Talkdesk Survey Finds Customer Experience AI Adoption Outpaces Orchestration

Generative AI is in use at 74% of the organizations surveyed and scripted AI at 65%, while 24% use agentic AI, which refers to systems that take a goal, reason through it and act across systems. Eighty-one percent are piloting or deploying AI agents, yet only 19% have scaled beyond a single use case, and nearly 80% run fewer than 10 AI automations in production.

Pedro Andrade, vice president of AI at Talkdesk, presented the findings in an analyst briefing. "AI adoption is no longer a question," he said. "Now the question is whether organizations can orchestrate all the elements needed to deliver measurable customer outcomes — agents, humans, data, knowledge, workflows, and governance — all in one package."

Talkdesk describes the gap as carrying a dual cost: companies pay for isolated AI tools while still absorbing the operational cost of customer requests those tools never complete. Founder and Chief Executive Tiago Paiva called the result "a false sense of progress," arguing that widespread deployment masks how few organizations can quantify AI's impact.

Sixty-four percent of organizations run specialized AI agents for functions such as identity verification, billing or technical support, but only 35% have AI that can maintain customer context and act across systems to drive resolution. "Routing work is not the same as resolving it," Andrade said. He cited a car accident as an example: one event triggers a tow provider, a claim, a repair shop and a rental — multiple departments, multiple systems, one expected outcome. Fifteen percent of companies can automate that journey end to end.

The research organizes respondents into a five-stage maturity curve with two chasms. The first, the agentic threshold, separates scripted and generative AI from AI that acts; 56% of organizations fall below it. The second, which Talkdesk calls the CXA unlock, moves from isolated agents to autonomous cross-system execution. Twenty-nine percent are Agentic Scalers with one of the two capabilities, and 15% are CXA Leaders with both.

CXA Leaders are roughly four times more likely than Scalers to report major gains in customer satisfaction or net promoter scores, 22% versus 5%. Thirty-eight percent already resolve more than 40% of customer issues autonomously, while 60% of Scalers still resolve fewer than 20%. Leaders are also about twice as likely to run revenue-oriented automations, such as churn prediction (51% versus 28%) and personalized recommendations (44% versus 19%).

Respondents pointed to infrastructure rather than model capability as the constraint. They cited compliance (50%), security (48%), disconnected systems (45%), legacy infrastructure (44%), insufficient skills (41%) and unclean or non-unified data (40%). Human agents lose an average of 28% of their time to system switching, data re-entry and searching for customer context, a figure that climbs to about 35% in the least mature organizations and falls to roughly 25% in the most mature. Respondents estimate that incomplete context, repeated explanations and manual escalations affect roughly one in four customer interactions, and 94% of organizations lack AI-assisted knowledge management.

Andrade said the knowledge problem is the one he hears about most often in customer meetings. "It's not about actually having it. It's more about how I make it ready to be consumed by AI." Only 64% of CXA Leaders have knowledge embedded in the workflow or assisted by AI.