One of the early use cases of Generative AI has been around, how to create, manage and operate Agents for supporting existing customers. As you might have noticed, Salesforce has been promoting AI agents in their platforms, so do other providers like Servicenow, Zendesk. Naturally it is the extension of their business model to protect existing business from over AI optimization, while making sure a their version of AI narrative is promoted. However there are plenty of AI-First agent products have been coming to market in 2024. We have seen good adoption of these agents in enterprise context.
As these technologies mature, a crucial conversation has emerged around leveraging AI for end-to-end customer support and success. This includes new customer onboarding to providing product support(including tech support in most cases).
So, if you are a Chief Customer Officer or Leader in this organization, naturally you have to be able to create Ai strategy to adopt agentic software capabilities. In most organizations, these capabilities are provided by IT function. However it is crucial to be able to understand and create your own strategy around AI for your department beyond toolings. Following are crucial points that keeps coming up in conversations between Exec Leadership and Chief Customer Success office.
"How can we leverage AI Agents to best support to customers to make them successful?"
"What's the fastest path to optimize existing customer support systems and data?"
"How can we increase key KPIs such as NPS and CSAT while optimizing customer success/suport investments?"
"How do we maximize our existing talent's efficiency?"
"Which current Gen AI/Agent tools can deliver immediate productivity gains?"
While these questions are critical, the answers vary significantly based on organizational role and AI expertise. This has created three distinct stakeholder groups:
1. Investors, particularly in PE and VC spaces, seeking efficiency gains in customer success and support budgets beyond offshoring.
2. Organizational leaders driving acceleration and digital transformation initiatives need to show ROI backed by key metrics including efficiency gain metrics
3. Product Support, Success and onboarding leaders tasked with adoption, and implementation
For those in the third category, the responsibility is significant. Success requires crafting both short and long-term strategies through careful discovery, stakeholder education, and adaptive road mapping - all while navigating this rapidly evolving technological landscape collaborating with technology function.
The challenge isn't just about adopting new tools - it's about understanding their true potential and limitations in your specific customer success, product and operational context. As we move forward, the winners won't be those who simply embrace AI, but those who strategically integrate it into their customer lifecycle managment processes while maintaining focus on business outcomes.
We invite you to learn from our real-world experience in developing and executing AI strategies, and discover how we can support your organization's AI journey.
