GO-Mobility

What if the future were MaaF?

#TalkWithGO: interview with Matteo Antoniola

In the world of transportation, the acronym “MaaS” has become a buzzword used by experts, transportation operators, and administrations. But what are its concrete applications, and where can they take us? We discussed this with Matteo Antoniola, Business Strategy Manager at 5T and one of Italy’s leading experts on MaaS. We wanted to explore the state of health of MaaS with him and explore the synergies of this sector with generative AI. But what are its concrete applications, and where can they take us?

In this article, we provide a clear and candid overview of Mobility as a Service and its possible developments, starting with the new concept of MaaF. The conversation is part of the #TalkWithGO column, dedicated to sharing experiences and knowledge to overcome common challenges in the field of connections between sustainable mobility and artificial intelligence.

Data is important, but what do we do with it?

In the mobility sector, as in many other sectors, there has been heated debate and awareness surrounding data. But what is missing is a systematic approach: everyone talks about data, but who is responsible for giving direction to all this information? Antoniola starts with a provocation: “Right now, there is a frenzy around data: the priority is to collect data, make it accessible, and standardize it. All this, however, without necessarily understanding what it is, and above all, for what purpose. Instead, it would be important to talk more about what to do with all this data: especially those who have to govern mobility dynamics.”

Right now, MaaS is a sector driven by industry, and therefore by the need to do business. The data is collected by different entities with different interests and objectives. But who is thinking about what to actually do with this data, as a public urban service project?

MaaS should not be reduced to a mere technological enabler for booking services. Antoniola continues: “To think about services, you need to know the demand. To know the demand, you need to know and profile behaviors and preferences. This is a type of data that transport operators are currently only able to use to a limited extent, because it is not yet part of their usual practice. Nor is it part of that of the public administration.”

The state of health of MaaS

As Antoniola confirms, there is now more awareness of and information about MaaS than there was a few years ago, when it was beginning to be talked about widely but with little knowledge. “Now that the market has begun to develop, the issue is starting to be approached more seriously by the public sector as well. The MaaS4Italy program, the first attempt to accompany the MaaS transformation with public direction, has certainly played a role in this.” According to Antoniola, this experiment has highlighted the difficulties, but it has also helped to break the deadlock and develop new MaaS operators. These are intermediaries, aggregators, and resellers of third-party mobility services such as UnipolMove City, ACI Sara GO!, and WeTaxi, which have joined the existing ones (MooneyGo, Urbi, Tabnet, and others).

However, to date, MaaS is still something for the few: “No operator has reached significant critical mass in terms of registered users, active users, or trips actually purchased and used through aggregation platforms.” Even outside Italy, the situation is no better: “Even in Berlin, the famous aggregation app Jelbi, produced by the public transport service, manages to bring volumes to a maximum of around 5%.”

This 5% actually reflects the average share of intermodal trips recorded in the analyses produced by GO-Mobility. It can therefore be inferred that MaaS currently appeals to that segment of the population that is already accustomed to traveling using a combination of means of transport. This segment has always represented a modest percentage, surpassed by a majority that mostly travels according to a less complex ‘point-to-point’ mono-modality. This habit is also widespread due to a national transport network that has never been redesigned with intermodality in mind, with overlaps between rail and road lines or between lines themselves.

Antoniola’s explanation for the difficulty of the MaaS service to take off is that the time is not yet ripe: not so much because of a lack of data or technological resources, but because of the users. “The necessary volumes are not being reached, partly because the service is not yet well known and understood, and partly because we are talking about something that will have volumes in ten or twenty years’ time: the MaaS target is more twenty-somethings than fifty-somethings. We cannot change the mindset of the latter to understand the value and convenience of these solutions, but we can change that of twenty-somethings.”

To date, therefore, it is important to work on confirmations: offering this intermodal user base the opportunity to continue their habits in an easier and more immediate way, possibly providing additional services. Meanwhile, for a more radical and widespread change in behavior, it will be necessary to capture the new generations, especially in cities: “In rural areas, it is understandable that car ownership and use remain predominant, but in cities we can no longer afford not to have alternatives. Changing habits, however, is a long process: if we now aim to remove the third car in the family, in ten years’ time we can hope to remove the second car, and so on. But we need to work on the twenty-somethings, who are tomorrow’s workforce and will hopefully make different choices from most of today’s 40-50-year-olds.”

This is therefore a process that may take longer than expected, and it is important to understand if and how long market operators are willing to wait. And this brings us to the title of this article: MaaF!

What is MaaF?

It is a new take on the concept of Mobility as a Service, where critical mass is achieved through the introduction of mobility as an additional component of existing apps and platforms that already have millions of users: Mobility as a Feature. A practical example would be notifying users of an event via Instagram, and if they are interested, they can buy tickets for the event and public transport directly in the app. Antoniola says: “The model on which the MaaS operator is based must bring together all mobility operators and seek 100-200 thousand users… it is likely to gradually decline. Because they will in turn be resold by Instagram, TikTok, Amazon, and so on. Mobility can become an additional feature of other applications that already have millions of users.”

This is a scheme that currently only exists in theory, but it would overcome the complexity and fragmentation that characterizes MaaS today. It is a reversal of the current usage model: it is not the user who has to open a specific app to find mobility options, but the app itself that, while you organize your work, errands, or leisure activities, suggests ways to get around and books and purchases your trips. “In the United States, Uber already does something similar: it syncs with your Google Calendar and reminds you of your appointments, offering to book a ride. Or Uber itself suggests events: ‘There’s a game at the stadium tomorrow, are you interested? Book an Uber.’ And this is already MaaF: a platform that also offers entertainment services, integrating mobility options.”

AI & MaaS

At this point, the main theme of our #TalkWithGO column comes into play: how important is artificial intelligence in enabling all these processes? It is easy to imagine that MaaF will necessarily have to be based on algorithms that profile our habits, needs, and preferences in order to suggest activities and modes of transportation. But today, what is the relationship between AI and MaaS in its current form, and how will it evolve?

Antoniola replies that, considering the current state of development of the MaaS industry, the role of AI is still marginal. Or at least, it is too early for it to have a significant impact: the priority at the moment is to make it work: aggregate services to produce value that captures the user’s interest, and improve the user experience, which can still evolve. “For AI to play a truly significant role, with advanced applications, investments would be needed that would perhaps only be possible if and when MaaS is integrated into larger platforms, the giants: just think of Google Assistant, Alexa, and Siri. It will probably be through them that we will book and purchase our mobility services, not through individual local operators. It will be the latter who will enter into contracts with the large platforms.”

Where AI can help us today is in customer care: limited implementations that help optimize and automate certain first-level practices, within the reach of current MaaS operators. One example, already mentioned in this article, is NIC-O, the first chatbot based on generative AI and designed to help citizens navigate the local public transport company’s website.

But how are relations between the public sector and private operators regulated in these processes?

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