Sunday, February 25, 2024

Does AI Create a New Rationale for "Smartphone as a Service?"

How far are we away from "smartphone as a service," where the cost of the device, plus mobile service plus AI is a single bundle with a recurring cost?


“Artificial intelligence” smartphones are likely to pose issues--or create opportunities--related to processing tasks and memory on devices; use of edge computing or cloud computing resources. That, in turn, might create an opening for different ways of envisioning device and service business models.


Regarding on-board resources, on-board machine learning models might require more on-device memory.  to load up even before we get to running them, although the availability of compressed models surely is coming. 


Processing also will be an issue. Running an ML model arguably requires more unique arithmetic logic blocks than your typical CPU, so specialized processors are likely necessary.


Smartphone processing likely will continue to be constrained by power consumption and heat generation limits, as well, so there will be some limits on on-board processing power. 


Leveraging cloud or edge computing obviously is a potential solution. Processing of some tasks--such as real-time language translation; camera features and voice-to-text will continue to make sense as an “on-board processing” capability. 


Other features might continue to make sense as an “edge- or cloud-supported” capability. 


The issues are that this could reshape needs for end-user data plan features and higher-speed, latency-bounded networks. Roaming costs also are an issue. 


So even if on-board processing is, in principle, ideal, it might not be practical for all devices (mid-range and low-end devices, for example). And heat and processor cost issues must be considered as well. 


As a marketing issue, “subscription phones and service” might need a rethink. To some extent, consumers often take advantage of subsidized phone offers from their service providers. So a service plan with a two-year contract that includes the cost of the device in the recurring cost already is a form of “phone as a service.”


Subscription plans for advanced AI service (Google’s Gemini or Microsoft’s Copilot) already exist. So we might see a rethink of possible product bundles that include, on a subscription basis, the device, the AI capabilities (on-board plus cloud or edge) and the recurring service plan costs. 


Creating such bundles should be easier for consumers to understand once we develop more valuable AI-enhanced apps and features usable on smartphones. People might expect AI features such as camera performance or image editing and translation services to be “bundled” with the device. 


But, eventually, some compelling additional use cases could--and should--develop that require an AI service plan that relies on cloud and edge computing, faster connections and more data allowances. So think of a 5G service plan using mid-band spectrum (for speed); unlimited data usage (so the external cloud and edge processing can be used) plus “AI device” supplied on a subscription basis, with a “new” device supplied every two or three years. 


Aside from all the practical details of figuring out the service provider’s cost to do so, we still need some new “killer apps” that make the purchase of an AI service plan such as Gemini or Copilot a reasonable and necessary investment by the consumer. 


As a business problem, this is a “logical bundle” issue. What features (device, AI, recurring service cost, features and apps) will make sense for many customers when all of those features are a subscription, not just the mobile service plan and the AI? 


Right now, it is not so clear what the new killer value requiring AI--and therefore a more-powerful device plus remote processing--is the trigger. Still, once one or a few such use cases do develop, with high customer interest, it will be easier to conceive of, and sell, new bundles of device, AI and service, for one recurring monthly price.


Saturday, February 24, 2024

How Much Opex, Capex Could Mobile Operators Cut?

Most connectivity service providers have programs in place to reduce capital expenditures and operating costs, where feasible. Mobile operators face continuing need to invest in spectrum resources as well as network platforms about every decade, so capex requirements will remain elevated.


Fixed network service providers will, in some cases, be able to better control network capex if they are far down the path of converting their access networks to optical fiber or other high-bandwidth access methods. 


Vodafone plans to cut €1 billion in costs by 2026 through various initiatives. For its part, América Móvil achieved $2.1 billion in cost savings in 2022.


The TM Forum predicts that telcos will achieve 20-percent to 30-percent cost savings by 2025 through intelligent automation and cloud adoption.


Arthur D. Little estimates that network sharing can generate cost reductions of up to 20 percent for the participating operators.


Company

Year

Opex/Rev (%)

Capex/Rev (%)

Verizon

2019

76.5

14.0


2020

75.2

15.6


2021

74.1

14.6


2022

73.5

14.2


2023 (est.)

72.8

13.8

AT&T

2019

74.8

15.6


2020

78.0

14.9


2021

75.4

15.2


2022

74.0

14.4


2023 (est.)

73.2

13.9

NTT

2019

78.2

10.3


2020

77.8

10.8


2021

77.0

11.2


2022

76.5

10.9


2023 (est.)

76.0

10.7

Vodafone

2019

72.3

14.7


2020

73.2

13.8


2021

72.8

14.2


2022

72.0

13.5


2023 (est.)

71.5

13.0


Many have significant hopes that artificial intelligence will help by supporting automated fault detection, self-healing networks, and dynamic power management, for example.


Migrating to cloud infrastructure and virtualization processes reduces some amount of physical infrastructure. Verizon, for instance, aims to have over 20,000 virtual RAN cell sites by 2025.


Infrastructure sharing likewise has been an effective tool for reducing radio access costs for mobile operators, in some markets. 


But opex remains the big potential cost target, as a percentage of revenue. 


Provider

2020 Opex/Rev

2021 Opex/Rev

2022 Opex/Rev

2023 YTD Opex/Rev





Verizon

71.8%

71.1%

70.0%

68.9%





AT&T

70.9%

70.3%

70.4%

69.0%





NTT

50.4%

49.6%

48.9%

48.6%





Vodafone

66.4%

65.2%

64.4%

63.5%






"Cloud Computing as a Service" Revenue Earned by Azure, Google Cloud, AWS s Hard to Compare

For many observers, it might not matter what components are counted as “cloud computing” revenues earned by Amazon Web Services and Azure Intelligent Cloud or Google Cloud. Revenue is revenue, some will maintain. 


For some, it might well matter what components are contained in each firm’s reported revenues, as Microsoft, for example, includes lots of end-user applications revenue within its reported Azure Cloud category. 


Keep in mind that reported Azure “cloud” revenue includes applications such as LinkedIn, Office, and other enterprise or consumer apps related to gaming, for example. The other competitors earn revenues mostly or exclusively from  "computing as a service" sales. 


Gartner, for example, estimates that in 2021, software-as-a-service (end user apps) represented 25-percent to 30-percent of global cloud infrastructure and platform services (IaaS and PaaS) spending. 


So some analysts speculate that the contribution of applications like Office and Dynamics 365 to Azure Intelligent Cloud revenue could be as high as 30-percent to 40-percent of total “cloud computing” revenues.


Provider

Market Share (%)

Cloud Computing Revenue $ Billion

Revenue Growth YoY (%)

Amazon Web Services (AWS)

33.1%

81.0

29%

Microsoft Azure

22.5%

50.1

35%

Google Cloud Platform (GCP)

10.1%

23.0

41%

Alibaba Cloud

7.5%

17.2

40%

Tencent Cloud

5.1%

11.6

48%

Other Providers

21.8%

49.9

38%


If so, then “apples to apples” comparisons of cloud computing revenues, excluding retail applications revenue, would have Azure remaining the second-biggest provider, but with a lead over Google that is not as large as generally believed. 


Azure core cloud computing (infrastructure and platform) might be in the range of $30 billion to $35 billion, for example.


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