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Breaking Down the Barriers of Using AI in the Vacation Rental Industry

Breaking Down the Barriers of Using AI in the Vacation Rental Industry

Artificial intelligence (AI) is disrupting and transforming industries across the board, and the vacation rental sector is no exception. After years of slow adoption, AI use surged over the past year, with a reported 72% of businesses worldwide incorporating AI, according to McKinsey’s The State of AI in Early 2024 survey. This mirrors the 70.1% AI adoption rate by short-term rental property managers revealed in our 2024 AI in the Short-Term Rental Industry Report.

From marketing and sales to service operations, human resources, IT and more, AI is being used across sectors and business functions, with 50% of companies adopting AI for at least 2 functions, per McKinsey. 

Despite the rapid uptake and cross-functional usage however, there still exists a lag between adoption of the technology and achievement of its full business potential. This is particularly true for smaller sectors like the short-term rental industry. As seen in our report, 32.5% of respondents flagged the complexity and technical challenges of AI as a significant concern, making it the biggest worry among property managers using AI in their business.

In this article, we delve into these key challenges, from system complexity and data limitations to ethical and environmental risks, all of which play a crucial role in shaping AI’s future in the short-term rental sector.

A chart mapping out AI adoption by business organizations worldwide since 2017

Manage Your Expectations: AI is Not Plug & Play

Many vacation rental property managers using AI for the first time mistakenly expect a plug-and-play experience. For example, a question that is regularly posted by new hosts on discussion forums is asking why their dynamic pricing algorithm is setting prices too high or too low. Some users even label the AI tool a scam for not performing as expected. 

In reality, these systems require input and fine-tuning from users to function optimally. To deliver good results, clear parameters must be input and tweaked when necessary. Even an off-the-shelf, fast-deployable AI cannot read minds.

The problem is not relegated to the short-term rental industry. As the IBM Global AI Adoption Index 2023 showed, 35% of respondents found concerns about the lack of skills for implementation a big inhibitor for using generative AI while one-in-five organizations reported not having employees with the right skills in place to use new AI or automation tools. 

Luckily for short-term rental property managers, the gap between purchase and implementation is small and does not require hiring new staff. This is why onboarding is so important. Even a property management system like Hostaway that does not require much fuss can only be harnessed to its full potential if set up right. In fact, large property managers are not afraid to take the time to ensure they are set up to execute for maximized output.

Data Availability: The Fuel for Successful AI Adoption

The effectiveness of AI systems such as guest messaging automation and predictive analytics hinges on data. Property managers taking on new properties for example won’t have an inbox of messages collected over months or historical financial data to draw from. 

In fact, even a whopping 70% of high performers in the McKinsey survey listed experiencing difficulties with data. Meanwhile the IBM survey found too much data complexity (25%) to be a top barrier hindering successful AI adoption.

Insufficient or poor-quality data can severely hamper a system's ability to answer guest queries, for example, or forecast optimal pricing. Unlike in most other sectors, short-term rental property managers are also limited by the lack of applicability of data from one property to another unless they are similarly situated. 

For AI to truly be effective in the vacation rental industry, systems must be trained on comprehensive datasets that accurately reflect the complexities of real-world customer interactions.

This is a line graph that illustrates the number of business functions that businesses worldwide are using AI for in early 2024

Ethical and Regulatory Challenges: The Risks of AI Mismanagement

As AI use becomes more widespread, ethical concerns — particularly around data privacy — too are growing. The European Union’s GDPR regulations set the gold standard for data protections, but many regions including the U.S. lack stringent laws governing how guest data is collected and used by AI systems. 

Property managers, who handle sensitive guest information like contact details, addresses and ID numbers, need to be aware of the ethical implications of using AI-powered tools. And sparse regulations will soon be a thing of the past. 

The European Union’s landmark AI Act was enacted this year while the number of AI-related regulations in the U.S. grew by 56.3% according to Stanford’s 2024 AI Index Report. Most companies are not prepared to handle these risks. 

Only 21% of respondents had even established policies governing the use of generative AI tools by employees in their work according to McKinsey’s 2023 Survey, which can lead to severe privacy and data security issues. The IBM survey found ethical concerns (23%) to be a top barrier hindering successful AI adoption while 43% of IT professionals found data privacy (57%) and trust and transparency to be the biggest inhibitors of generative AI at organizations not exploring or implementing the technology.

As ethical concerns are mainstreamed in importance and regulations address the emerging technology, property managers who are already putting best practices in place will save on costs and mitigate future risks. This is already borne out by the McKinsey survey finding that organizations seeing the largest returns from generative AI are more likely than others to follow a range of best practices.

This is a bar chart showcasing the carbon emissions produced by different activities including GPT-3

Environmental Impacts: The Hidden Cost of AI

The environmental footprint of AI is largely being overlooked. The servers required to run AI models consume vast amounts of electricity and water for cooling purposes and are exacerbating environmental challenges. 

According to the Stanford 2023 AI Index, the bigger the model, the bigger the carbon emission numbers, though power usage effectiveness at data centers and grid efficiency also have an impact. At the time, GPT-3 was the heaviest carbon emitter by far, outputting the total carbon emissions of an average human over a year by more than ninety-onefold.

The McKinsey 2023 Survey notes that companies are becoming more aware of AI’s environmental toll, particularly as consumers demand more eco-friendly practices. Property managers who market themselves as eco-conscious in particular will need to figure out their actual environmental impact and how to offset it.

Mastering AI Integration: Transforming Challenges into Opportunities

The challenges of AI adoption in the vacation rental industry are the growing pains typical in the early days of any technological shift. As AI use cases continue to expand, property managers will become more adept at configuring these systems to deliver optimal results. By addressing these challenges proactively and adopting best practices, property managers can maximize their AI investments, ensuring they stay ahead of the curve while building trust with guests.

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