Ali Merchant, CEO of Orvera (formerly CallBotics), speaks with Einat Weiss, former CMO of NICE, about how AI is reshaping enterprise operations beyond experimentation into real operating models. The conversation highlights a fundamental shift in how enterprises approach AI. It is no longer a standalone technology initiative but a business transformation that impacts customer experience, decision making, and execution speed across the organization. Einat frames the current enterprise challenge as a tension between speed and risk, where organizations must move quickly with AI adoption while maintaining governance, compliance, and trust, creating friction at both leadership and operational levels.
The discussion also emphasizes that many organizations are misaligned in how they approach AI, often starting with technology questions or cost savings instead of focusing on outcomes, leading to fragmented pilots and limited impact. Ali brings in an operator’s perspective, highlighting real-world challenges such as inconsistent service quality, slow execution, and the difficulty of scaling operations, reinforcing the importance of starting with simple, repeatable workflows to prove value before scaling. A key theme throughout the session is the gap between demos and real enterprise deployment, where success depends on strong data foundations, clear ownership, and early focus on security and compliance. The conversation concludes with practical guidance for leaders to define clear outcomes, assign ownership, stay curious, and ensure AI adoption is tied to measurable business impact rather than experimentation.
What are some of the biggest operational and leadership challenges you see organizations dealing with today?
I think that's a very, very common mistake. Questions like:What is the first practical step you would advise them to take, given your extensive experience?And the third thing, and that's really, really important when you have to start adopting something, is:What mistakes do you see organizations commonly making when they begin exploring AI or advanced technologies?
Launching a new campaign, the first question was always, always think about the measurable outcome.Tell me about the potential at an enterprise level.This is a big challenge. So I think CX leaders are absolutely challenged with.That's a great question. Things move so fast. So my practical advice is.
So hello everyone, welcome to Enterprise AI by CallBotics, a conversation series where we speak with enterprise leaders about how they are thinking about AI and how AI adoption is shaping real-world enterprise operations.
I am Ali Merchant, and today I am joined by Einat Weiss.
Einat brings deep experience in enterprise technology and go-to-market leadership, including her time as Chief Marketing Officer at NICE, where she worked closely with large global enterprises on digital transformation and AI-driven platforms.
It is great to have you here. Thank you for joining us today.
Of course, it's a pleasure to be here, and I'm looking forward to having this conversation with you.
Likewise. So to start, for those who may not be familiar with your background, can you share a bit about your journey in enterprise technology and the kind of work you have focused on across your roles?
Yes, of course. Over the last few decades, I have been working at the intersection between technology and go-to-market.
I spent half of my career in product, making sure enterprise software companies bring the right product to market in the right way.And the second half in marketing, again making sure we take very complicated, advanced technology concepts and translate them into category-leading positioning.
Most recently, I was the Chief Marketing Officer at NICE, where I worked very closely with the leadership team on making the company a category leader, and specifically transforming it into an AI leader, which I think is very relevant for our conversation today.
Great. What a great journey. So let's dive right into it.
Having worked closely with large global enterprises, what are some of the biggest operational and leadership challenges you see organizations dealing with today?
So I will give you my perspective, and I am also happy to hear from you.
Essentially, what we see today is a tension between speed and risk.
Many enterprises are built to be very risk-averse. Now they are being asked to run two businesses in parallel. One that is risk-averse, and one that is extremely fast with the adoption of AI.
That creates a lot of friction.
Second, organizations often look at AI as a technology product, but really, it is a business transformation. It is a business decision. So you have to create the right organizational alignment behind it.
The third thing that I see has to do with talent. Leaders have to reassess the talent they have and how they hire, ensuring they bring in people who push them forward rather than hold them back.
No, absolutely. I think organizations are built to be risk-averse, but that is not an option anymore.
AI is not just a cost efficiency play. It directly impacts customer experience, and there is no way of delaying it.
I was just looking at a study where financial and healthcare organizations, which traditionally moved more slowly, are now leading AI adoption. That was surprising because they are highly regulated.
From a leadership perspective, what excites you most about AI at an enterprise level, and what concerns do you have?
The exciting part is divided into two.
First, in CX, AI reduces friction with customers. It improves frontline decision-making with much better context and minimizes invisible work such as summarization.
Second, across the enterprise, AI creates a self-service model. Employees can independently handle tasks like content creation, design, and reviews, even if they were not originally trained for it.
But there are concerns.
AI creates an illusion of progress. It is easy to build demos or proof of concepts that are 60 percent complete, but operationalizing at scale with security and compliance takes much more effort.
It is our responsibility to help enterprises understand the difference between a demo and something that truly works.
Absolutely. CX leaders are challenged with filtering out vendors who can actually deliver.
One way to evaluate this is to see who stands behind their product. Long-term contracts up front are becoming less acceptable. Enterprises need flexibility to test fit because sometimes the issue is not the product but the fit.
What mistakes do organizations commonly make when exploring AI?
One major mistake is treating AI as a technology question.
Questions like what can I do with AI or how much money can I save are the wrong starting points.
Instead, organizations should focus on outcomes and identify where AI can drive massive scale.
Second, many organizations get stuck in a pilot phase, running multiple pilots without scaling any of them.
Third, they underestimate data readiness. AI does not fix bad data. It amplifies it.
Absolutely. AI is only as good as the data behind it.
We have also observed that starting with complex use cases slows adoption. Beginning with simple, repeatable workflows makes it easier to prove value and gain internal buy-in.
Trust is another key factor.
Enterprises must address trust, compliance, and security early in the process rather than trying to fix it later.
Looking ahead, how do you see AI influencing enterprise operations over the next two to three years?
The biggest winners will be organizations that redesign their operating model around AI, not just add it as a feature.
AI will become part of frontline decision-making and not just a support tool.
It will also compress work across the enterprise, reduce time to market, and enable hybrid human and AI workforces at scale.
If a senior leader is unsure where to start, what is the first practical step?
Choose a business-critical workflow.
Then define the outcome, define the baseline, and assign an owner.
Without clear ownership, AI initiatives fail.
Also, leaders need to stay curious. AI evolves quickly, and leaders must actively stay informed.
How should leaders navigate stakeholders?
You need to demonstrate three things.
Scale potentialReturn on investmentSecurity
When communicating internally, address concerns openly. Many employees may feel threatened, so clarity around goals is essential.
So tell us, what is your approach to consuming knowledge? With so much noise, books, papers, and podcasts, how do you filter and learn what actually matters?
That’s a great question.
The real answer is all of the above.
A lot of insights come from conversations. Sometimes hearing someone talk about challenges in cybersecurity gives you ideas that apply to other industries.
I listen to podcasts, I consume a lot of information, and I also use AI tools to synthesize and summarize content.
But overall, it is about constantly staying curious and actively looking for what is new and relevant.
Last question from my side.
Being a girl’s father, I tend to ask this to every successful woman. It is tough, and we have to accept that. You have reached a leadership position at a top CX company.
What advice would you give to women leaders?
First of all, thank you.
I will share two things.
For parents, especially fathers of daughters, demand the same from them as you would from a son. Do not lower expectations.
Encourage them to pursue science fields such as math, physics, or biology. There is often less push in this direction for girls compared to boys.
For women, my advice is simple.
Speak up. Say what you want to say.
Think about what your male colleague would do. Would they hesitate as much before speaking in a meeting? Probably not.
You do not need to be perfect. You just need to be present and have your voice heard.
Also, do not expect special treatment. See yourself as equal.
That makes a lot of sense.
I always tell my wife and mother that I do not see a difference between a girl and a boy. I try to align my actions with that belief.
I think preparing her for the real world is the most important thing.
This is very reassuring. I can go home today and share this perspective.
Thank you so much for sharing all this so transparently. I am sure this will be valuable for leaders and for women navigating this fast-paced change.
Thank you again.
Thank you.
