Agentic AI and Saas - The next chapter in CX

Customer service has always been fundamental to success in the software as a service (SaaS) industry, and we're on the cusp of a new era. The promise of agentic AI is setting the stage for more autonomous and seamless customer interactions. Is your business ready for the next evolution of artificial intelligence (AI)?

Agentic AI refers to AI systems that can take purposeful, autonomous actions based on contextual understanding. Gartner calls agentic AI a "game-changer" for customer engagement, representing a major shift in how service operations are managed. AI agents will be able to handle complex tasks, anticipate customer needs and resolve issues proactively. Gartner also predicts that by 2029, these agents will handle 80% of standard customer service questions without human intervention.

While it's still early days, the technology is emerging as a strategic priority. To remain competitive, you need to be prepared.  

AI is math, not magic

Demystifying AI can help businesses understand how to best use it. The technology starts with math, like the algebra you learned in high school, such as plotting curves on an XY axis. Although modern AI models leverage more advanced methods used in statistics, calculus and linear algebra, they build on that same kind of math with more complex systems that use patterns in data to figure out what you're probably looking for to give you the best possible answer. In short, AI is a very powerful tool based on things that can be measured and calculated.

McKinsey explains that AI is evolving from simply providing knowledge or generating content to becoming more capable agents that can perform complex, multi-step tasks autonomously. Agentic AI is not a chatbot that follows a fixed script. These systems function as a "guru" or intelligent intermediary that "connects the dots" of diverse data, integrating insights, acting on behalf of the user, and adjusting to user needs in real-time. Like a vast encyclopedia with agency, AI is shifting from simply providing information to taking action.

Through a SaaS lens

Customers don't really need to know or care about how AI works because users seek simple, effective solutions. Like Dorothy in The Wizard of Oz, the real power of AI lies not behind the curtain but in how users choose to use it. In addition, when customers don't know what they want, the "wizard" (AI) will make recommendations. Consumers encounter this daily as ads or streaming recommendations appear while they scroll through apps, driven by patterns in their behavior.

Traditionally, support systems have leaned on slow, step-by-step human workflows—which can be frustrating for users who expect fast, personalized help. But with agentic AI, SaaS platforms will be able to take things to the next level. Expect agentic AI to simplify the interface between users and technology, delivering the right information at the right time with minimal user effort.

Imagine an AI-powered customer success manager that tracks user behavior to spot signs of churn or improve onboarding. The agent could automatically send personalized messages or tweak in-app experiences to keep users engaged. In another use case example, an agent could handle customer sales complaints from start to finish. This means analyzing order data, processing refunds and updating the right departments without needing constant human oversight.

From concept to capabilities

For businesses, agentic AI has the potential to augment the decision-making process on what tasks should be automated and how best to streamline business processes. Early models suggest a future where users engage through dynamic, chat-based interfaces that are deeply integrated with backend tools and systems. This approach promises to shift customer support away from static "how-to" documentation and one-size-fits-all consulting, toward more interactive, example-driven assistance that adapts to individual needs and scenarios.

Success-based outcomes will improve. Simply diagnosing an issue isn't success, and even offering a solution only gets you partway there. A success-based outcome means understanding the problem, knowing the desired result and delivering a solution that achieves it.

This shift toward adaptive, example-driven assistance can enhance the user experience and enable more meaningful, outcome-oriented interactions. Focusing on delivering success and not just answers is important because organizations want to be able to ensure their tools meet real user needs in practical, measurable ways.

If customers are empowered to explore tailored solutions through guided experiences, organizations could reduce repetitive consulting efforts and deliver more value through scalable, automated channels. This frees up business teams to focus on more strategic initiatives.

Preparing for agentic AI

Begin with targeted development rooted in a clear understanding of the technology's real capabilities. Again, AI is not magic, and if your approach is just to adopt the latest AI, you run the risk of wasting your investment on generic, ineffective solutions. 

Focus on specific, repeatable, high-impact use cases. Identify processes that can benefit from automation, orchestration or decision support, and prioritize areas where AI can enhance efficiency or decision-making under human supervision.

Avoid the temptation to overreach. Plan on incremental implementation with a human in the loop that maintains decision authority. Your systems should be designed to evolve. Avoid monolithic platforms that lock you in and choose vendors that support interoperability and iterative deployment.

Responsible AI adoption should be grounded in secure and ethical practices:

• Implement private large language models (LLMs) where sensitive data is kept within your control. Avoid routing proprietary or customer data through public models without safeguards.
• Establish strong access controls and rigorous authentication protocols to protect both internal systems and AI-driven workflows.
• Develop ethical guidelines and governance frameworks that define acceptable uses of AI agents. This includes maintaining transparency and an auditable trail. 

Reshaping the customer journey

Agentic AI holds the potential to significantly reshape how organizations approach both customer experience and internal operations. It will help users help themselves, while enabling escalation with a human agent when needed.

By developing a foundational understanding of agentic capabilities and identifying processes that could benefit from its integration, businesses can lay the groundwork for smarter, more adaptive customer engagement. The time to prepare is now.