Discussion: Module 7 – AIML-April-2026

[Miranda]

One thing I learned from this class is just how much AI and machine learning are already being used throughout the hospitality industry. Before this course, I mostly thought about AI in terms of chatbots or automation, but now I see how it connects to things like pricing, forecasting, guest feedback, personalization, and daily operations.

I also learned that implementing AI is not only about technology. A lot of important conversations involve privacy, ethics, transparency, and data security. Several of the case studies and discussions showed that guests are more likely to trust these systems when companies are open about how information is being collected and used.

Another thing that stood out to me was how important the human side of hospitality still is. Even with all the advances in AI, guests still value personal interaction, empathy, and genuine service. The best examples we discussed were the ones where technology supported employees instead of trying to replace them.

Two questions I still have are how smaller hospitality businesses will be able to afford and keep up with new AI technologies, and where guests will eventually draw the line when it comes to personalization and privacy.

The part I found most interesting was predictive personalization. It’s interesting to think about how hotels can use past preferences and behaviors to create more customized guest experiences.

My biggest takeaway from this class is that AI is changing hospitality, but it is not replacing what makes hospitality special. Technology can improve efficiency and support decision-making, but people and human connection still matter most.

One quote that sums up my experience in this class would be: “This class helped me better understand how AI is shaping hospitality while also reassuring me how important the human side of the industry still is.”

[Craig]

Hi Miranda,

You have many of the same concerns that I do. I have a few friends who own independent hotels and B&Bs, and the reality is they simply cannot afford to stay at the cutting edge of every new technology that comes along.

What’s interesting is that many of them already pay dues to industry associations such as the American Hotel & Lodging Association, state lodging associations, and regional tourism organizations. I think it’s time for those groups to step up and play a bigger role in helping their members navigate AI by providing practical tools, training, best practices, and genuine solutions rather than leaving each business to figure it out on its own.

The large hotel brands will likely continue to lead the way, but there is a real opportunity for industry associations to help ensure smaller operators aren’t left behind.

[James]

Hello Miranda,

I really like your takeaway about AI and its impact on hospitality. Even though the technology is always evolving, the human element at its core is what’s most important. Workers in the hospitality sector have to make sure we don’t get too far away from the human element.

[Jack]

This has been a great class! Three things I learned about the implementation and impact of AI/ML in hospitality include the following:

1. Predictive analytics, in my estimation, delivers the greatest efficiency impact for guest accommodations including optimizing staffing, inventory, dynamic pricing, and personalized upselling.

2. Human engagement remains essential, at least in the near term; AI can augment service but cannot fully replace the human touch that defines guest experience in hospitality.

3. Small, boutique, and generational family-run properties are particularly vulnerable: they may lack resources to adopt AI/ML while preserving their unique character, and could be displaced or forced to join franchises or perhaps align as cooperatives.

Two questions I still have

1. How can regulators and industry stakeholders balance strong privacy protections (as in parts of Europe) with the flexibility needed for innovation and operational adoption of AI in hospitality?

2. What affordable, privacy-preserving AI deployment models exist for small and boutique properties so they can compete without sacrificing identity or data security?

One aspect I find most intriguing that I had not thought a great deal about includes the following: the convergence of transparency, privacy, accountability, and trust across hospitality and healthcare — using AI to personalize and streamline experiences while safeguarding sensitive data — represents the most compelling transformational opportunity and challenge for leaders in the industry. As a higher education professor, swe need to adapt and model training and skills development for the next generation of hoteliers!

My key takeaway from this class

Effective AI/ML adoption in hospitality requires not only technical solutions (e.g., predictive analytics, IoT sensors, automation) but also rigorous privacy frameworks, human-centered design, and equitable deployment strategies so benefits reach all property types.

Quote of feedback for course promotion/improvement

“This course clarified practical AI/ML uses for hospitality while highlighting critical privacy and equity challenges — highly relevant for professionals bridging operations, guest experience, and regulatory compliance. Generalizable concept learning across disciplines such as healthcare and assisted living.”

Brief personal note (context)

From recent international travel and classmates’ case studies, it’s clear Europe—especially Germany—has advanced privacy safeguards, which both protect guests and slow some AI adoption; cost and regulatory constraints help explain limited deployment of room sensor/smart systems overseas.

Again, I enjoyed learning with everyone. Thank you for the open sharing you all displayed; and thank you to Suzanne and Dale for the excellent video work and resource provision/ curation!

Best,

Jack

[Miranda]

Hi Jack,

Great reflections! I agree with your point that AI can support hospitality operations, but it can’t replace the human connections that make guest experiences memorable. That’s one of the biggest takeaways from this course for me as well.

I also think your concern about boutique and family-owned properties is important. It will be interesting to see how smaller businesses can adopt new technologies without losing the personality and uniqueness that set them apart. And I really liked your comparison between hospitality and healthcare. Both industries depend on trust, personalization, and protecting sensitive information, so there is a lot we can learn from each other.

I’ve enjoyed reading your posts and learning from your perspective during the course. 🙂

[Craig]

Jack, you’re reinforcing a belief I’ve held for some time and one I’ve been sharing with fellow alumni from my university: hospitality is one of the best industries to be in for this new wave of technology.

Used correctly, AI has the potential to make us all better at our jobs, helping us make smarter decisions, work more efficiently, and ultimately deliver a better experience for our guests. What excites me most is that the time and mental capacity it frees up could allow us to focus more on what truly matters—creating genuine hospitality moments and meaningful human connections.

In my view, AI shouldn’t replace hospitality; it should give us more opportunities to deliver it.

[Rachel]

Hi Jack! I enjoyed reading your post. Your point about small boutique and family-run properties stood out to me because I had a similar question about whether businesses that cannot afford AI technology will eventually fall behind larger brands. It will be interesting to see if more affordable solutions become available so smaller properties can stay competitive while maintaining their unique identity. I also agree that human engagement is still essential in hospitality. While AI can improve efficiency and help businesses make better decisions, I think guests will always value personal interactions and great service. Finding the right balance between technology and the human touch will be important as the industry continues to evolve.

[Craig]

Three Things I Have Learned About the Future Trends / Implementation and Impact of AI and ML in Hospitality

1. AI is at its best when it helps operators make better decisions.
One of the biggest lessons I have taken from this course is that AI is not about replacing people; it is about helping them make smarter decisions. In my own role overseeing airport lounges, I am already using AI to analyze guest feedback, create heatmaps that identify problem periods, and better understand where we should focus our resources. Instead of reacting to issues after they occur, AI allows us to identify trends and take action sooner.

2. The opportunities go far beyond guest-facing technology.
Before this course, I probably thought of AI mainly from a guest experience perspective. What I have learned is that some of the greatest opportunities exist behind the scenes. Predictive ordering, staffing forecasts, and food waste reduction all have the potential to improve profitability while also improving the guest experience. As someone currently involved in sustainability initiatives, I find it particularly exciting that AI can help reduce waste while saving money at the same time.

3. Human oversight remains essential.
The more I have learned about AI, the more convinced I am that it still requires strong leadership and oversight. AI can process more data than any individual ever could, but it cannot replace experience, intuition, or human judgment. The best outcomes will come when operators challenge, validate, and refine AI recommendations rather than simply accepting them at face value.

Two Questions I Still Have

1. How quickly will smaller hospitality operators be able to adopt AI?
Large hotel companies, airlines, and hospitality groups can afford dedicated teams and significant technology investments. However, many independent hotels, restaurants, and B&Bs do not have those resources. I am curious to see whether industry associations and technology providers step up to help smaller operators access affordable solutions so they are not left behind.

2. How will regulations evolve around AI?
As AI becomes more involved in guest communications, operational decision-making, and personalization, I still wonder how regulations will evolve, particularly around privacy, data retention, and accountability. We already see strict requirements such as GDPR in Europe, and I expect AI governance will become an increasingly important topic over the next few years.

One Aspect I Find Most Intriguing

The aspect I find most intriguing is the potential for AI to give hospitality professionals more time to focus on hospitality itself. If AI can help forecast staffing needs, identify guest trends, reduce food waste, and automate repetitive administrative tasks, then leaders and frontline employees can spend more time creating genuine hospitality moments and building meaningful connections with guests. To me, that is where the real opportunity exists.

My Key Takeaway From This Class

My biggest takeaway is that AI should not be viewed as a threat to hospitality but as a tool that can elevate it. Throughout this course, I have found myself continually thinking about practical applications within my own lounges, from predictive staffing and ordering to guest sentiment analysis and sustainability initiatives. The organizations that embrace AI thoughtfully and responsibly will gain an advantage, but the winners will be those that use technology to strengthen the human experience rather than replace it.

Feedback on My Experience in This Class

“I came into this course with an open mind and a broad hospitality background spanning 28 years. During that time, I have worked across independent hotels, large hotel chains, restaurants, senior leadership positions within the cruise industry both shipboard and shoreside, and most recently within the airport lounge and contract catering segments. As a result, I have developed a well-rounded understanding of the hospitality industry and the guest journey—from home to airport, lounge, flight, hotel, cruise, and back again.

This course helped me step back and take an eagle’s-eye view of the wider tools, technologies, and innovations that are shaping our industry. While some concepts were familiar, many challenged me to think differently about how technology can support operations, sustainability, guest experience, and decision-making. I have no doubt that I will continue to refer back to many of the topics, guest speakers, and tools introduced throughout this course for years to come as our industry continues to evolve.”

• This reply was modified 3 months, 2 weeks ago by  Craig.
• This reply was modified 3 months, 2 weeks ago by  Craig.

[Rachel]

Hi Craig! I liked your point that AI helps people make better decisions rather than replacing them. That was one of my biggest takeaways from this class too. I also agree with your question about smaller operators. I wonder if hotels that can’t afford AI will eventually struggle to keep up with larger brands that have access to more technology. Your point about AI giving employees more time to focus on hospitality really stood out to me. At the end of the day, guests still want human interaction, and I think the best use of AI is helping employees provide better service, not replacing them.

[Rachel]

One thing I learned in this class is the importance of predictive analytics in hospitality. Predictive analytics uses artificial intelligence to analyze historical guest data, identify patterns, and predict future customer behaviors and preferences. This can help improve the guest experience, make pricing and demand decisions more accurate, and create more effective marketing campaigns. By understanding what guests are likely to want or need, hotels can provide a more personalized experience while also increasing revenue.

Another thing I learned was how technology is changing the way hotels and venues market themselves. Several of this week’s articles discussed virtual tours and how they help sell hotel rooms, event spaces, and amenities. Guests can explore a property before booking and imagine themselves staying there, which can make them feel more confident in their decision. I think this is a great example of technology improving the customer experience while also helping businesses increase sales.

A third thing I learned is how AI can help reduce costs through better staffing decisions. By analyzing booking trends and predicting demand, hotels can better determine how many employees they will need during certain periods. This helps avoid overstaffing during slow times and ensures enough staff are scheduled when business is busy. As labor is one of the largest expenses in hospitality, this can have a significant impact on a hotel’s budget.

One question I still have is how quickly hotels that cannot afford AI and machine learning technology will fall behind competitors that are able to invest in it. Another question I have is how quickly guests, especially older generations, will adapt to highly automated hospitality experiences. For example, my grandfather would never want to stay at a completely contactless hotel where check-in is done through an app and there is little to no human interaction. While many travelers enjoy convenience and technology, some guests still value personal interactions and traditional customer service.

The aspect of AI and machine learning that I find most intriguing is facial recognition technology. I think it is fascinating because it is already being used in places like airports to verify identities and speed up processes. In Charlotte, I have seen systems where travelers scan their ID, have their face recognized, and then proceed through security with very little interaction. It will be interesting to see if hotels eventually use similar technology for check-in, allowing guests to verify their identity without having to show an ID at the front desk.

My key takeaway from this class is that AI and machine learning are not replacing hospitality but enhancing it. These technologies can help businesses make smarter decisions, improve efficiency, personalize guest experiences, and better meet customer needs. However, hospitality is still a people-focused industry, and finding the right balance between technology and human interaction will be important moving forward.

Feedback Quote: This course gave me a better understanding of how AI and machine learning are being used in hospitality today and how they may shape the future of the industry. I enjoyed learning about real-world applications and how these technologies can improve both business operations and the guest experience. One of my biggest takeaways was that AI is not necessarily replacing human jobs, but helping hospitality professionals work more efficiently and make better decisions while still maintaining the personal interactions that are essential to the hospitality industry.

[Craig]

Generational adoption is going to be interesting, i fear many of our older folk will just not want to learn and likely they will be just fine however those around my age (44) will have to learn and understand or we will quickly be surpassed by the generation below us and unfortunately will only have ourselves to blame…. Luckily for us we are the generation that came before computers, before cell phones and as such we learned before and we will learn again. Thanks for sharing Rachel!

[James]

Hello Rachel,

I was definitely intrigued by your question on, “How quickly hotels that cannot afford AI and machine learning technology will fall behind competitors that are able to invest in it”.

That question always cross my mind when I’m at work. I know some of the bigger brands like Marriott and Hilton will be using it soon, so I will some of the other mid-level and lower brands be able to keep business. Good point Rachel.

[Kimberley]

Rachel, you are so right about hotels changing the way they market themselves with AI. I have seen where hotels have not adapted and are unable to reach their target audience, decreasing guest acquisition.

[James]

Three things that i learned about the implementation and impact of AI and ML are:

1. Traditionally, hotels adjusted room rates based on historical seasonal data and manual competitor checks. Modern ML algorithms have turned this into a real-time, predictive science. Platforms like Duetto pull in vast streams of live data—local weather forecasts, flight delays, neighborhood events, and macro-economic trends—to dynamically adjust pricing multiple times a day. The impact isn’t just a bump in RevPAR (Revenue Per Available Room); it allows properties to capture demand they didn’t even know existed while protecting margins during sudden dips.

2. Behind the scenes, AI is tackling one of hospitality’s toughest challenges: labor optimization. Predictive analytics tools can forecast guest occupancy and specific service demands (like peak check-in hours or heavy room-service windows) with incredible accuracy. This allows management to build tighter, smarter staff schedules—minimizing overstaffing costs during slow periods while ensuring the front desk and housekeeping aren’t overwhelmed during surges.

3. The integration of AI-driven guest communication (such as Myma.ai) has proven that automation doesn’t have to feel cold. By handling up to 70-80% of repetitive, incoming guest inquiries—like “What’s the Wi-Fi password?” or “Can I get late check-out?”—AI instant messaging frees up human staff. Instead of being buried under basic phone calls, front desk teams can focus on high-value, high-empathy guest interactions. The industry is finding that the most successful implementation isn’t replacing humans, but using AI to remove the administrative friction so humans can actually play host again.

Two questions I still have regarding AI/ML applications or challenges in hospitality.

Can algorithms manage predictive staffing without destroying employee trust and retention?

Using machine learning to match staff labor to fluctuating, predictive occupancy demands makes perfect sense on a balance sheet. However, hospitality is fundamentally a human-centric business, and a hotel’s culture depends entirely on its team

How do we prevent automated hiring tools from reinforcing historical bias during high volume recruitment?

To combat industry-wide labor shortages, many hospitality groups have implemented AI-driven talent acquisition platforms to screen, score, and rank hundreds of hourly applicants instantly.

One aspect that you find most intriguing about these technologies’ potential to transform hospitality experiences.

What is most intriguing about this technology is the transition from reactive service to predictive, invisible hospitality.

Traditionally, hospitality has been a game of rapid reaction: a guest experiences friction (a loud room, a slow check-in, an incorrect order), they complain, and staff scrambles to recover with a voucher or an apology.

Your key takeaway from this class on AI and ML in hospitality.

Technology is at it’s best when it’s used to make the hospitality experience more human, not less. It’s easy to get caught up in automated messaging and algorithm staffing, but the property should still want to keep a human touch to it.

A quote of feedback about your experience in this class, which might be used for a future course promotion or improvement.

Have real time interaction with the professors and engagement with classmates as well. See about potential employment opportunities that students can look into.

• This reply was modified 3 months ago by  James.

[Kimberley]

I agree that there will be a challenge in AI managing staffing and keeping team members satisfied. I believe AI might eliminate bias that some employees benefited from.

[Craig]

Team, does anyone know how to upload the Case study by following the instructions? I can’t seem to find it unfortunately.

[James]

It’s a voiced over powerpoint, and you will select one of the case study options and present how you engaged with AI

[Kimberley]

Three things I’ve learned

1. AI delivers the most value in hospitality when it augments staff rather than replaces them. This is by handling routine, high-volume tasks (chatbot inquiries, check-in, basic scheduling) so people can focus on higher-touch service moments.

2. Personalization and forecasting are only as reliable as the data infrastructure underneath them. Fragmented systems (PMS, POS, CRM) produce shallow or misleading insights, no matter how sophisticated the AI layer is.

3. Trust, transparency, and consent aren’t optional extras. They are what separates helpful personalization from something that feels invasive, and what determines whether guests actually embrace a new technology (the Henn na Hotel case was a great real-world example of this backfiring).

Two Questions I Still Have

1. How will hospitality brands balance increasingly personalized, AI-driven guest profiles with growing regulatory and consumer expectations around data privacy, especially across different international markets with different privacy laws?

2. How are hospitality brand funding fast-improving changes with AI and constant training and what is the return on investment meant looking like for sustainability?

One most intriguing thing.

AI was supposed to be seen as competition for human workers and so many companies started letting go of staff. Until it was realized that AI is an adjunct to human resource and now have to rehire humans to monitor AI for quality assurance.

Key Takeaway

AI in hospitality succeeds or fails based on discipline, not sophistication: clean data, a clear business question before analysis, sequenced implementation, and a persistent commitment to augmenting rather than replacing human judgment. The technology is rarely the bottleneck; the surrounding practice is.

Feedback Quote

This course gave me a genuinely practical framework for thinking about AI in hospitality; not just the exciting use cases, but the data discipline, ethical guardrails, and sequencing that actually make those use cases work in the real world.

[Samir]