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The future of CX: AI agent stacks are redefining complex inquiry handling for lightning-fast service

AI in customer engagement started with chatbots, but modern demands call for a broader, comprehensive approach to AI-powered solutions.

The future of CX: AI agent stacks are redefining complex inquiry handling for lightning-fast service

Thursday March 13, 2025 , 4 min Read

Hubspot’s Future of Customer Service Report, which reviewed more than 100,000 customer interactions across industries, shows that nearly 60% of customers expect their issues to be resolved immediately (the report defines a response within 10 minutes as immediate). In comparison, less than half had this expectation five years ago. That is a significant shift in customer demand.

This trend is particularly noticeable in India, where most consumers are aged between 21 and 35 and the median age is 28. Having grown up with on-demand services, whether for dating, transportation, or meals, customers today see little reason to wait long for support.

In 2019, many businesses concentrated on converting leads. Now, companies face a dual challenge: they must convert leads while also addressing complex product inquiries, troubleshooting technical issues, and offering personalised recommendations in near real-time.

This situation creates a conflict between increasing product complexity and decreasing customer patience. Traditional service models are finding it difficult to meet both demands effectively.

Beyond chatbots: A comprehensive approach to AI-powered solutions

AI in customer engagement started with chatbots, but modern demands call for a broader solution. 

A complete system today needs to address several key areas:

  • Workflow orchestration: AI should manage the entire customer workflow by breaking down complex processes into manageable tasks that can be either automated or handled by human experts.
  • Human oversight: Although AI can manage many routine tasks, human intervention is necessary when situations require nuanced judgement.
  • Omnichannel engagement: The system must function across chat, voice, email, and social media, ensuring that interactions remain continuous even if a customer switches channels.
  • Knowledge management: AI should organise and access vast amounts of information quickly to provide the most appropriate responses.
  • Data classification: Automated tools can analyse inputs, such as product images, to identify issues promptly, reducing the need for manual review.
  • Continuous improvement: Regular updates and training are essential for maintaining accuracy and relevance.
  • Customer sentiment analysis: Monitoring feedback helps identify areas for improvement and informs strategic decisions.
  • Deep integrations: Connecting with CRM, ERP, and ticketing systems ensures that customer interactions are informed by up-to-date business data.
  • Data security and compliance: Safeguarding customer information is a fundamental requirement.

The role of human-AI collaboration

Advances in AI have been impressive, yet the best results are achieved when technology works alongside human expertise. Research from McKinsey indicates that companies using integrated human-AI systems report 30% higher customer satisfaction than those relying solely on one approach. 

In practice, AI handles routine investigations and standard inquiries, while human agents step in to manage more complex issues and provide additional context. This balanced approach helps ensure both rapid response and thoughtful, effective problem resolution.

Looking ahead

Customer engagement is set to be transformed by systems that can simultaneously process text, images, audio, and video. Early examples already let users snap a photo of malfunctioning equipment, with the technology analysing the image, pinpointing the issue, and guiding them through a solution—all in one smooth interaction.

Forrester’s forecasts for digital transformation in customer support stress that by 2026, advanced data integration will be critical for handling complex inquiries, with many analysts estimating that around 85% of such interactions will depend on a combination of data types (e.g., CRM data, real-time chat logs, social media signals, and historical customer information). 

The increasing demand for systems that can smoothly manage a variety of inputs is highlighted by this trend.

Hybrid solutions are the way of the future for customer support as products get more complex and client patience declines. Moving from simple chatbots to fully automated, networked workflows that improve the customer experience at scale, the emphasis is now on integrated solutions where AI and human intelligence collaborate rather than having to choose between automation and human touch.

The author is CEO and Co-founder of Squadstack, a SaaS-enabled talent marketplace for sales.


Edited by Swetha Kannan

(Disclaimer: The views and opinions expressed in this article are those of the author and do not necessarily reflect the views of YourStory.)