Hard to believe that it’s been nearly two years since ChatGPT exploded into the public view. Since then, we’ve seen enthusiastic adoption, followed by pushback, artificial intelligence hallucinations, and doubling down. It's like swimming in a wave pool: When you don’t know which direction the waves are coming from, you can’t be blamed for simply treading water.

The good news is that the waves are calming. We now have a good understanding of how AI is being used across workforces, how it can support and supplement workflows, and how it can ultimately improve efficiency and provide a competitive advantage. If you’ve been sitting on the sidelines, or simply wading in the AI pool, now’s the time to ride the GenAI wave.

Joint research with WBR Insights shows that 81% percent of surveyed B2B manufacturers and distributors are currently using generative AI. That’s higher than the market share of Windows on desktops and laptops worldwide.

Such a high rate of adoption means that companies are realizing a competitive advantage from GenAI. So how are B2B companies using it?

The biggest opportunities broadly break down into two categories: those that benefit the business and those that benefit the customer. They work together to improve sales and reduce tedious labor.

Benefits to Businesses

When B2B leaders were polled about their GenAI use cases, three stood out: automating repetitive tasks, analyzing data, and enhancing decision-making. More than 90% of respondents viewed these use cases as “somewhat important” or “very important” for investment.

GenAI famously came to prominence by creating human-like texts almost from thin air. But that represented only a sliver of what it could do. A second branch of GenAI, generative adversarial networks (GAN), works to generate data by pitting two AI models against each other.

These GAN networks promise to evolve predictive analytics and business intelligence — two key areas of supply chain management.

For example, predictive maintenance, a critical component of maintaining supply chains, relies on mountains of data, along with arrays of sensors, automated responses, and teams of data scientists. GAN networks can reduce the information required by synthesizing smaller amounts of new data.

GANs can be used to similar effect for demand forecasting and production planning, by reducing the amount of data needed to create competent models.

Going further, companies can feed the results from GANs into further GenAI programs, which will analyze the data and generate proposals for action. Deeper analysis with AI suggestions will allow companies to, in turn, make better informed decisions without having to rely on armies of data analysts.

Benefits to the Customer

It’s frustrating to consult a chatbot that gets stuck in a loop, responding with “I didn’t quite understand that.” These applications rely on keywords from the customer — they’re not smart. GenAI fixes this problem. Just as ChatGPT generates a response to a prompt, a smart chatbot will generate (not fetch) a response to the direct query. Customers get the information they need faster, hopefully without having to type “speak to a human.” GenAI can augment the customer search process, providing search assistants and smart recommendations based on buyer behaviors. For example, if a buyer adds 100 commercial-grade printers to a cart, then searches for “toner,” smart search will present toner that’s compatible with the selected printers.

Smart search returns relevant responses, which cut down on search time, lead to faster sales, fewer returns, and a happier customer experience.

Though it may have seemed like the AI waves were crashing in from every direction, today, the surf is far less chaotic. With two years of adoption under our belts, we can see how the waves of AI have benefited B2B businesses, and we can envision where these waves will carry us.

Sebastiaan Verhaar is chief executive officer of Sana Commerce.