What happened
As enterprises rush to adopt artificial intelligence, a new major challenge has emerged: architectural fragmentation. Gaurav Anand, global head of the Customer Interaction Suite at Tata Communications, warns that most organizations have implemented AI agents and voice solutions by "bolting" them onto legacy systems that were never designed for such data flows. The result is an inconsistent Customer Experience (CX), where information does not flow seamlessly between messaging, voice, and digital platforms.
Technology context
Orchestration in the AI context refers to the automated coordination and management of workflows between multiple AI models, databases, and user interfaces. Instead of having an isolated chatbot answering simple questions, orchestration allows an "orchestrator agent" to take a complex request, query the company's ERP system, check inventory, and finalize a transaction, all while maintaining conversation context if the user switches from chat to a phone call.
Why it matters
Industry impact is profound because customer expectations have evolved. A modern customer does not want to repeat information when transferred from a bot to a human operator or from WhatsApp to email. Without proper orchestration, AI becomes just another data silo, increasing user frustration instead of diminishing it. For companies, operational efficiency depends on the ability of these agents to work together rather than in isolation.
Key terms explained
- Legacy Systems: Outdated technologies, software, or programming languages that are still used by organizations because they are critical to daily operations.
- AI Orchestration: The process of managing interactions between multiple AI agents and backend systems to execute complex end-to-end tasks.
- CX (Customer Experience): The sum of all interactions a customer has with a brand, from the first website visit to post-sale support.
- Conversational AI: Technology that allows computers to simulate human conversations through text or voice, using natural language processing (NLP).
Impact
In the short term, we will see an increase in investment in middleware platforms that can bridge the gap between AI and legacy systems. Companies that fail to integrate these flows will lose ground to competitors offering instantaneous and personalized responses. In the medium term, the role of the human agent will be radically transformed, becoming a supervisor of the AI agent "orchestra," intervening only in cases of extreme complexity or high emotional stakes.
What's next
Predictions indicate a shift from reactive AI agents to proactive ones. The future of CX will be dominated by systems that anticipate customer needs before a request is even formulated. Furthermore, we will witness the standardization of communication protocols between AI agents from different vendors, allowing for unprecedented interoperability within enterprise ecosystems.
Sources
Analysis based on the report provided by VentureBeat AI and insights from Tata Communications regarding the Customer Interaction Suite.
Educational analysis generated with AI and editorially reviewed.