Enterprise AI is a speed vs risk battle
Einat Weiss explains why enterprise AI is a business transformation, not just technology, and why trust and compliance must be designed in from the start.
Up nextWhy Most AI Contact Center Projects StallOverview
About this session
In this clip from Enterprise AI with Ali Merchant, Einat Weiss, former CMO of NICE, explains why AI adoption is so much harder inside large organizations. AI is often treated as a technology project when it is really a business transformation, and enterprises built to be risk averse are now being asked to run two businesses in parallel: one cautious and one moving extremely fast.
That tension creates friction, and so does trust. Enterprises spend years building their reputation with customers, so compliance and trust have to be addressed early, when the process is first architected, rather than patched in after issues appear. The clip is designed for enterprise CX and technology leaders.
Key takeaways
What comes out of it
A business transformation. AI is more than a technology project.
Two speeds at once. Risk-averse enterprises must also move fast on AI.
Friction is natural. Running both modes in parallel creates tension.
Design in trust early. Address compliance when the process is architected, not after issues.
TranscriptRead the full session
Einat Weiss 00:00:01.60 Sometimes organizations look at AI as a technology part, but really it's more of a business transformation. Many organizations, enterprises are built to be very risk averse, right? And now they're actually asked to run two businesses in parallel. One that is risk averse and one that is extremely, extremely fast with adoption of AI. So I think that creates a lot of friction. The second is I think many enterprises build their reputation for years, right? Creating trust with their customers. I think addressing the trust issue when it comes to AI, that it may be compliant to be addressed very, very early on when the process is being architected versus best-selling at the end after issues have already occurred.
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.