After the Booking: Where Spotnana’s CEO Sees the Untapped Economics

Most travel companies concentrate on discovery and the sale. Steve Singh, executive chairman and CEO of Spotnana, points instead to what happens after the booking: cancellations, refunds, changes and support. In his view, that unglamorous servicing layer is where travel businesses actually earn or lose trust and margin.

Singh says Spotnana is already using AI agents to handle routine servicing tasks including cancelled segments, unticketed flights and refunds. Human agents, he argues, can then focus on higher-value interactions where personal service matters. He believes servicing costs can fall by 50% or more while the traveler experience becomes more personalized and proactive.

That claim rests on a broader infrastructure bet. Spotnana has built direct connections with airlines, hotel chains and other travel providers so that a booking change made in one system is reflected everywhere. As conversational AI narrows the options shown to travelers, Singh says providers must supply richer, accurate product information, and direct integrations are the best source of that data. He will make his case at Skift Global Forum in New York from September 22 to 24, alongside executives from Sierra, Booking Holdings and Expedia Group.

Inside Singh’s Servicing Thesis and the Questions It Raises

Why the Servicing Argument Reframes Travel Investment

Singh’s case is that search, distribution and booking are crowded battlefields, while servicing has been treated as a cost centre. If AI can reliably absorb routine post-purchase work, the economics of that cost centre changes. The strategic question is whether the advantage sits with the platform that automates servicing best, or with the consumer brand a traveler remembers when something goes wrong.

Spotnana’s 50% Target Is a Large Claim on a Hard-to-Compare Cost Base

The 50% or more reduction is Singh’s company-specific target and current observation, not an audited industry result. Servicing costs are often hidden inside support teams, operations budgets and agency workflows, making direct comparison difficult. The test is whether the same reduction holds outside a managed-travel platform built for automation, especially where legacy systems and fragmented content remain.

What Happens to Human Agents Once the Routine Queue Disappears

Singh frames automation as freeing humans for high-value service. The unresolved point is whether that higher-value work generates enough volume to absorb displaced agents, or whether total agent headcount simply shrinks. For travel management companies and agencies, that distinction determines whether AI servicing is a margin story or a job-contraction story.

The 95% Curation Bar Is Specific but Needs an Auditor

For conversational AI booking, Singh says Spotnana aims to present the option a traveler would have chosen at least 95% of the time from the full list. It is a precise and testable standard, but he does not say who audits that figure or what the missing 5% costs a traveler. If a narrowed set of recommendations erodes trust, the savings from automated servicing could be spent repairing it.

Direct Connections Are the Real Infrastructure Behind the Thesis

The servicing and curation arguments depend on direct links to airlines, hotel chains and other providers. Without those connections, an AI agent cannot safely cancel, rebook or synchronize changes across systems. That gives integrated platforms an advantage over middle-layer aggregators that depend on third-party content.

What Travel Operators Should Do With the Servicing Shift

For travel operators and corporate travel buyers, Singh’s argument suggests specific areas to test rather than a vendor headline to accept at face value.

  • Establish your current servicing cost per booking for cancellations, refunds and unticketed segments. Spotnana’s 50% target is only useful against your own baseline.
  • Test AI automation on the three tasks Singh names as live at Spotnana: cancelled segments, unticketed flights and refunds. These are the clearest proof points.
  • Require vendors to define who audits any curation metric. Singh’s 95% standard is meaningless without a defined audit method and a documented cost for the missed 5%.
  • Prioritize direct integrations with airlines and hotel chains over third-party content alone. Singh argues direct sources provide richer product information and make booking changes synchronize across systems.
  • For corporate travel programs, ask your TMC or platform whether AI servicing is already deployed and whether any savings are contractually benchmarked, rather than relying on a general percentage claim.

Risk & Opportunity Assessment

Commercial RiskMediumIf Singh’s 50% servicing-cost reduction is realized at scale, travel agencies and TMCs that do not automate routine servicing could lose margin and client contracts. The claim remains unproven outside Spotnana’s platform.
Competitive RiskHighIntegrated platforms with direct provider connections and AI servicing could gain a structural advantage over human-heavy agencies and aggregators that rely on third-party content.
Regulatory RiskLowNo new regulation is mentioned. AI handling of refunds and cancellations could later attract consumer-protection or accountability scrutiny, but no regulatory trigger is indicated in the story.
Reputation RiskMediumSingh ties trust to service. If AI agents mishandle cancellations or conversational AI narrows recommendations incorrectly, travelers may lose trust quickly.
Technology DisruptionHighAI agents are already taking over cancelled segments, unticketed flights and refunds at Spotnana, shifting work away from human agents and changing the data requirements for booking and service.
Commercial OpportunityHighA 50% reduction in servicing costs, with more personalized and proactive service, would create significant margin opportunity for platforms that can automate reliably across integrated content.