As part of Solutions Review’s Premium Content Series—a collection of contributed articles written by industry experts in enterprise software categories—Amit Ben, the founder and CEO of One AI, outlines a few of the ways AI can (and likely will) affect various industries in 2023 and beyond.

As the race for AI dominance heats up in 2023, many influencers are welcoming the Age of Artificial Intelligence, including Microsoft, which recently considered investing $10 Billion in OpenAI, the maker of ChatGPT. Technology is sure to disrupt many industries, and it’s clear that the future of business is being shaped by artificial intelligence. However, looking beyond the hype, how can companies assess the impact on their organizations? How can natural language processing (NLP), also known as language AI, revolutionize different industries in 2023? What are the potential effects, the disruption of traditional business models, and new possibilities for expansion? 

For starters, we’ll see a shift in how humans interact with machines as people will come to expect products and services with language AI capabilities. In the race to embrace AI-driven capabilities, those that fail to keep up and leave humans isolated from AI creation and moderation superpowers will be left behind.  

A New Division of Labor Between Humans and Machines 

As machines and algorithms become increasingly sophisticated, they can take on tasks previously the exclusive domain of humans. This is already happening in industries like manufacturing, where robots and automated systems are replacing workers on the factory floor. It is also coming strong to the language field, driving the labor cost of many, sometimes unexpected, tasks close to zero.

Businesses will better understand which tasks should be automated using NLP models and which tasks should be left to humans. This division of labor between humans and machines will allow businesses to streamline operations, use resources more efficiently, and improve data integrity. NLP models will be designated to handle increasing language tasks, freeing human workers to focus on more complex and creative tasks.  

Focus on Business Impact 

NLP can quickly and accurately digest massive amounts of language data. Organizations can gain insights, make informed decisions, and act on both the managerial and operational levels. This will lead to a better understanding of customer needs and preferences, improving the overall customer experience.  

Recent technological advances are making it possible to create advanced NLP that is accurate and affordable, opening up new possibilities for businesses and organizations to unlock value from their language data.  

Here are a few examples of how NLP may transform specific industries: 

Customer Relationship Management (CRM)

CRM providers that adopt NLP-based capabilities, such as identifying customer intent in conversations throughout the engagement and analyzing calls for customer satisfaction, will have a significant edge in the market. Not having these capabilities can lead to challenges in retaining customers and gaining market share. Check out NLX’s innovation in this field. 

E-Commerce

E-Commerce customers will expect NLP-based capabilities such as product categorization, sentiment analysis, and personalized recommendations from their shopping experience. Companies that fail to adapt to this trend may lose customers to competitors who can provide a more seamless and customized experience. Check out this analysis of Amazon Echo reviews for some inspiration. 

Video Conferencing

Video conferencing tools that adopt NLP-based automatic meeting summarization and action item tracking will be in high demand. Without these capabilities, video conferencing providers may face challenges in attracting and retaining customers and staying relevant in a highly competitive market. Peech is a good example of innovation in the Video editing industry. 

Healthcare

Healthcare patients and wellness customers expect NLP-based capabilities such as medical record analysis, diagnostic assistance, and improved communication with their providers. Providers that fail to adapt to this trend may lose patients to competitors who can offer more accurate and efficient services. Kai AI is one example of utilizing comprehension and generation tools wisely.  

HR

In the HR space, Job seekers will expect NLP-based capabilities such as job posting analysis, resume screening, and interview evaluation from their job search experience. Companies that fail to adapt to this trend may struggle to attract and retain top talent. You can check out the work done by Teal for inspiration. 

Content Aggregators

Content aggregators will be expected to have NLP-based capabilities such as automated summaries, topic categorization, and personalized content recommendations from their content discovery and distribution platforms. Companies that fail to adapt to this trend may lose market share to competitors who can offer a more efficient and personalized content experience. One example is Daily.dev, an aggregator that provides automatic tl;drs of their content. 

Integrating NLP capabilities can revolutionize how businesses utilize language data and AI in 2023. How will your business evolve with this new capability?

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