As part of the annual discussion on what the new year has in store for the CRM industry, The CRM Playaz assembled two groups of executives from some of the leading vendors in the industry to get their take on how they see 2025 shaking out. And during a portion of the Day 2 discussion the conversation centered on why data is critical to seeing and feeling signficant impact from AI in a varitey of ways.
in this short clip:
* Vijay Sundaram, Zoho's Chief Strategy Officer, highlights the transformative potential of AI at a system level, particularly in applications like #CRM.
* David Singer, Global VP of Go-to-Market for Verint, says that while data powers tools and tools enable tasks and tasks deliver outcomes, success happens when the focus is initially on identifying what the desired outcomes are.
* Jason Miller, Chief Evangelist at Creatio, stresses the importance of integrating the three prevailing AI patterns - predictive, generative and agentic - seamlessly with each other to maximize their potential.
*. Tara DeZao, Adtech and Martech Product Marketing Director for Pegasystems, explains that real-time data enables adaptive AI to deliver differentiated outcomes compared to predictive models that rely on historical data.
* Clint Oram Cofounder and Chief Strategy Officer for SugarCRM, highlights that hashtag#GenAI performs well even without perfectly structured data, unlike ML models which require clean input data to be effective.
Full show video can be seen at https://youtube.com/live/lu0hPE5OmwM?feature=share
Below is an edited transcript of thisconversation.
Vijay Sundaram: I think a piece that we may not talk about enough but is happening is what is AI doing at a system level. What is the future of putting in a system like a CRM. It's not inconceivable to think of a small language model that's figured out completely a particular AI system. All its use cases. All its modules. All the kinds of implementations that have ever been done on it. So when you come into that system and say I want to do this and this is my industry, it lays it out for you. So, AI can do a number of things.
David Singer: Data powers tools. Tools enable tasks. Tasks deliver outcomes. But a lot of times people focus on the tool and improving the task and forget about the data and the outcome on the other side. There's got to be the centralization and curation of the right data to make them work.
The most important part in my mind is focusing on the outcome first. The outcome is the fastest resolution of a claim for the customer. Maybe you don't need a human that loop at all. So if your outcome is that forget the tools and tasks you're doing today. You can apply a different model based on different data to do that automatically 80 percent of the time.
When people start thinking about the outcome first think about the data you need and then the tools and tasks fill in naturally. But if you focus on the tool and the task first all you get are incremental benefits.
Clint Oram: You nailed that David. Nobody wants to buy software just to buy software. They want to buy outcomes, and software just happens to be the path.
Jason Williams: The 3 major patterns of AI that are becoming prevalent in business today are predictive, generative and agentic. If you cannot put these working together moving seamlessly back and forth between predictive generative and agentic patterns you are missing out, because you're going to be able to do things like taking outcomes from a predictive AI pattern and use that as an input for a generative - or for an agentic pattern or vice versa. You're going to be using agentic and generative hand-in-hand to solve problems.
These things aren't all in one place looking at the same data set It's going to fail It just is because no way can it have good meaningful conversations and drive meaningful outcomes.
Tara Dezao: The kind of data we're talking about is it real-time. How fresh is this data? Because if it's not real-time and you're using predictive, that's a different outcome. But if you're acting on real-time data with adaptive AI, that's a total differentiator.
Clint Oram: We put generative AI into place with our customers starting this past summer, blowing people away. It just works, as simple as that. Whereas with predictive AI and MLs it' garbage in garbage out. If your data wasn't perfectly structured you're not going to get much value out of ML. But with generative AI man. it just works.