By Alessio Delpero, Professor of Strategic Management and Innovation in Hospitality at Glion Institute of Higher Education - 12.15.2025
What is the fastest adopted technology in history? WhatsApp, perhaps? That may once have been true, but the title now belongs to ChatGPT.
This should come as little surprise to anyone who follows the news media, which has become almost obsessed with the technology. Wherever you look, AI is either going to save the world or destroy it, create jobs or eliminate them. Either way, it seems clear that things will never be quite the same.
As an academic with a focus on innovation, the current moment we find ourselves in with respect to AI and other emerging technologies is genuinely fascinating. That is largely because no one truly knows the extent to which AI applications might disrupt an industry such as hospitality. Could these innovations eventually become as fundamental as the rise of Airbnb or online travel agencies like Booking.com?
There is certainly plenty of signal and noise. But the vital point to understand is that AI is an enabler, a platform, not a solution in and of itself.
The ability of AI to absorb and synthesize vast quantities of information is already being used to address what I would call “low-hanging fruit,” such as refining marketing campaigns or optimizing operational processes. We are also seeing some playful experimentation, including chefs using AI to develop new recipes. However, it is important to distinguish between gimmicks and genuine progress for the industry.
The recombination promise
Can AI actually drive genuine, blue-sky innovation? After all, at the heart of the technology lies an aggregation of existing data and knowledge. This is a critical question, and one that brings to mind Joseph Schumpeter, the Austrian economist often described as the “father of innovation,” who defined innovation as the recombination of existing resources and knowledge.
Consider the smartphone and the excitement that followed when it incorporated a digital camera. That was innovation through recombination: mobile phone manufacturers simply adopted a technology developed by digital camera makers. Viewed through this lens, could AI have the capacity to innovate through recombination?
In principle, this is entirely possible, given the vast amount of knowledge and data AI models can access. We have already seen promising experimentation in fields such as pharmaceuticals, where AI has helped generate advanced new drugs by recombining molecules. However, at present—particularly in sectors where user experience is paramount—the technology lacks the layer of human intuition that often emerges from tacit, non-codified knowledge. Without this, AI struggles to recombine knowledge in ways that produce truly game-changing innovation.
This is why I believe the human element remains essential to the innovation process. Regardless of the many ways humans and AI may collaborate, the key message is simple: we should use AI for its strengths as a tool, while recognizing its limitations.
In academia, for example, we have unfortunately seen a surge in fully AI-generated essays and dissertations. These are often suboptimal in quality and easy to detect due to inherent shortcomings, such as fabricated citations or references to non-existent sources.
Similar issues are emerging in business. One high-profile example involved Deloitte Australia, which reportedly received a substantial fine after submitting a report containing AI-generated errors.
For managers, an overly AI-reliant approach carries clear risks. If a task is delegated to an AI system and it produces an error, who is ultimately accountable? The technology itself, or the human overseeing it? These uncertainties must be addressed before organizations can deploy AI with full confidence.
This is why it is increasingly important to train people—students, employees, and collaborators alike—to use AI and large language models wisely and responsibly.
That said, this assessment reflects the current state of the technology. AI is evolving rapidly, and I would not be surprised if I am forced to revise some of these views in the near future.
Other innovation streams in hospitality
While AI dominates headlines, it would be a mistake to overlook other important innovations emerging within hospitality. I see four primary drivers: labor shortages, sustainability, personalization and customization, and new business models.
Labor shortages are well known across the industry. During the pandemic, many hospitality workers moved into other sectors, and a significant number have not returned. This shortage has accelerated innovation around process optimization and the use of technology to replace humans in repetitive tasks. Whether through robot bartenders or fully automated check-in, the industry remains in an experimental phase, and it will take time to determine which approaches will endure.
Sustainability is the second major driver. This spans the entire hotel lifecycle, from construction materials to energy efficiency and local sourcing of food. While hospitality has not led radical change in this area, it has adopted best practices from other industries and responded to guests’ growing environmental awareness. One interesting development is the use of data to guide guests away from overcrowded destinations during peak periods and toward less-visited locations or off-season travel.
The third driver is the growing demand for customization. Hotel guests increasingly expect personalized experiences and a steady supply of novel offerings they can share on social media. Operators are responding by carving out niches tailored to specific segments, such as luxury hotels targeting families while maintaining an exclusive positioning. Hyper-personalization has few theoretical limits, provided it is economically viable, and AI is becoming a useful tool to support this across the guest journey.
The fourth driver involves new business models. Concepts such as all-you-can-stay hotel passes illustrate genuine experimentation, often inspired by platforms like Airbnb. As with all innovation, the challenge lies in distinguishing scalable ideas from those that are little more than marketing exercises.
These drivers frequently overlap. Sustainability can lead to new business models, while AI and digitalization often act as enablers across multiple innovation streams.
Barriers to innovation adoption
In my experience, the greatest barrier to innovation is inertia. “We’ve always done things this way—why change?”
This presents a familiar dilemma for managers who recognize the necessity of innovation but struggle to embed it across an organization. The classic case study is Kodak, which foresaw the rise of digital photography and even invented the digital camera, yet failed to adapt due to entrenched core competencies that became core rigidities. The company filed for bankruptcy in 2012.
Larger, more established organizations tend to face this challenge most acutely. One effective countermeasure is partnering with startups, allowing companies to explore new domains while maintaining focus on their core business. Another approach is acquiring innovation, as seen when groups such as Accor and Marriott International entered new segments by acquiring brands like Mama Shelter and citizenM.
However, acquisition carries its own risks. Absorbing a startup into a corporate structure can stifle the independence that made it successful. A strong example of managing this balance is Disney’s acquisition of Pixar in 2006. By allowing Pixar to retain operational autonomy, Disney preserved the creative engine that continues to produce innovative films decades later.
Don’t overlook the human element
Amid the pursuit of innovation, it is crucial not to lose sight of hospitality’s defining trait: it is fundamentally a human business. While much innovation focuses on tangible systems and processes, success in hospitality is equally driven by intangible factors—human interactions and the psychological responses they create.
This represents a significant research opportunity: how to incorporate the human element into models traditionally focused on variables such as space and time. Measuring feelings, memories, and emotional responses remains a challenge. How do you quantify the moment when a hotel fragrance triggers a positive memory?
These questions invite collaboration across disciplines, including innovation studies and psychology. For hospitality researchers and industry leaders alike, the future promises continued experimentation, discovery, and thoughtful exploration of how technology and humanity can coexist.
Alessio Delpero teaches Strategic Management and Innovation in Hospitality at Glion Institute of Higher Education. He founded and managed companies in the sport and hospitality sectors before entering the world of academia, and his research activities explore how firms recombine knowledge to innovate, with a specific emphasis on how digital technologies – especially AI – shape creativity and innovation at individual and organizational levels. Alessio holds a PhD in Business Administration and Management from Bocconi University, where he also taught.
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