Context
For AI Strategy Lab project in Information Strategy course, my group decided to build a prototype of an Agentic AI-based dashboard to provide recovery package recommendations for airline staff which then communicated to passengers through their mobile application to tackle the problem of sudden peaks in passenger recovery-demand while airline staff capacity cannot scale at the same rate. This problem was chosen based on the experience that my groupmates experienced flight disruption when they were travelling that they were faced with long queues, uncertainties, and stress. We reflected that this is a relatable topic and there is a possibility to implement AI in order to alleviate the pressure of airline staff during disruption management activities.
Reflection
Tasks were divided within the team based on preferences and education backgrounds, with my groupmates with stronger technical backgrounds were in charge more of the technical side. I was responsible for developing the problem and opportunity components, and the competitive and ecosystem analysis as well. As the decision is to build an Agentic AI-based dashboard to improve an internal process within an airline company, several questions were raised in accordance with implementing learned frameworks and concepts from the lectures. For instance, we were unsure how to implement monetization, in terms of pricing, subsidies, and network effects since we had decided to implement this Agentic AI-based dashboard as an internal process improvement. However, the IS team has been helpful throughout the project journey too that they provide valuable feedback. Based on the feedback we received, it gave us clarity and guidance that helped us figure things out and continue with our project journey. For instance, we received feedback regarding monetization that it did not need to always be about pricing and subsidy, and we were able to realize the monetization through outcomes such as resolution time or avoided operational costs instead of solely focusing on identifying a pricing or subsidy mechanism, which did not apply to our case since it is not a platform. This reminds me that not each business model concept applies in the same way for every case.
Throughout the project journey it was clear that a lot of considerations and critical thinking are needed rather than carelessly slapping the title AI and hoping that it will magically automate a process and that it will solve every problem there is and create an optimal sustainable value. Being responsible for the two components of the project, made me realize that AI itself does not necessarily create a sustainable competitive advantage. AI is an accessible technology that other companies, even other than the airline companies themselves, are able to access and make use of it to compete with each other. The differentiator is how an organization will apply AI to address a meaningful organizational problem and also combining it with their unique organizational resources and capabilities. For instance, in our case, my focus shifted from only considering the Agentic AI technology, itself, considering the airline’s resources like its partner networks, existing system and data history, and workflows, as well. By doing this, it will create an AI strategy that is strategically valuable and sustainable. This taught me that competitive advantage comes from the combination of technology and how well the technology is integrated within an organization’s existing capabilities.
Overall, our group dynamic worked well. Each person was responsible for their own parts, and we were always open to brainstorming and having discussions when there is a doubt or issue someone is facing in completing their parts. We also made sure to critically challenge each other’s work and ensure comprehension and alignment of our work, so that our project is solid and cohesive. Although everyone has their own schedule and pace in working the assignments, we managed to take responsibility of our parts and supported each other in completing this project. Flexibility, communication, and teamwork are the key skills here that really brought things together.
As the person who has more business and finance background, my understanding of AI and business strategy has been enhanced and becomes more whole. From the business side, I have a higher level of understanding and a more comprehensive view like how value is created, captured, delivered and understanding how to strategically defend our solution. Meanwhile, the technical aspects were new and uncomfortable to me, and it was interesting to do this project because it gave me the opportunity to be exposed to not only considering how it would visually look like but also what are the technical considerations that goes behind it. For instance, things like testing prototypes with simulations and assumptions, governance and risk analysis on the AI part, and future market test which turned out to be connected to the defensibility, are new to me. The opportunity was also a not so intimidating one because I have my groupmates that could also explain and gave me their opinions from their experiences. In other words, I did not have to dive in cluelessly but rather gently with the help of my groupmates. This project has provided me opportunities to learn and consider a proposition from many different perspectives and challenged me to be critical not only on the business side and the financial feasibility but also from the technological side, which I have not experienced or even thought of before this project.
In a Nutshell
All in all, although the timeline for this project was quite tight, I rather enjoyed the journey. Looking back on my experience, I gained valuable knowledge in terms of theoretical concepts and frameworks, as well as practical experience in applying them directly to our group project.
