AI to reshape CX and call centers in 2026, says ibex CTO
NEW JERSEY, UNITED STATES — As companies enter 2026, artificial intelligence (AI) is no longer just an experiment in customer experience (CX) but a defining factor that separates leaders from laggards in the global call center industry.
While many enterprises have poured resources into AI, results have been uneven, sharpening the focus on execution, agility, and real-world impact rather than ambition alone.
In a Forbes thought leadership article, Michael Ringman, chief technology officer at ibex, argues that the coming year will mark a turning point in how AI reshapes CX and contact center operations.
He notes that despite widespread adoption, “many organizations are going to struggle to demonstrate the ROI of AI,” even as investments continue to rise.
BPOs driving AI strategy and agent empowerment
According to Ringman, business process outsourcing (BPO) providers are poised to play a larger role in helping enterprises close the gap between AI investment and measurable outcomes.
As BPOs handle direct customer service work, they provide brands with authentic use cases that have significant business value since these firms know best how to handle customer interactions.
“I believe that the role of BPOs will shift to become trusted partners who educate clients on how AI in the contact center can fundamentally improve customer engagement,” Ringman said.
He added that AI should ultimately be used to “do a better job of meeting customers where they want to be met.”
Rather than replacing human agents, AI is expected to amplify their effectiveness. Ringman emphasizes that “the role of the agent will not diminish in the age of AI,” adding, “I believe it will grow stronger.” This trend is supported by analysts who urge blending human strengths with AI intelligence in 2026.
Tools such as voice analytics, sentiment analysis, and large language models are increasingly being deployed to help agents respond in real time to complex, highly individualized customer needs.
Transforming QA and knowledge management in CX
Beyond agent support, Ringman points to knowledge management as a critical enabler of AI success. Enterprise knowledge remains fragmented, and AI-driven systems that surface the right information at the right moment are becoming essential.
“Enterprise knowledge is scattered across the organization,” he wrote, highlighting the need to make internal data instantly accessible to frontline teams.
Quality assurance is also undergoing a transformation. Ringman notes that QA today often relies on limited sampling, but AI will allow organizations to analyze every interaction across channels, shifting the focus toward understanding the full CX rather than isolated agent performance.
Customer journey mapping has developed into an essential strategic priority for organizations.
The validation of customer movement assumptions through chatbots, IVRs, and live support will enable companies to identify friction points and emotional distress areas, which will result in a better understanding of customer needs.
The outsourcing industry faces both new business prospects and potential dangers because of these market changes. BPOs that succeed in using advanced AI technology together with their in-depth business knowledge will achieve greater strategic importance.
Organizations that cannot advance from their current partial AI implementation will face difficulties in competing within a market that now values fast execution and effective coordination as its main advantages.
