The machine learning boom is here, and it’s only going to get bigger. When the pandemic decimated workforces and limited in-person interaction, artificial intelligence tools helped companies increase productivity. Industries such as hospitalityhealthcare, and energy have all benefited from recent A.I. innovations, but there’s more disruption on the horizon. Instances of businesses using automated experiences are increasing, and automation is expected to grow in both the metaverse and in how companies pursue environmental, social, & governance (ESG) initiatives, according to Pranay Agrawal, co-founder and CEO of A.I. services and analytics provider Fractal.

Here are three predictions from Agrawal on some of the next big steps for A.I.

Customers will expect more from automation services.

When the pandemic hit and businesses scrambled to adapt to a digital world, automation became much more commonplace in everyday life. People became used to seamlessly talking with customer service chatbots and virtual assistants, and that familiarity has led to increased expectations from consumers.

“Over the last few years,” says Agrawal, “companies like Apple and Amazon have created incredibly nifty and user-friendly products, and I think customers and society at large now expect a more fully personalized service and experience.”

Examples of this more “personalized experience” include better-targeted ads, personalization of social media experiences, or customized experiences at banks, healthcare companies, and telecom companies, according to Agrawal.

As an example, take virtual assistants such as Amazon’s Alexa. A common complaint with Alexa is its “by the way” suggestions, where after answering a question, the bot will ask if the user would like to engage in an unrelated task, such as buying a suggested product or asking about the air quality. Agrawal says that in the near future, it will be easier for consumers to fully customize how their A.I. assistants interact with them, without potentially annoying disruptions.

Companies will use A.I. to improve their environmental initiatives.

Companies are under more pressure than ever to prove themselves as being environmentally friendly and sustainability-focused, as investors are increasingly using environmental and social criteria to determine where to put their money. Automation can help companies boost their ESG efforts, such as by using A.I. to optimize power consumption.

“We’re going to see a lot of progress happening in the ESG space as more companies implement A.I. to assist in managing their carbon footprint,” says Agrawal. Machine learning also allows companies to extract more relevant data when it comes to analyzing potential environmental and social investment. There is no standardization for ESG datasets, meaning different research companies use their own methodologies to determine ESG rankings. Because of this lack of consistency, data researchers sometimes need to use intuition when converting information into a quantifiable metric. With machine learning, the algorithm can determine what is and isn’t relevant data with far more accuracy than a human, and without the need for guesses. 

However, Agrawal says that the adoption of A.I. to assist with sustainability will coincide with a need to address ethical concerns related to A.I., such as whether consumers have a right to know when they’re interacting with an A.I. rather than a human.

Moving to the metaverse will increase the need for A.I.

The prospect of doing business in a virtual online world like the metaverse is understandably confusing, but the real world has already begun transitioning into a mix of physical and digital. For example, Pokémon Go, the viral hit of 2016, got millions of people out of their houses to capture digital monsters and store them in their phones.

Agrawal says that younger generations, including Millennials and Gen Z, are much more comfortable “living” online compared to older generations, and companies that want to capitalize on those younger demographics should be thinking about how to use virtual worlds for e-commerce and marketing.

Already, machine learning is at play in the development of both augmented reality and the metaverse, as building large virtual worlds often requires some level of automation combined with human design. Agrawal says that by analyzing your likes and interests, machine learning can direct you to a specific corner of the metaverse relevant to you personally.

Machine learning will also be used to power next-generation of non-playable characters in these virtual worlds, which will be able to respond much more intuitively than your typical video game NPC. These characters will be key to the metaverse’s success, as they may also be responsible for selling you both physical and digital items.