Despite significant gains, emotion AI has yet to “go mainstream”. At least, not in the same ways we’ve seen from other sales innovations – like social CRM and cloud-based CX. That will change in 2023, as more businesses realise value in the technology and see what they’re missing out on.
Just what will that change look like? Here are four ways that emotion AI will transform sales in the coming months.
Overcoming the fear of AI tracking technology
One of the biggest barriers to widespread emotion AI adoption is a pervasive fear that the technology will “track” behaviours users consider personal. However, sales applications that use emotion AI are designed to detect buyer sentiment and engagement – not recognise personal feelings or collect sensitive data.
Sales organisations will, in time better understand the type of data that emotion AI looks at. They will also assess the level of insight it can bring to cataloguing meetings and analysing what does or does not work. In time, organisations’ fear will turn to fascination and, consequently, adoption.
Capitalising on and circulating emotion AI
Sales organisations are inherently innovative, and turning capability into cash is what the marketplace does best. Emotion AI is no different.
As more businesses adopt the technology, experimentation will naturally follow. As forward-thinking enterprises uncover new opportunities and value in using emotion AI, other businesses will quickly follow suit.
Fears and accelerating mainstream privacy and data security legislation
In response to “tracking” and other data privacy fears, many companies behind emotion AI technology have implemented stringent systems to protect user data. While private, enterprise-level efforts will certainly allay some fears, government legislation will significantly strengthen confidence. Relaying this wide range mindset in the technology can help to accelerate its adoption.
Because legislation varies by region, solutions can adapt to new and emerging government mandates. These will be considerably more desirable than their less-flexible counterparts as businesses plan for the future.
The long-term players in the emotion AI market will be the global thinkers
Many companies are churning out AI products based on freely available tools from Google, Facebook, Open AI and others. However, most focus exclusively on supporting English language AI tools. As a result, many so-called “foundation models” are already outdated.
To avoid investing in (near-)obsolete tech, companies are beginning to lean into “future-proof” solutions. Especially those with a focus on handling many languages. While many current AI modelling efforts focus on interpreting language or visual information in isolation, this is often not how information is truly represented.
Next year we will see growing interest in multimodal platforms that integrate many types of data inputs. These include gestures and visual cues, tonality, contextual and historical information, and other data points taken from the context of global trends and events. As its value becomes more apparent—particularly in virtual engagements—expect greater adoption rates across nearly every industry.