Will Telecom AI Grow Over Next 5 Years?

Though connectivity providers have been slow to adopt artificial intelligence, that is expected by some to change dramatically over the next five to 10 years. 

source: Omdia 

Mobile operators seem to have moved earlier to adopt artificial intelligence than fixed network operators. At least, that is what STL Partners discovered in May 2019. Telcos that had incorporated at least some AI often used it to optimize existing network operations. 

Beyond that, some used AI for network planning and optimization, human resources, accounting and fraud-management. Some also use AI for cybersecurity and predictive analytics. 

AI also has been used for sales and marketing and customer experience (fault resolution, churn management) as well as supporting chatbots and virtual assistants. 

Singtel’s DataSpark provides access to GPS and mobile network data that other organizations can incorporate into their applications and services. 

AI is almost certain to be employed to help maintain profit margins as global revenue growth remains slow for the foreseeable future. 

source: GSMA Intelligence 

Is IT Productivity Slowing?

Industry disruption now has a familiar pattern. It starts with a cheaper, simpler version of a familiar product, which has some structural advantage. The product improves cumulatively, until the traditional industry can no longer compete. 

This illustration from Consensys shows value added in the financial services sector, compared to some more “physical” industry verticals. The broader point is simply that, by some accounts, either cloud computing or artificial intelligence are the forces leading productivity change.  

source: Consensys 

Technology optimists and pessimists tend to wage an unending war about the value of technology improvements. Some believe we are reaching an era of limits, such as the end of Moore’s Law, while others believe we will simply find other ways to keep pushing ahead. 

Optimists might counter that productivity now is shaped by software or cloud computing, not hardware.

This visualization by Deloitte shows the percentage of top 500 technology firms in Deloitte’s Fast 500 index. About 78 percent of the firms are in either the software or “digital” categories. About 10 percent of firms are in the hardware, devices or networking categories. 

source: Deloitte 

Nor is that an especially new trend. In consumer computing markets, new hardware has not propelled innovation advances as much as new cloud-based software and applications, for example. A study by Logic Monitor found that 74 percent of information technology executives in the United States, Canada, United Kingdom, Australia and New Zealand expect 95 percent of all software to be run in the cloud within five years. 

source: Logic Monitor 

The point is that pessimists might tend to see hardware limitations as negatively affecting rates of productivity growth. Those who see software, artificial intelligence or cloud as the drivers might tend to be optimists.

Study Shows Managers, Workers Believe Remote Work is Less Productive

A study of remote work at the Research Institute of Economy, Trade and Industry suggests workers and managers do not believe remote work is as productive as many claim. Keep in mind this is a survey of attitudes, not an attempt to directly measure some proxy for actual output. 

The productivity of remote work can improve over time, the researcher expects. Of course, much depends on the type of work. 

Some jobs simply cannot be conducted remotely, such as service jobs requiring physical contact with customers, often including doctors, nurses, hairdressers, and restaurant waiting staff.

Most work conducted by “information” workers in offices are easiest to do remotely, one might argue. The REETTI study suggests that the jobs of managers of knowledge workers might be far harder to do on a remote basis. 

Research Institute of Economy, Trade and Industry 

The study suggests four main classes of issues impairing higher productivity. Many people said the user friendliness of software and hardware for remote access was an issue. But Masayuki Morikawa, Research Institute of Economy, Trade and Industry, believes that is an issue which is resolved over time as workers become more experienced. 

Some tasks, conducted in the office, sometimes for security reasons, were hard to replicate in a remote context. 

Some people “emphasized the loss of the valuable, quick communication that is only possible through face-to-face interactions with their colleagues,” he said. 

Finally, a poor working environment at home, particularly the lack of a private room specifically designed for work, was reported as a serious constraint by many respondents. 

User experience and better remote location security and communications might be easier to fix. Home working environments will be much tougher to improve, as will the loss of face-to-face interactions. 

Will AI Upset Our Notions of How Much "Upskilling" Will be Needed by 2030?

It is hard to disagree with this McKinsey analysis of how skill requirements might change in the United States and Europe between 2016 and 2030. On the other hand, it also is possible to argue that we simply do not know yet how much artificial intelligence will reduce requirements for cognitive skills or technology skills.

In principle, AI should reduce the need for humans to acquire many cognitive or technology skills, as AI will automate so much of what we now believe will be required that perhaps there will be less “upskilling” need than the analysts expect. 

source: McKinsey 

"Five Nines" Availability Might Not be Possible Anymore

In the internet era, something profound has happened to traditional connectivity provider thinking and spending related to network service availability. Something equally important has happened to consumer expectations about service or app availability, as well. 

Service and app providers using the internet as the access platform generally cannot expect to reach 99.999 percent availability. Neither can mobile services of any type. Virtually all fixed network services except perhaps voice also now will fail to reach 99.999 percent availability. 

The reason is simply the math. Availability of any single device, in principle, could reach 99.999 percent availability, though that is not true of routers or servers. End user devices also never reach 99.999 percent availability. 

But system availability is the sum of every single device in the delivery chain. And even if every device and network element had 99.999 percent availability (“five nines”), reliability shrinks with the number of devices. 

It is demonstrably not possible for most end user internet experiences or applications, almost certainly. In the transport business, 99.999 percent availability is probably possible only on the portions of the network with the fewest total network elements, end to end. 

As a rule, I think we safely can assume that any internet-delivered will not ever reach 99.999 percent availability at the user level. It also is safe to assume that mobile voice, text messaging and internet access virtually never reach 99.999 percent. Possibly only legacy fixed network voice can hope to do so. 

It goes without saying that the Internet is a complex system, with lots of servers, transmission paths, networks, devices and software all working together to create a complete value chain.

And since the availability of any complex system is the combined performance of all cumulative potential element failures, it should not come as a surprise that a complete end-to-end user experience is not “five nines.”

Any end-to-end network, and the applications delivered over that network, have many single points of failure. Even if most network element has five nines levels of availability, and there are just eight total elements in series, with one device having 85 percent availability, and one device has 95 percent availability, total end-to-end system availability is just 59.87 percent. 

That is calculated as 85%*90%*99.9%*98%*85%*99%*99.99%*95%, or 59.87 percent. 

Redundancy is the way performance typically is enhanced at a data center, by a transmission network or application. But the total number of network elements for any single app also is going to be more than eight. 

Component	Availability
Web	85%
Application	90%
Database	99.9%
DNS	98%
Firewall	85%
Switch	99%
Data Center	99.99%
ISP	95%

So one way of thinking about reliability or availability is that modern application delivery systems cannot actually meet the old “five nines” standard, end to end. There are simply too many network elements involved in any end-to-end system. 

The business implication is that “five nines” increasingly is not possible. 

But consumer expectations also are involved. Consumers know mobile phones are not as reliable as fixed network phone service. They are willing to make the trade off. They know computers, operating systems and web apps are not “five nines” available. They know they will have to reboot on occasion.

The business implication is that consumers can live with “less than 99.999 percent availability if value is high enough. The corollary is that they also might not be willing to pay what it theoretically costs to move closer to five nines availability. 

The bottom line is that five nines cannot be provided, nor will consumers pay for it. Some level of availability less than 99.999 percent is acceptable and even expected. The question is how much availability is required to keep a user satisfied, as they might not be willing to pay much more--if anything more--to get that level of availability. 

Much More AI Use in Telecom in 5 Years

If a recent forecast by Omdia is correct, telecommunications service providers will be spending quite heavily on artificial intelligence software over the next five years. Though AI will be a bigger capability for virtualized networks in the future, the current use cases often focus on customer service, especially call centers. 

source: Omdia 

AT&T, for example, uses AI-assisted systems to optimize technician schedules, minimizing commute time, for example. AT&T reportedly recorded a seven percent reduction in miles traveled per dispatch and a five percent increase in productivity.

The AI incident management process also uses AI to detect network issues in real-time, even before the customers are aware there is a potential problem. It is said that AT&T has the ability to manage about 15 million alarms per day.

Users Will Migrate to 5G, Maybe Because of New Value, But More Likely Because of Supplier Push

End user demand for various connectivity services changes over time, but typically when some new need arises. But sometimes supplier push drives the change.

That might be the case for 5G, early on. Since 5G requires new devices, 5G device availability, especially for the most-popular brands, is a key requirement for higher 5G adoption. It is less clear that any immediate new use cases will be obvious.

Changes in demand have many drivers other than new needs, of course. At other times, revolutionary changes in supplier policy can shift demand quite radically. 

There was a time when a deliberate pricing strategy by AT&T mobility drove a huge amount of product substitution, literally leading to huge use of mobile calling as a direct substitute for long distance, and also leading to mobile substitution for local telephone service as well. 

 source: Telecom Policy Institute

Few now recall it, but AT&T Wireless once drove rapid mobile adoption by consumers by revolutionizing the way consumers paid for--and how much they paid for--long distance calling.

Back in 1998, AT&T unveiled a major new pricing plan for mobile users that priced all domestic calls for 10 cents a minute. That Digital One Rate plan effectively erased the distinction between local and long distance calling and provided a major incentive for consumers to buy mobile service.

Even many astute industry watchers did not appreciate the revolutionary nature of the plan. Technology pundit Walt Mossberg once called Digital One Rate “marketing hype.”

“It promises to make your cell phone as simple and affordable to use as a landline phone, so that you'll use it even for casual calls without a second thought,” said Mossberg. “The actual service behind the marketing isn't good enough to really allow that. I've been frustrated with it again and again.”

Digital One Rate was anything but hype. It really did revolutionize the way consumers and businesses made calls. It really did begin the mass adoption of mobile phones and the demise of landline service.

Beyond that, Digital One Rate changed the key profit drivers in telecom, from long distance revenue to mobile service. Within a decade, the industry profit driver changed from long distance to mobility. The shift from voice to data would follow.

In the ensuing years after Digital One Rate was introduced, long distance revenue plummeted, as did use of landline phone services. Digital One Rate was the driver, as the whole industry shifted pricing and packaging.

It is unclear how much 5G can shift end user demand. It is clear that at least some mobile service providers in the U.S. market are going to try and drive a substitution of mobile broadband for fixed network access. It is not clear whether end user demand shifts will mostly be driven by end users or suppliers. 

Some of us can remember the new needs that caused us to upgrade to specific devices, and then to web-centric devices. I actually do not recall which 2G device I was using when the “need” for a Blackberry happened. Odd enough though it will seem now, “mobile email” was a huge draw, providing enough value to make it an easy choice. 

I also remember when the Blackberry became a barrier. There was a time when smartphones did not routinely offer access to turn-by-turn directions, and for no subscription fee. That alone was the killer app that made the Blackberry suddenly less capable than I needed, and made the value of a 4G device much more attractive. It meant I did not need a discrete GPS device, with a required subscription. 

I had used 3G dongles for wireless internet access when on business travel, as painful as it was, experience wise. The shift to a 4G dongle was a “no brainer” decision because the user experience was so much better. 

The visual web made routine upgrades of my fixed network, to get higher speeds, a logical decision. It has been years since download speed actually has been an issue, though, as speeds and pricing have been more than adequate for all my use cases. 

Work from home has not been a particular issue, as I have worked remotely, and out of my home, for most of the last 25 years. But what is new is the amount of time I spend on videoconferencing services. And since my connection is asymmetrical, with what now insufficient bandwidth for consistent user experience. 

The new need is “more upstream bandwidth,” for the first time. At least so far, my 4G experience is not a pain point, as I tend not to do work videoconferencing on the mobile device. 

In all those instances, a shift to different or new services, though anecdotal, was driven by a change in demand for features or services. 5G will be the same sort of thing for most people, and might initially be driven simply by the need for a new device that just happens to use the 5G network.