According to IndustryARC, the AI market in the travel and hospitality sector is projected to surpass USD 1.2 billion by 2026, growing at a compound annual growth rate (CAGR) of over 9.7% between 2021 and 2026.
Artificial intelligence is now reshaping the end-to-end travel journey from the initial spark of wanderlust to post-trip engagement. AI-powered chatbots and virtual assistants are simplifying bookings by handling flight searches, hotel reservations, payments, and even baggage tracking. Meanwhile, automation and robotics are being deployed to enhance baggage handling, ground operations, and turnaround times. As these capabilities mature, hyper-personalization is becoming the new baseline, enabling travel providers to tailor offers, services, and experiences to individual traveler preferences in real time.
However, the promise of AI is tempered by a growing trust gap. A study by National Research Group (NRG) highlights that many consumers remain cautious about relying on AI for critical travel decisions. High-profile instances of poorly generated AI travel content, misleading guidebooks, and inaccuracies in generative AI responses have exposed limitations in data quality, validation, and contextual understanding. These gaps highlight a critical challenge for the travel and hospitality industry: AI adoption alone does not guarantee seamless experiences; trust, accuracy, and quality engineering ultimately determine success.
Key Findings from the NRG Study:
81% of travelers would feel more comfortable double-checking AI-provided information before deciding about their trips.
81% are reluctant to share information about their kids with AI systems.
77% feel uneasy about allowing AI access to important travel documents, such as visas and passports.
51% are concerned that AI-powered travel tools may not adequately protect their personal data.
5 Key AI Challenges Impacting the Travel & Hospitality Industry
Let’s examine some of the most pressing AI challenges currently shaping the travel and hospitality industry, as organizations transition from experimentation to large-scale, real-world AI adoption.
- AI Reliability and Trust Issues
While AI promises efficiency, speed, and personalization, trust remains a critical barrier. Many travelers remain hesitant to fully rely on AI systems for high-stakes tasks, such as booking, itinerary changes, or handling personal information, especially during disruptions like delays or cancellations. In travel, where real-time accuracy is non-negotiable, even small errors in recommendations or system responses can quickly erode traveler confidence.
- Ethical Considerations and Transparency
As AI increasingly drives personalized offers, pricing, and recommendations, ethical concerns around privacy, transparency, and algorithmic bias are intensifying. Travelers are more aware of how their data is collected, stored, and used and are wary of opaque AI decisions that cannot be explained or justified. Industry observers highlight that biased or incomplete datasets can lead to unfair pricing, skewed recommendations, or exclusionary experiences. Without transparency and governance, AI-driven personalization risks damaging brand trust rather than strengthening it.
- The Complexity of AI Technologies
AI systems are inherently complex, requiring specialized skills, high-quality datasets, and continuous model tuning. Many travel organizations struggle to source diverse and representative data or to attract and retain talent capable of building and maintaining advanced AI solutions. According to McKinsey & Company (2024), a significant portion of AI initiatives stall because organizations underestimate the engineering and operational complexity required to move from pilot to production. For smaller and mid-sized travel players, the upfront investment and skill gap can make AI adoption particularly challenging.
- Managing and Processing Large Volumes of Data
Travel and hospitality companies operate across fragmented data environments spanning booking engines, loyalty platforms, CRM systems, operational systems, and social media channels. Integrating and processing this data at scale remains a major hurdle. Poor data quality, inconsistent formats, and siloed systems can compromise the accuracy of AI, resulting in unreliable predictions and recommendations. As AI models are only as good as the data they consume, data management and validation remain foundational challenges for the industry.
- Scalability
As travel demand fluctuates and digital engagement grows, AI systems must scale seamlessly to support increased users, transactions, and real-time interactions. Designing AI architectures that can handle peak loads while maintaining performance and responsiveness is a persistent challenge. Many organizations find that AI solutions that perform well in controlled environments struggle under real-world conditions, particularly during seasonal surges or disruption scenarios. Scalability, therefore, becomes not just a technical concern but a critical business requirement.
Tackling AI Challenges in Travel & Hospitality
Building AI Reliability and Trust at Scale
To address concerns around AI accuracy, reliability, and real-world performance, Coforge integrates comprehensive quality engineering and testing strategies into AI solutions for the travel and hospitality sector. The focus is on validating critical, high-impact systems, including booking engines, customer data platforms, pricing and revenue systems, and real-time operational platforms. By rigorously testing these components across expected and unexpected scenarios, Coforge ensures that AI systems continue to function accurately under peak loads, disruption events, and dynamic customer interactions.
Coforge’s Test Center of Excellence (TCoE) plays a central role in validating AI-driven travel applications, including Point of Sale (PoS) systems, integration layers, and downstream services. This approach ensures seamless system performance, consistent outcomes, and reliable customer experiences across channels.
Addressing Ethical Concerns Through Responsible Data Management
As AI-driven personalization becomes more prevalent, ethical data usage and privacy protection are critical to maintaining traveler trust. Coforge’s data management frameworks are designed to ensure responsible, transparent, and secure use of customer data across the AI lifecycle. By enabling centralized data architectures, such as data lakes, Coforge helps travel organizations store and manage travel-related data in both raw and structured formats, supporting flexibility, traceability, and governance.
This foundation allows AI models to be trained on high-quality, representative, and unbiased datasets, reducing the risk of skewed recommendations, privacy violations, or unintended bias. Coforge’s approach to ethical AI enables travel companies to deliver hyper-personalized experiences while maintaining compliance, data security, and user confidence.
Enabling Scalability and Simplifying Complex AI Deployments
Scalability is a defining requirement for AI adoption in the travel and hospitality industry, where demand fluctuates, and real-time responsiveness is essential. Coforge leverages cloud-based architectures to help organizations design AI platforms that scale efficiently as data volumes, transactions, and customer interactions grow. These cloud-native approaches enable flexibility, cost optimization, and resilience, allowing AI systems to perform reliably during peak travel seasons and disruption scenarios.
In parallel, Coforge’s experience in executing large-scale modernization and migration programs helps organizations deploy advanced AI capabilities with minimal operational disruption. This ensures that complexity does not become a barrier to innovation, allowing AI initiatives to transition confidently from pilot to enterprise scale.
Conclusion
As AI continues to reshape the travel and hospitality industry, success depends on more than innovation alone. Addressing challenges related to reliability, ethical data usage, scalability, and operational complexity is essential for AI to deliver sustained value. Coforge brings together deep travel domain expertise, AI-led engineering, quality assurance, and cloud transformation capabilities to help organizations overcome these challenges holistically.
By embedding trust, governance, and scalability into AI solutions from the outset, Coforge enables travel and hospitality organizations to deliver seamless, personalized experiences, improve operational efficiency, and build lasting customer confidence. With the right foundation in place, AI evolves from an experimental capability into a trusted, integral part of the end-to-end travel journey.
Need help? Connect with Coforge experts to explore how digital assurance, AI engineering, and cloud services can help you overcome AI challenges and transform travel and hospitality experiences at every stage of the customer journey.