Why Most AI Contact Center Projects Stall
Einat Weiss explains why AI demos are easy but operationalizing them at scale with the right security and compliance takes far more effort.
Up nextWhat do 17 years inside a contact center teach you?Overview
About this session
In this short, Einat Weiss, former CMO of NICE, speaks with Ali Merchant about why so many AI contact center projects stall. AI creates an illusion of focus: it is easy to build demos and proofs of concept that get about 60% of the way to where things need to be.
Operationalizing that work at scale, with the right security and compliance measures, takes far more effort. Einat argues that vendors have a responsibility to make sure senior enterprise buyers can tell the difference between an impressive demo and something that will actually work in production. The clip is designed for enterprise buyers and contact center leaders evaluating AI projects.
Key takeaways
What comes out of it
An illusion of focus. Demos make AI look simpler than it is.
60% is not done. Proofs of concept stop well short of production.
Scale takes real effort. Security and compliance must be built in.
Buyers need clarity. Vendors should show the gap between a demo and a working system.
TranscriptRead the full session
Einat Weiss 00:00:00.00 AI creates in some ways an illusion of focus. So it's very, very easy to build demos, to build proof of concept, to take it kind of 60% over things need to be, but really operationalizing it, at scale, with the right security and compliance measurement, that takes much more effort. And I think that at the end of the day, it's our role, right, to make sure that senior enterprise buyers There's no difference between a demo and something that wouldn't work.
Keep watching
More clips
Like what you
just watched?
The same agentic voice, agent assist and quality workflows, running on your own call flows in 3 to 6 weeks.