Jason: Thibault, as we geared up for our on-stage panel, there was a lot of buzz surrounding AI. Despite my involvement in this field since 2016, I still had mixed feelings about it. On one hand, I was hopeful that more people were recognizing the immense opportunities AI could bring, revolutionizing decision-making across all aspects of business and life. This optimism fueled the inception of Pace Revenue. However, I must admit, I also had some doubts about the sudden surge in AI interest and how hype might be influencing the conversation. I found Richard Baldwin’s quote, “AI won’t take your job, it’s somebody using AI that will take your job,” to be thought-provoking. It made me wonder where we were starting off and what everyone’s perspective was on the matter.

Thibault: We had to start by addressing the elephant in the room: ChatGPT. The conference was called “Unfold” but may as well have been called “Unfold ChatGPT” because it was the buzzword no one could escape. And let’s be clear: it scared people. What the panel did well was this: it was established early that AI is not a replacement for humans, but an extension of them. That helped focus the group on key aspects, such as the importance of staying in touch with these developments closely, which is possible without being an expert in tech! What became clear is that this time right now is about the democratization of AI and about making an open audience understand rapid developments.

Jason: During the on-stage discussion, you inquired about the steps to avoid falling behind in the face of rapid development. At first, I thought, “There’s no checklist of actions to follow.” Instead, it’s all about the ongoing generation of ideas and actions within your team, fostering agility, and learning from those experiences. Staying ahead requires embracing a growth mindset, which involves continuous experimentation and perseverance. Along the way, goals may evolve, and that’s perfectly acceptable! It’s all part of the continuous learning journey, where the destination remains fluid.

Thibault: I believe you even mentioned the book ‘Mindset’ by Carol S. Dweck. Reading naturally fosters an open mind, and it goes hand in hand with attending conferences and being intentional about what influencers to follow, and newsletters to subscribe to. I think what the panel was telling everyone was to actively ask questions. And I would take that a step further: ask ChatGPT. Recently, I asked it for suggestions considering part of my job can be done by AI, and it responded with a list of five jobs that will not be disrupted.

Jason: It goes to show that the current change is about more than being adaptable as an industry, it’s about adaptable strategies. Players who can shift gears and communicate changes in strategy and goals rapidly and effectively throughout their business are much more likely to forge a winning path. The clear opportunity here is to use the tools of data science to influence your whole business in a powerful way. Do not stop at revenue management! Ideally, strategy drives decision-making. Decision-making drives actions. Those actions drive results. If you don’t see the results, it’s time to make adjustments on this path. And who makes those adjustments? You do. The human who excels at divergent thinking and integrating multiple narratives into their thinking. That includes the narrative supplied by machine learning and its econometric approach.

Thibault: Right, and human ideas and strategies are powered by AI. It’s used as a tool rather than a replacement. Artificial Intelligence collects data and makes sense of it, then shows what it thinks is the most important information. Any user can combine this with the trends and patterns they consider pertinent and act. It’s a comic book example but think of J.A.R.V.I.S. in Iron Man; AI is the assistant.

Jason: With the support of technology, we are empowered to combine our insights with those provided by AI. Even though machines possess vast amounts of data, we still have access to valuable information that they do not. This dynamic allows us to elevate the significance of our roles and makes our jobs even more crucial.

We did talk about what that meant for revenue management and how AI will specifically assist us there. I think I mentioned the old example of how accountants, arithmetic geniuses of their time, did not lose their jobs when spreadsheets completed calculations for them; they advanced the profession and dedicated their strengths to other parts of the process. Accountants use spreadsheets. Revenue Managers use AI.

Thibault: AI allows people to do more with less; for hotels and revenue management, that means going beyond managing rooms. Widely expected improvements that the group listed were enhanced forecasting, personalization, and automation. We know there are tools that offer pricing suggestions today that are not followed. So, I would like to explore how AI can become prescriptive. I’d say the answer is communication. Just like a GM asks a Revenue Manager “Why” and “What is included in this analysis”, AI cannot be a big black box. There has to be a sense that we understand or control the machine. That means AI has to make the process more transparent. How? Like any assistant: by explaining complex issues in simple terms. A system should not simply produce a suggestion, but communicate that “based on developments in x over the last 50 days, we suggest doing this.”

Jason: During the audience Q&A, the audience raised the question of whether AI would bring about Total Revenue Management universally. Let’s be honest, it’s a buzzword that everyone discusses, but nobody is actually implementing. Personally, I wish I had emphasized at the time that Total Profit Management is where support is truly needed. Unfortunately, profit tends to be solely measured against costs, and technology often gets unfairly labeled as a cost center. This kind of thinking can kill agility, growth, and the entire learning journey we just talked about. In an industry where infrastructure and information sharing still have room for improvement, technology should be a driving force for maximizing profits. The progress of both our learning and technology are intricately linked, and that’s something we must recognize.

Thibault: Yes, but look at it this way: there was a shift in focus from revenue to profitability during the pandemic, and, arguably, revenue is now back. I do agree that profitability is even more critical, but let’s see Total Revenue Management as a step in between. A focus on profitability is easier pursued by big brands, whereas Total Revenue Management, driven by AI, sounds like a way to entice those hotels that have never participated in revenue management, to do so now. This may be their way in, before they add on F&B and ancillary services, to eventually focus on profitability. I believe the way to accelerate a focus on profit is to make Total Revenue Management more accessible, supported by AI.

Another option would be for profitability to make a sudden comeback, as we are potentially on the verge of another financial crash. What will be AI’s impact then? The traditional practice is that owners and operators credit the market for its excellent performance, while during rough times, they blame their revenue management teams, rather than the marketplace. I hope that revenue managers who are empowered by AI will have a few things to say, find hidden data, and claim credit where they can.

Jason: I certainly agree and want to give credit where credit is due, Thibault. Thank you for leading the panel and agreeing to challenge my thoughts in this way!