2023 AI predictions: Rising costs will drive brand AI adoption

Experts are predicting that 2023 is going to be the year brands finally make the shift to AI implementation due to rising costs.

According to McKinsey, organisations using AI in at least one business region have increased more than twice in number since 2017. The most crucial spike in adoption was between 2017 (20%) and 2018 (47%). AI adoption reached a peak in 2019 (58%) but has since trickled down to 50% in 2022.

Read more: AI’s positive impact on fashion: Customers find better-fitting clothes, manufacturers find the next fashion trend

But experts are predicting better organisational adoption of AI in 2023. Olga Beregovaya, the VP of AI and Machine Translation at AI and translation management platform Smartling, believes that brands will call on the tool – with many foolishly relying on it as a one size fits all solution.

She predicts that the chatbot evolution is upon us.

“We’ll continue to see advancements with AI technology like Open AI to drive independent human interaction and AI training itself to better adapt to human responses,” she says. “In the customer service space specifically, businesses will forego the method of human interaction to allow AI technology to take the place of call centers and human operators”.

Recently, the AI research group OpenAI has launched the beta version of a chatbot based on the GPT-3.5 language model called ChatGPT. Its potential is such that it’s being touted as the replacement for Google itself.

We’ll continue to see advancements with AI technology like Open AI to drive independent human interaction and AI training itself to better adapt to human responses

She also predicts that text-only services will soon go to mixed media services.

“Implementation of AI will go beyond written content on a page. Advancements now allow AI to train itself on images and audio data to create contextual content. This will be a big priority for businesses when it comes to content creation as part of their localization strategy with the burden of busy work for translators being reduced,” she explains.

“Reliance on automated content generation will play a huge role as people look to do more with less. The shift in how organizations will conduct business will impact how project managers work, taking on a data analyst role to create boundaries for AI to operate independently in,” she adds.

Read more: The Tech Panda list of 7 AI startups of the month

In terms of use cases, organisations are mostly using AI to improve service operations (24%). Robotic process automation (39%) is in the forefront when it comes to organisations using AI. This is followed by computer vision (34%), natural-language text understanding (33%), virtual agents/chatbots (33%), and deep learning (30%).