaviour from users, flagging it as potentially concerning.

There’s no doubt that emotion AI can (and soon, will) be used to improve business operations, moving beyond merely enhancing operational productivity and onto improving employee and customer satisfaction.

Of course, there’s still plenty of controversy surrounding privacy issues and the efficiency of the technology, but as emotion AI continues to develop and progress, there’s no telling what the future may bring.