In the never-ending quest to deliver a great customer experience (CX), organizations are, of course, turning to artificial intelligence (AI) — specifically agentic AI — for help. In a recent survey of 500 executives with AI experience, 61% said they planned to increase spending on both general CX initiatives and AI-specific programs this year, with 77% considering or actively trialing agentic AI to improve and automate CX functions.
The survey, conducted by NewtonX for Teradata, found that expectations are high, with more than half of the respondents anticipating a return of at least $1 million in revenue or cost savings from AI for CX initiatives, including 36% who expect over $2.5 million.
However, those benefits will come only if organizations can succeed in fighting some AI headwinds. Most notably, challenges include creating governance frameworks, which 93% of the survey respondents cited as an issue. Such issues are giving some companies pause, with 35% saying they prefer to wait until AI solutions are proven, up from 22% in the same survey last year.
Three requirements for an agentic AI platform
It’s clear that companies need a helping hand if they are to see their agentic AI plans come to fruition. What they need is an AI solution that addresses at least three areas, as follows.
1. An open and connected platform to promote effective data use
Data drives all AI efforts, and CX applications are no different. The problem is that relevant CX data often lives in many areas, including customer relationship management (CRM) tools, business process management systems, contact center applications, and more. Step 1 is to ensure access to all the relevant data where it lives and then use a database or a vector store within the platform to make the data usable to agentic AI applications.
That platform should also provide the data governance capabilities that survey respondents clearly need. It needs to enforce rules and policies regarding issues such as data quality and integrity, security and privacy, regulatory compliance, transparency, and explainability.
2. Working within an agentic ecosystem
Agentic AI solutions must be able to coexist with and leverage the existing IT ecosystem in which most companies operate. That means not only the various sources of data noted above but also the hybrid cloud environments that are the norm for most organizations. It may also mean support for multiple AI engines and models, as well as specialized graphics processing units (GPUs) intended to support AI applications. Many companies will also need third-party experts to guide their agentic AI efforts.
3. Autonomous agents supporting key processes
As its name implies, agentic AI ultimately comes down to AI agents performing useful functions. As such, an effective platform should make it easy to infuse agents throughout the end-to-end process from data to signals to actions. Ideally, this would be a mix of out-of-the-box agents that perform routine functions, such as reading and parsing PDF documents, and easily customizable agents for more company-specific use cases.
Agentic AI in practice: Customer lifetime value
An example of how these elements come together is how Teradata’s Autonomous Customer Intelligence solution enables AI-driven insights into customer lifetime value (CLTV). Teradata has long offered a data analytics platform, so it has a wealth of historical data and intellectual property to draw from. Adding agentic AI capabilities on top enables it to deliver actionable insights at scale, so companies can:
- Ask natural-language questions and get answers instantly, backed by real data
- Uncover the root causes of CLTV shifts, such as a lack of engagement that leads to churn
- Receive recommendations for strategic interventions to keep customers happy
- Scale insights across millions of customers and billions of queries
- Simulate the impact of initiatives such as product cross-sell, deposit growth, and digital migration on CLTV
That’s just one example that shows that plans for increased spending on agentic AI, along with expectations of success, are well founded — and that solutions to perceived challenges are at hand.
To learn how Teradata’s autonomous AI and knowledge platform and AI services can help you boost your CX efforts with agents, visit Teradata.com and its customer experience page.
