Dealing with AI's Tradeoffs

August 1, 2024

Written by Eric Krapf, General Manager and Program Co-Chair, Enterprise Connect Publisher

One of the few areas of consensus in these early days of enterprise Generative AI has been that the contact center application most likely to provide a quick win is call summarization for agents. It seems to check all the boxes: It’s a clear time-saver, shaving seconds or more off post-call work by writing the agent’s report for them; it keeps a human in the loop, since the AI-generated summary gets reviewed by the agent before it’s saved; and it’s internally-facing, so that even if errors or embarrassing phrases do crop up from the AI, the brand is spared customer and public blowback.

But even call summarization has its complexities and concerns, as Forrester senior analyst Christina McAllister points out in this conversation with No Jitter senior editor Matt Vartabedian. McAllister’s review of these challenges shows just how much human effort and judgment needs to go into the process of making Gen AI truly enterprise-grade.

The fundamental tradeoff in this and many other Gen AI applications is, as McAllister explains, “latency versus accuracy.” Basically, the quicker the AI produces its call summary, the less time it’s had to apply context from the model, which can make the summary less accurate. But if you allow the system to take more time to achieve greater accuracy, “every precious second eats into the projected time/cost savings of the Gen AI summary solution,” she explains.

You should definitely read the whole article; it’s a great explanation of some of fundamental tradeoffs that enterprises confront when they deploy Gen AI functions in the real world.

That real-world perspective is also what we’re bringing with our first-ever Enterprise Connect AI conference, Oct. 1 – 2 at the Santa Clara, CA, Convention Center. We’re well past the initial hype stage of Gen AI, and enterprises now must look at the kind of details and tradeoffs that McAllister discussed with No Jitter, and from this examination determine a realistic business case and ROI. Our program is built around sessions that offer this level of detail and analysis, while our keynotes off a vision from companies that are enabling or building strategic implementations of Gen AI at scale that show the possibilities of this revolutionary but complex technology.

On that note, I’m delighted that we’ve announced two additional keynotes: Our conference will open on October 1 with a fireside chat featuring Darrius Jones, SVP, chief digital & design officer at USAA; and our October 2 opening keynote will be a conversation among three leaders at Deloitte: Rohit Tandon, managing director, Lauren Littlefield, managing director, and Vinita Kumar, business development.

I hope you can join us in Santa Clara this October for two compelling days of learning and networking about AI in the enterprise.