Travel and Hospitality Companies Are Missing Out on AI-Driven Profits

In the fiercely competitive travel and hospitality sector, companies would be foolish to overlook the crucial opportunities that AI presents for profit enhancement. Despite achieving some operational cost reductions and modest sales increases through IT and operational improvements, a more strategic application of AI has the potential to dramatically boost revenue.

Recent findings from a survey conducted by Rackspace Technology in collaboration with AWS (Amazon Web Services) shed light on this issue. The survey, which polled 1,420 global IT decision-makers, reveals that AI has already contributed to cutting operational costs for 42% of travel and hospitality companies and increasing sales for 50% of them. Despite these gains, there is a stark contrast in how AI strategies are implemented across different units within these organizations.

Currently, only about one-third (32%) of AI strategies in the travel and hospitality sectors originate from revenue-generating units, while the majority—50%—are driven by operational divisions. This misalignment is striking, considering that 66% of these companies identify revenue growth as the primary key performance indicator (KPI) for assessing the success of their AI and machine learning (ML) initiatives. This indicates a significant missed opportunity for leveraging AI to maximize revenue.

While challenges still exist in fully harnessing the benefits of AI, there are several key areas where IT departments can maximize their ROI.

AI and Marketing

AI is already proving its worth in travel and hospitality. According to the survey, 52% of companies across the industry say they are seeing substantial benefits from AI, including increased sales (50%), enhanced innovation (51%), reduced risk (46%), and more personalized marketing campaigns (49%). This reflects a broader trend where AI is being utilized to enhance customer engagement and improve service delivery.

But the potential benefits of AI extend beyond these metrics. For instance, AI-driven tools can refine marketing strategies by analyzing customer data to deliver tailored promotions, optimize pricing strategies through dynamic adjustments based on market conditions, and improve operational efficiency through predictive maintenance and resource allocation. This comprehensive application of AI can result in a more engaged customer base, higher retention rates, and ultimately, increased revenue.

Embracing Private Cloud for Revenue Growth

One critical area where many travel and hospitality firms are falling short is in their adoption of private cloud solutions. While public cloud services are often perceived as an easier route to revenue generation due to their scalability and lower initial costs, private cloud environments offer unique advantages that can drive revenue growth.

Private clouds provide a level of customization and control that can lead to improved margins and more sustainable business expansion. By allowing companies to tailor their cloud infrastructure to meet specific needs, they can enhance competitive advantages and support strategic business goals more effectively. This flexibility is crucial for implementing AI solutions that often require secure and efficient handling of sensitive data.

Survey data reveals that 73% of IT decision-makers in the travel and hospitality sectors plan to invest between $500,000 and $5 million in AI this year. This represents a substantial increase in budgets compared to the previous year and highlights a growing recognition of AI’s potential to drive revenue. However, to fully realize this potential, companies should think holistically about how they can integrate AI with private cloud solutions.

Overcoming Barriers

Several barriers continue to hinder the effective implementation of AI across the travel and hospitality sector. Data management, cybersecurity, and trust in AI/ML outputs remain major concerns. 55% of survey respondents acknowledge the increasing importance of fraud detection and cybersecurity, while 52% express worries about data security risks associated with irresponsible AI practices. Data privacy is another significant worry, with 58% of respondents highlighting it as a key factor in responsible AI use.

Furthermore, 59% of IT leaders in the travel and hospitality industry identify cybersecurity as the greatest risk in AI adoption, while 68% believe that the accuracy of AI/ML systems needs substantial improvement before they can be fully trusted. These concerns underscore the need for a balanced approach that combines robust security measures with continuous improvement in AI accuracy and reliability.

The Demand for AI/ML Skills

As AI technology advances, the demand for skilled professionals capable of managing and leveraging this technology is also growing. According to the survey, 86% of travel and hospitality companies have actively sought to add employees with AI/ML skills over the past year, though competition for talent remains fierce. Having a workforce proficient in AI and ML is essential for harnessing the full potential of these technologies. Companies that invest in upskilling their employees or place an emphasis on recruiting top talent are better positioned to implement effective AI strategies and achieve their revenue goals.

FinOps: Optimizing Cloud Spending

An often-overlooked aspect of AI adoption is the financial management of cloud services. Many travel and hospitality companies may be overspending on cloud services, especially as their AI usage increases. This is where FinOps—a practice aimed at optimizing cloud spending—becomes crucial.

FinOps involves strategies to maximize the value of cloud services while controlling costs. It can be implemented internally or outsourced and even enhanced by AI for large-scale optimizations. As of 2024, approximately 60% of corporate data is stored in the cloud. However, many organizations fail to realize cost savings from their cloud migration efforts because they did not have a robust FinOps program in place.

Clearly, travel and hospitality companies have a significant opportunity to enhance their profitability through a more strategic application of AI. By extending AI use beyond operational improvements to encompass revenue-generating units, embracing private cloud solutions, addressing barriers to implementation, and optimizing cloud spending through FinOps, these companies can unlock new levels of revenue and drive sustainable growth in an increasingly competitive.

About the Author

Nirmal Ranganathan isVice President of Engineering, AI - Rackspace Technology.