Generative AI is poised to revolutionize every customer connection, and small businesses aren’t going to be left behind, according to Ben Schreiner, head of business innovation for small and medium businesses at AWS.
While the language models that power many AI interactions have been around for some time, they previously required a dedicated team to manage. Now, modern services can crunch the data behind the scenes and deliver the results, such as personalized scripts for customer inquiries, directly to those who need it.
However, implementing generative AI for the sake of having it is a losing proposition for small companies with tight budgets, according to Schreiner. Schreiner encourages companies to determine the problems they’re aiming to solve and invest in solutions accordingly.
The power of AI has historically been the domain of major banks, large retailers and other businesses with money to spare. But modern generative AI tools, backed by cloud computing, are democratizing the benefits for companies of all sizes, according to Schreiner.
AI capabilities are great at powering enhanced customer support experiences to drive higher satisfaction and retention, Schreiner said. The key is making sure business leaders use AI in a way that best fits their specific needs.
“We should not have a hammer in our hands walking around looking for nails,” Schreiner said in an interview with CX Dive. “That's the wrong approach to this. We should actually look at the problems that you have and then figure out what tool best solves that problem.”
Determining and communicating the business value of AI is often the hardest part of getting the implementation right, according to Schreiner. Aligning results with budgets is a problem CX leaders are facing in general, and for small businesses with tight budgets, the cost of implementing AI can add another wrinkle to the problem.
Schreiner suggests that companies work backwards from an identified problem and seek out an AI solution that “moves the needle for that customer experience.”
For instance, if long calls are leading to a drop in customer satisfaction, companies should look for patterns that reveal the cause of lengthy conversations.
From there, they can see which generative AI tools, if any, can help.
The right AI service can retrieve relevant solutions for customer inquiries faster than an agent manually searching a database, according to Schreiner. AI can also create conversational scripts on the fly, updating solution suggestions rather than forcing an agent to stick to a static script with useless suggestions.
AI tools can also improve the customer experience by improving the employee experience, according to Schreiner. The right AI might be able to determine if an employee needs a break to avoid negative customer interactions, which could also impact call center performance.
“I think there's two sides of that customer interaction that — now that you're going to have this tool — companies are going to be able to look at,” Schreiner said. “It’s not just how the customer is reacting but also how the agents are performing.”
