Mobile executives these days are talking about ways to monetize artificial intelligence beyond using AI to streamline internal operations. Generally speaking, these fall into three buckets:
Personalizing existing services to drive higher revenue, acquisition and retention (quality of service tiers of service, for example)
Creating enterprise or business services (private 5G networks with AI-optimized performance,, for example)
AI edge computing services for autonomous vehicles, for example
Obviously, those are AI-enhanced extensions of ideas already in currency. But some of us might be quite skeptical that such “AI services” owned by telcos will get much traction. History suggests the difficulty of doing so. How many “at scale” new products beyond voice have telcos managed to create? Text messaging comes to mind. Mobile phone service also was a big success. So is home broadband.
All those share a common characteristic: they are network services owned directly by the service providers. Generally speaking, other application efforts have not scaled well.
Mobile service providers have been hoping and proclaiming such new revenue opportunities since at least the time of 3G. But many observers might agree there has been a disconnect between the technical leaps (faster speeds, lower latency, better efficiency) and the ability to turn those into new revenue streams beyond the basic "sell more data" model.
That is not to say that service providers have had no other ways to add value. Bundling devices, content and other measures have helped increase perceived value beyond the core network features.
But the core network as a driver of new products and revenue is challenging for a few reasons.
Open networks mostly have replaced closed networks (IP versus PSTN)
Applications are logically separate from network transport (layers)
Permissionless app development is the norm (internet is the assumed network transport)
Vertical control of the value replaced by horizontal functions (telcos had full-stack control of voice, but only horizontal transport functions for IP-based apps)
As I have argued in the past, modern telcos have a hybrid revenue model. They are full-stack “service” providers for voice and text messaging. But they are horizontal transport providers for most IP apps and services, and sometimes are app providers (owned entertainment video services, for example).
The point is that most new apps and revenue cases can be built by third parties without telco or mobile operator permission, which also takes transport providers out of the direct revenue chain.
So I’d argue there is a structural reason why telcos and mobile service providers do not directly benefit from most of the innovation that happens with apps. Think about all the customer engagement with internet-delivered apps and services, compared to service provider voice and messaging.
In their role as voice and text messaging providers, telcos are “service providers” (they own and control the full stack). For the rest of their business, they are transport or access providers (capacity or internet access such as home broadband), a horizontal value and revenue stream. ISPs get paid to provide “internet access,” not the actual end user apps.
And that has proven a business challenge for now-obvious reasons. Once upon a time, voice services were partly flat-rate and partly usage-based. In other words, telcos earned money by charging a flat fee for access to the network, and then variable usage based on number, length or distance of voice calls.
In other words, greater usage meant greater revenue. But flat-rate voice and texting usage subverts the business model, as most of the revenue-generating services become usage-insensitive. That is the real revolution or disruption for voice and texting.
In their roles as internet access providers, some efforts have been made to sustain usage-based pricing. Customers can buy “buckets of usage” where there is some relationship between revenue and usage.
Likewise, fixed network providers have used “speed-based” tiers of service, where higher speeds carry higher prices. Still, those are largely flat-rate approaches to packaging and pricing. And the long-term issue with flat-rate pricing is that it complicates investment, as potential usage of the network is capped but usage is not.
So as much as ISPs hate the notion that they are “dumb pipes,” that is precisely what home or business broadband access is. So internet access take rates, subscription volumes and prices are going to drive overall business results, not text messaging, voice or IoT revenues.
To be sure, we can say that 5G is the first mobile generation that was specifically designed to support internet of things applications, devices and use cases. But that only means the capability to act as a platform for open development and ownership of IoT apps, services and value. And even if some mobile service providers have created app businesses such as auto-related services, that remains a small revenue stream for mobile service providers.
Recall that IoT services are primarily driven by enterprises and businesses, not consumers. Also, the bulk of enterprise IoT revenue arguably comes from wholesale access connections made available to third-party app or service providers, and does not represent telco-owned apps and services (full stack rather than “access services”).
Optimistic estimates of telco enterprise IoT revenues might range up to 18 percent, in some cases, though most would consider those ranges too high.
Though automotive IoT revenues (again mostly driven by access services) arguably are higher for the largest service providers, their contribution to total business revenues is arguably close to three percent or so, and so arguably contributing no more than 1.5 percent of total revenues, as consumer services range from 44 percent to 65 percent of total mobile service provider revenues.
The point is that the ability to monetize AI beyond its use for internal automation is likely limited. Changes in the main revenue drivers (consumer and business mobile phone subscriptions and prices) are going to have more impact on revenue and profit outcomes than IoT as a category or automotive IoT in particular.
