As companies explore the integration of AI across various functions, an interesting development has surfaced: businesses are now turning to AI to help their bots better understand human emotions.

This emerging field, known as “emotion AI,” is highlighted in PitchBook’s recent Enterprise SaaS Emerging Tech Research report, which forecasts significant growth in this technology.

The concept is straightforward: when AI assistants are deployed to support executives and employees, or when AI chatbots are positioned as frontline salespeople and customer service representatives, it becomes essential for these systems to accurately interpret human emotions. For instance, an AI needs to distinguish between an angry “What do you mean by that?” and a confused “What do you mean by that?” to respond effectively.

Emotion AI is considered a more advanced iteration of sentiment analysis, which traditionally focused on gauging human emotions from text-based interactions, especially on social media. Unlike sentiment analysis, emotion AI is multimodal, utilizing visual, audio, and other sensory inputs, combined with machine learning and psychological insights, to detect human emotions during interactions.

Leading AI cloud providers, such as Microsoft Azure with its Emotion API and Amazon Web Services with Rekognition, offer developers access to emotion AI capabilities. However, these services have not been without controversy.

While emotion AI technology is not entirely new, the rapid increase in the use of bots within the workforce suggests it may play a more prominent role in the business world moving forward, according to PitchBook.

“With the widespread adoption of AI assistants and the automation of human-machine interactions, emotion AI holds the promise of enabling more human-like interpretations and responses,” notes Derek Hernandez, senior analyst for emerging technology at PitchBook.

A number of startups are now emerging to capitalize on this trend. Companies like Uniphore, which has raised $610 million (including $400 million in 2022 led by NEA), as well as MorphCast, Voicesense, Superceed, Siena AI, audEERING, and Opsis, are all working to advance emotion AI with backing from various venture capitalists, according to PitchBook.

However, emotion AI reflects a typical Silicon Valley approach—using technology to solve problems that arise from the interaction between technology and humans. And while it’s likely that many AI bots will eventually incorporate some form of automated empathy, there’s no guarantee this approach will be truly effective.

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