From Boardrooms to Bus Terminals
A Lesson in Practical AI.
Moving AI from a boardroom slide to a bus terminal is harder than it looks. We often talk about artificial intelligence in grand, abstract terms, but for the average person, those high-level discussions do not mean much when they are just trying to get home for the holidays.
I recently led a project at UIB where we partnered with Park May Berhad to launch Malaysia’s first WhatsApp-based booking platform for Transnasional and Plusliner bus tickets. It sounds simple on the surface, but the journey to making it “simple” for the user taught us a lot about what it actually takes to bring meaningful AI solutions to the real world.
Here is a pragmatic look at the hurdles of practical AI and how we navigate them.
Stop building apps nobody wants
The first hurdle is ego. Many companies want to build their own “destination” app, hoping users will download it, register, and keep it on their home screen. The reality is that people already have app fatigue. They do not want another login to remember or another 100MB of storage taken up for a task they do once a month.
Our approach was to meet people where they already are: WhatsApp. By sending a simple “Hi” to a specific number, a traveler can search for routes, check seats, and buy a ticket. This is not about being “high-tech” for the sake of it. It is about being useful.
If your AI requires a user to change their behavior significantly, you have already lost.
The messiness of the “Last Mile”
Real-world AI is never as clean as a demo. To make the bus booking system work, we had to integrate conversational AI with legacy backend systems, real-time seat inventories, and secure payment gateways.
This is where many AI projects fail. It is easy to build a chatbot that answers “What time is the next bus?” It is incredibly difficult to build a system that securely processes a credit card payment, generates a boarding pass, and updates a database in real-time within a messaging interface.
Practical AI is 20 percent “intelligence” and 80 percent robust engineering and integration.
The “Grandmother Test” for inclusion
If an AI solution only works for the tech-savvy, it is not a success; it is a niche. For a national transport operator like Transnasional, the demographic is everyone. We had to ensure that a student, a business traveler, and a grandmother could all navigate the same interface with the same level of ease.
By using conversational AI, we removed the friction of complex menus and forms. You just talk to the service. This inclusivity is what drives digital adoption.
When we make AI human, we make it accessible to people who might otherwise be left behind by the digital divide.
Lessons from the field
If you are looking to bring a practical AI solution to market, my advice is to ignore the hype and focus on the friction.
Find the one task that is most annoying for your customer.
Identify the platform they already use every day.
Build the bridge between the two.
As we are moving away from an era of “using” AI to an era of “simply communicating” with the world around us, AI should not feel like a new tool you have to learn. It should feel like the tool you already have just got a whole lot smarter.
About the Author
Muzzamel Mazidee is the General Manager and Director at UIB Malaysia for UIB.ai and a leading expert in conversational AI and digital transformation. He specializes in bridging the gap between complex technology and everyday human needs, helping global brands realize the power of AI at scale.
About UIB
UIB is an API-first company that allows businesses to connect with their customers via the most popular messaging and AI platforms through a single API. Our tagline, “Simply Communicate,” reflects our mission to make human-to-machine communications as natural as human-to-human interaction.
To explore how Muzzamel and the UIB team can help your business realize practical AI solutions, feel free to email them at info@uib.ai or simply send them a WhatsApp message.
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