“Then there’s thinking about new metrics beyond the traditional ways. That’s what’s really exciting about the possibilities of these tools,” she said.

Build generative AI tools with guardrails to foster trust

To deliver on the promises of generative AI, organizations must ensure the accuracy of the model to build trust, according to McKinsey.

In Brightcove’s case, it took a cautious approach, setting well-defined guardrails around the use of customer information that require permissions, rigorously testing the system, and having in-house technical experts scrutinizing the output.

“It's not one person looking at it; it's 50 people looking at it,” Levine said.

The Amazon team worked closely with Brightcove staff, teaching them how to craft questions to get the most suitable answers and taking time to train the bot on its extensive library of documentation as the source for responses.

“Streaming is complex, and that creates a lot of information about how to do it the best way across thousands of customers,” Levine said.

The bot-generated answers also include citations that link to the Brightcove source information so if the answer doesn’t look right, human experts can verify the response and feed that back to the tool. It adds an important layer of trust and teaches the model to help improve its output as it processes more queries.

“We have a lot of very technical people here at Brightcove, and when we see answers that aren’t right, we call it on it,” he said.

The end result is that the bot provides customer and product support teams with responses to customer questions. Brightcove has found it’s not only reduced the response time but also improved the overall efficiency of the support team.

“It’s about giving our customers the information they need quickly and accurately, and continuously improving that process,” he said.

Avoiding the trap of one-off tools

To maximize the potential of generative AI, McKinsey recommends that organizations avoid one-off solutions and invest the time and resources into tools that will scale.

Copeland cautioned that organizations must think through the longevity of the platform they’ll be working with.

“Use as your base platform a known entity, such as a large outfit that already offers customer experience tools you’re using across the business,” Copeland said.

While organizations might want to experiment, they also need to avoid different internal groups building their own tools independently to ensure widest application of new tools.

“If you get one-off customizations, it’s difficult to pull together, and when things are done in bits and pieces without any kind of central coordination, it becomes a nightmare to centralize and scale,” Copeland said.

In the case of Brightcove, Levine sees ways to expand the company’s use of generative AI to address more complex tasks such as enhancing metadata management on video streams or automating translation services to convert a video into multiple languages.

“Our customers have footprints all around the world, and if we can enable them to translate content on the fly, that's another use case for generative AI,” Levine said.

Above all, Brightcove’s use of Amazon Q is meant to not only improving operational efficiency but also add value to its service for customers.

“Everything we do starts with that mindset and driving business value,” he said.