As the tech industry experiences a difficult economic period — one that’s been particularly harsh to startups — there’s one area of artificial intelligence (A.I.) that’s seeing substantial activity, even without the financial injections of venture capital or government intervention. Natural language processing (NLP) is enjoying a huge spike in investment, reach, and usage among both established companies and small startups, and shows no signs of slowing.

At its core, NLP seeks to understand human language, which gives us the opportunity to better interact with machines via our own language. It has applications across industries and businesses, from customer service algorithms that allow us to communicate naturally with them, to fin-tech security capabilities for authenticating user identities.

And unlike many other A.I.-related investments, NLP is already paying off for businesses. In its application with customer service, businesses are starting to see lower costs and happier customers — the two staples of any successful business model. This, paired with reduced development costs, has led to an influx of NLP-based solutions entering the market and a corresponding shift in the way the industry views this aspect of A.I.

The tech community generally looks at the current state of the industry with some trepidation — but NLP’s success has seen it emerge as a bright spot among the doom and gloom. Companies of all sizes, from Apple to Microsoft, are investing in natural language-based solutions to help deliver exceptional customer experiences.

Equally important is the fact that, unlike many other A.I. solutions, NLP does not require massive amounts of data and infrastructure. This makes it easier for younger companies to build on the solid foundation of open source tools that have already been developed — and start to achieve results almost immediately.

As more companies look to cut costs, NLP may prove to be a great investment that offers cost savings and improved customer service in the long run. If the industry is willing to look beyond the tech gloom and focus on NLP’s current successes, we may be on the cusp of yet another A.I. revolution.