What Changed in AI Over the Last 12 Months?

Over the past 12 months, AI models have improved dramatically in both reasoning and generation capabilities. That progress is creating a fundamental shift in how software is built and how customer experiences are delivered. For years, customer service automation relied on traditional chatbots, voice bots, and IVR systems. These solutions typically followed deterministic workflows with predefined steps, sequential logic, and conditional branching. Their primary goal was to answer questions and route customers through a process. Today's AI agents are different. Modern AI agents are no longer limited to responding to queries. They can execute actions, complete workflows, and work across multiple systems, policies, and business functions. Instead of operating as isolated automation tools, they can coordinate information and tasks across teams and platforms to help resolve customer needs end-to-end. This shift represents a move from single-agent automation to multi-agent, action-oriented systems capable of handling increasingly complex business processes. In this short clip, we explore: -- How AI models have evolved in the last year -- Why traditional chatbot architectures are changing -- The difference between answering questions and completing workflows -- The rise of multi-agent AI systems -- What these changes mean for the future of customer experience (CX) As AI capabilities continue to advance, businesses are rethinking what's possible in customer service, support, and automation. #ai #artificialintelligence #banking #aitools #digitaltransformation #fintech #futureofai #aiautomation #aiagents #agenticai #enterpriseai #service #kore_ai