Monetizing AI: "Picks and Shovels" or "Personalization"

“Monetization” of investments in artificial intelligence already are a top issue for CxOs who have to authorize the spending. 

So far, the early winners are suppliers of “picks and shovels” such as Nvidia, which supply infrastructure necessary to use AI. 

The tougher issue comes in areas where “personalization” based on “behavioral and data mining” come into play as the value drivers. And that is the likely monetization case for most firms and most people. 

Better “personalization” is likely the key upside for most applications, services and products. Consider the old adage about wasted advertising: “We know half our advertising is wasted; we just don’t know which half.”

As has been the case for data mining so far, so too will AI provide value in terms of surfacing customer behavior and demand in a more precise way. 

All of that assumes data privacy rules do not prevent this, of course, allowing a “social graph” to become something more like a “hyper-personalized” human context. Or call it an:

• Intelligent social graph

• AI-powered social graph

• Semantic social graph

• Contextual social graph

• Cognitive social graph

• Behavioral social graph

• Predictive social graph

The point is that AI extends the capabilities of existing social graphs as they are relevant for advertising, retailing, marketing and other existing operations supporting existing monetization models. 

A retailer could use AI to develop a personalized recommendation engine that suggests products to customers based on their social media interactions, purchase history, and the purchase history of their friends and connections. 

An advertiser could use AI to target ads to customers based on their social graphs and interests. For example, if a customer has recently liked a post about a new restaurant on social media, the advertiser could serve them an ad for that restaurant.

A social media platform could use AI to recommend new people to follow based on a user's interests and social connections.

A job search platform could use AI to match candidates with jobs based on their skills, experience, and social connections. For example, if a candidate has the skills and experience required for a job and their friends are connected to people who work at the company that is hiring for the job, the platform could recommend the job to the candidate.

For any marketing-related or ad-related expenditure on the part of a seller, or the fulfillment operations of a platform, the value will come in the form of an outbound marketing and selling value that has higher conversion rates, even if the services and products bought by the advertiser or marketer cost more. 

More-personalized capabilities will benefit retailers for similar reasons. Knowing the size and shape of any potential customer’s foot, their preferred indoor and outdoor activities, travel preferences and interests, where a person has traveled recently or regularly will allow retailers to more effectively sell footwear, socks and related gear, for example. 

For most CxOs, firms and people. AI will be something like a new adjective modifying an existing noun. New features and capabilities will be used to support existing processes. 

Eventually, some entirely novel use cases could develop, with new business models. It’s just hard to predict what they will be. 

For nearly-all practical purposes, firms will take advantage of their “picks and shovels” value or will apply AI to personalize existing operations in ways that support the existing business model. 

But in all these cases, firms will sell more of something they already supply. In a fewer number of cases the monetization will be quite direct (picks, shovels) but in most cases the benefit will be indirect (better personalization leads to higher sales volume or conversion rates).

Net Neutrality and "Fair Share" are Flatly Incompatible and Contradictory

One might argue that neither network neutrality nor “fair share” payments by a few hyperscale app providers make sense. 

Net neutrality is the principle that internet service providers (ISPs) should treat all data on the internet equally, regardless of the source, destination, or type of content.Without net neutrality, proponents argue, ISPs could block or slow down access to certain websites or services, or charge consumers higher fees for accessing certain content.

“Fair share” is the concept that a few popular app providers should pay telcos a fee for using their infrastructure. You see the contradiction. “Fair share,” by definition, treats bits differently and allows ISPs to charge fees to some sources. 

Note that the principles are mutually exclusive: treating all bits the same--irrespective of source--means no “fair share” payments are allowed. 

Beyond that, even when net neutrality rules are in place, ISPs are allowed to groom traffic during times of congestion. But net neutrality does not prevent ISPs from practicing traffic shaping or congestion control, which do not treat all bits equally. 

Also, keep in mind that ISPs and internet domains already compensate each other for asymmetrical traffic flows, in the form of  interconnection payments.

Critics might note that internet domains--including the targeted hyperscale firms--already pay such fees for traffic asymmetry, even ignoring the fact that it is ISP customers themselves who are asking the hyperscalers to send data to them. 

Hyperscale App Provider	ISP	Interconnection Payment
Netflix	Comcast	$1 billion
Netflix	Verizon	$750 million
Amazon Web Services	Comcast	$1.2 billion
Amazon Web Services	Verizon	$900 million
Microsoft Azure	Comcast	$1 billion
Microsoft Azure	Verizon	$750 million
Google Cloud	Comcast	$800 million
Google Cloud	Verizon	$600 million
Microsoft Azure	AT&T	$75 million per year
Alphabet	Charter	$100 million per year
Amazon	AT&T	$150 million per year
Microsoft	Charter	$75 million per year
Google	AT&T	$125 million per year
Meta	Charter	$50 million per year
Meta	AT&T	$75 million per year
Alphabet	China Telecom	$150 million per year
Amazon	NTT	$125 million per year
Microsoft	Deutsche Telekom	$100 million per year
Google	Telefónica	$75 million per year
Meta	Singtel	$50 million per year
Meta	Orange	$75 million per year

Some might argue that “fair share” essentially is an effort to recreate the old closed network, where every app on the network had to be approved by the access service provider.

6G Should "Enable," Not "Create" New Apps and Use Cases

After our experiences with 3G, 4G and now 5G, perhaps we ought to be more circumspect about all the positively amazing new experiences that will actually develop when we get to 6G. 

Already, observers offer examples of new applications and services that could be enabled by 6G:

• Real-time holographic video conferencing

• Augmented reality experiences

• Self-driving cars

• Remote surgery

• Mobile broadband in rural areas

• IoT connectivity in dense urban environments

None of that will startle: those were raised as apps that could be supported by 5G, and might yet emerge. 

And more to the point, despite the expected improvements in latency performance and bandwidth, maybe we should be cautious about claiming too much for the ways artificial intelligence or virtual reality will be embedded into the core network. 

No doubt AI will be used to support the core network and its processes. But that’s different from possible efforts to embed AI or AR or VR as customer-facing features of the networks, as some might propose. 

Beyond making the network operate as efficiently as possible, offering the best latency performance and bandwidth support we can reasonably develop in the next generation of networks, we might remain skeptical of efforts to claim or support network features that go beyond making the network as liquid as possible; as dynamic as possible; as flexible as possible. 

An energy-efficient network, using an on-demand architecture featuring low latency capabilities and no restrictions on bandwidth, using virtual mechanisms, is a reasonable goal. 

Beyond that, what we probably still need is a permissionless development environment, where app software does not have to assume much other than the existence of the low-latency, high-bandwidth connectivity. 

In other words, perhaps all we want is a network that is as open as possible, as virtualized as possible, as flexible and dynamic as possible, capable of supporting any conceivable application but without embedding any of that inside the core network. 

But some will try to create capabilities that are embedded into the core network, no doubt. That’s one way of attempting to profit from apps using the network.

Will 6G Try to Recreate Closed Networks?

Already, some are suggesting 6G will be different from 5G in a significant way: where 5G is still a connectivity mechanism, some tout 6G as a computing mechanism. It will “enable immersive, ubiquitous, and sensory digital experiences on a massive scale,” some argue. 

“Enable,” yes, in the same way that home broadband “enables” use of internet-delivered applications.  “Embed,” in the sense of the network itself being the supplier of the features, probably not, and for good reasons. 

Modern computing is based on layers. That is what allows us to innovate faster and avoid monolithic solutions because functions are compartmentalized; independent objects rather than integrated processes. 

Even if infrastructure suppliers want us to accept new forms of functions integration as a way of convincing us to buy their new platforms, we should resist the notion. We actually do want permissionless app creation, not “integrated” solutions. 

In other words, some are likely to argue for 6G standards that are more centralized and controlled than 5G networks. More “closed,” in other words. 

Some will argue this is necessary because 6G will need to support a wider range of complex and demanding applications, such as immersive virtual reality and real-time AI-powered services. 

We might want to resist that notion. It is a move in the direction of walled gardens, closed networks and app development controlled, to a larger extent, by the entities providing internet access. 

Is that going to be better? 

Some will argue for advantages such as enhanced security or privacy. But permissionless development enabled by the layered architecture  has worked well. It’s easy to see why some in the value chain would prefer more closed, centralized networks. 

It recreates the experience of the public switched telephone network, where telcos controlled “all” the apps running on the network. 

To use the network, you needed permission from the network operator. Is that going to be better?

Every mobile generation gets hyped. Each will, it is said, enable and revolutionize the experience. Improvements happen, yes. Latency is reduced; bandwidth is increased; energy efficiency gets better. 

6G should “enable” immersive experiences such as the metaverse by staying out of the way. Embedding such features into the fabric of the network--beyond measures to control latency and supply lots of bandwidth--will be a mistake.

C-Band is a Huge Deal for Verizon: Extends Home Broadband Addressable Market from 25% to Virtually 100%

One iron rule for internet access services is that if one has enough bandwidth, access speeds can be very high. For mobile operators, bandwidth expansion can come in a few ways: adding more spectrum, building smaller cells or deploying better modulation techniques or radios.

In that regard, for 5G, mid-band spectrum has been key for firms such as Verizon, which have had less mid-band spectrum than others. The difference is striking. 

After deploying C-band spectrum, Verizon mobile peak speeds “go from 9 Mbps to an amazing 2.4 gigabits per second,” said Hans Vestberg, Verizon CEO.

That has implications for home broadband as well, as, in principle, peak speeds might reach gigabit per second levels. And that, in turn, is important because it dramatically extends the addressable market for fixed wireless from perhaps 25 percent of buyers to perhaps 99 percent of buyers (those who buy home broadband at speeds up to about 2 Gbps, and do not require symmetrical access)

True, Verizon has millimeter wave assets to deploy in urban areas, but C-band means fixed wireless has higher bandwidth in suburban and rural areas as well. 

For Verizon, which has a smaller fixed network footprint than many of its leading competitors, that really does matter, as it means Verizon can compete for home broadband customers who want higher speeds in most U.S. geographic areas. 

Of a total of 140 million U.S.  homes, AT&T’s landline network passes 62 million. Comcast has (can actually sell service to) about 57 million homes passed.

The Charter Communications network passes about 50 million homes, the number of potential customer locations it can sell to.

The number of Verizon homes passed might be 27 million. Lumen Technologies never reports its homes-passed figures, but likely has 20-million or so consumer locations.

The point is that Verizon cannot easily expand its fiber to home footprint outside its historic service areas, for reasons of investment magnitude. So fixed wireless makes eminent sense for a firm that can presently reach only about 19 percent of U.S. homes using its fixed network. 

The same sort of logic holds for T-Mobile, which historically has had zero access network fixed network footprint. There is neither time nor money for T-Mobile to wire the entire country, or even a substantial part of it, using FTTH. 

So C-band is a really big deal. It extends Verizon’s home broadband addressable market from about 25 percent of homes to up to 100-percent of homes.

The Purpose of Deregulation is to Cause Leaders to Lost Market Share

The functional purpose of any industry deregulation is to cause incumbents to lose market share. The functional purpose of new regulation often is to restrict market share held by market leaders, eventually causing share loss for the leaders. As regulators examine markets led by hyperscale app providers, that is going to be a relevant issue.

That is precisely what has happened in the connectivity business. That will be the case for possible regulatory restrictions placed on hyperscale app providers, as was true for connectivity providers.

Consider services purchased by enterprises. 

Though Verizon, AT&T and Comcast stand atop the market share ranking for sales of connectivity services to U.S. enterprises, about 40 percent is shared by a number of other providers. 

Company	Percentage
Verizon	25%
AT&T	20%
Comcast	15%
Other specialized connectivity service providers	40%

Among them are: 

• Lumen Technologies

• Cogent Communications

• Windstream

• Zayo Group

• Equinix

• Digital Realty

• Telehouse

• NTT Communications

• GTT Communications

• Tata Communications

To be sure, U.S. enterprise spending on information technology services and products has grown steadily since 2000, according to IDC estimates. The issue is market share, as many new competitors have entered the market. 

Year	Services	Products	Total
2000	242.0	295.0	537.0
2001	234.0	275.0	509.0
2002	227.0	250.0	477.0
2003	220.0	225.0	445.0
2004	213.0	200.0	413.0
2005	206.0	175.0	381.0
2006	200.0	150.0	350.0
2007	206.0	175.0	381.0
2008	212.0	200.0	412.0
2009	218.0	225.0	443.0
2010	224.0	250.0	474.0
2011	230.0	275.0	505.0
2012	236.0	300.0	536.0
2013	242.0	325.0	567.0
2014	248.0	350.0	598.0
2015	254.0	375.0	629.0
2016	260.0	400.0	660.0
2017	266.0	425.0	691.0
2018	272.0	450.0	722.0
2019	278.0	475.0	753.0
2020	284.0	500.0	784.0
2021	290.0	525.0	815.0
2022	296.0	550.0	846.0
2023	302.0	575.0	877.0