Telco use-cases for AI: A simple categorisation model

The coming years will see the application of AI technology across all sectors of the economy and life. The telecoms industry is no different. Although I’ve been commenting on telco-sector AI in the context of “TelcoFuturism” for some time (link), and co-ran a workshop on it in May 2017 (link), the last few months have seen a notable upswing in interest. I’d say that the public use-cases now seem to be significantly in advance of those for blockchain, in terms of potentially-transformational technologies.

That said, it can still be hard for many executives to grasp exactly what is likely to change, and when, for AI/telecoms combinations. This is highlighted by the surge in AI-related panels, presentations and even complete streams at industry conferences – although sometimes I see more interest from generalist AI people about the telecoms vertical, versus telecom specialists looking at what’s new. 

Both sides of the equation have large volumes of obscure acronyms, multi-layered technology stacks, and complex volume chains – which can mean that mutual understanding is often confined to narrow niches. AI covers machine- and deep-learning, language processing, machine-vision and much more. Telecoms includes vast realms of internal systems and processes that are unknown to most who are not insiders – domains like core networks, OSS/BSS, network optimisation, toll fraud and service-assurance are alien to those not steeped in the industry.

One of the ways I’ve been using to “set the scene” for describing AI/telecoms intersections is to simplify and categorise the use-case areas. I count three, possibly four, large “buckets” into which a variety of telecom AI impacts will fit. These buckets are not based on either specific AI or telecoms technology slices, but more on understandable business functions and roles:

• Dealing with customers
• Managing operations
• Creating new services
• (External risks)

 Within each of these areas, there are many, many sub-sectors – and also some overlap.

“Dealing with customers” can include everything from voice/text chatbots for customer-service, through to predictions of which customers are least-happy and may “churn” to competitors. Where telcos have retail outlets, it could incorporate various in-store technologies, or it could be about smarter web-consoles for B2B customers running complex managed services.

“Managing operations” is even more diverse – it could be fault prediction for network elements, optimising the 100s of configuration variables for radio networks, spotting fraudulent traffic to international premium-rate numbers, allocating engineering resources more productively, or protecting against hackers and malware. There are hundreds of possible uses here, which mostly overlay on top of existing operational/business support systems (OSS/BSS) See also my recent post (link)

“New services” also spans a range of areas, but broadly splits between AI-enabled and AI-enabling services. An AI-enabled service could be a local-language voice assistant added to a cable operator’s set-top box or remote control. Or it could be the provision of integrated “smart city” solutions including video-cameras and security analytics. AI-enablement could include offering “edge” servers for hosting local processing, milliseconds transport-time away from a device, or it could be the provision of anonymised bulk data for others to apply algorithms to. Telco opportunities with IoT+AI include both enablement and enabled services, in numerous manifestations.

The “risks” category includes a diffuse set of possibilities by which AI might harm the telecom industry, or dampen demand for services. Smarter devices (eg autonomous vehicles) will be able to host their own offline image processing & route-planning locally, rather than needing realtime connectivity at 5G speeds/latencies. Another threat could be customers’ smart assistants renegotiating price-plans on their behalf – after crowdsourcing millions of conversations to deduce how best to game the retention staff’s scripts and objections. (Of course in the latter example, the customer-retention team could themselves be bots). Numerous types of automated “least-cost X” and arbitrage engines are likely to emerge. Various security risks are also probable here too.

Clearly, using just these four "buckets" misses much of the fine-grained detail. But I find it helpful as a starting point, as most top-level industry issues apply differently to each. 

Consider input data, for example – for both customer management and operations, telcos have abundant historical records and ongoing data collection that may generate terabytes per day. But for the former, privacy considerations often come to the fore in terms of regulation and risk, while this is far less of a concern for internal operational data, for example on how the network is running. For new services, almost by definition the focus is on collecting/processing/transporting new data, rather than deriving conclusions from existing sets. 

This four-way framework is also useful for thinking about different types of ROI model - split broadly between impacting existing revenues, existing costs, new revenues and potential changes to underlying assumptions. 

I'll be covering these topics in more depth in various upcoming presentations and reports, as well as looking at other areas of telco-linked innovation such as blockchain, 5G and enterprise verticals. Please get in touch if you would like more detail, or are interested in internal workshops, external support through events or white papers, or are seeking ongoing strategic advisory support.

Blockchain and the Telecoms Industry: Thoughts from TMForum Live

I’ve just returned from TMForum’s annual conference in Nice. Blockchain / distributed-ledger technologies (and even more so AI, which I’ll cover in another post) figured quite highly.

(I'm expecting this post to be read by some non-telecom people, so a bit of background is likely to be useful here)
 

TMForum Live is an event traditionally aimed at the IT-facing parts of the telecoms industry. This is usually called BSS and OSS in the vernacular – business and operations support systems, such as billing, ordering, customer service, network & fault management etc. TMF was originally the “telemanagement forum”. The event talks about top-level industry themes (5G is a hot topic, as is IoT) but couches them in terms of “monetisation” and “operationalisation”. It’s necessary back-office stuff, but sometimes a bit dry.

So for outsiders – such as blockchain specialists - looking at the telecom industry, the BSS/OSS sphere is a pretty impenetrable forest of acronyms, legacy software, IT frameworks and solutions to deal with telcos’ sprawling operational and customer-facing needs. It also showcases “catalysts” – joint R&D projects run by consortia of companies, highlighting future possibilities – which are a bit more accessible, with dozens of workgroups exhibiting demos and results of their work.

In recent years, two major trends have led to the event’s character changing significantly:

• A blurring of the boundaries between IT systems and the telcos’ networks, as virtualisation (NFV – network function virtualisation & SDN – software defined networking) takes hold
• An increased focus on IT systems to support new customer-facing services, or adjacent areas that telcos hope to find new roles in servicing, such as IoT platforms, content, banking and smart cities. (Yes, the dreaded word “digital” makes frequent appearances)

More mundanely, the event has looked at ways to enhance the bread-and-butter costs and effectiveness of BSS and OSS solutions. Terms such as “customer experience management” and “service assurance” are everywhere, with user-centric improvements to mobile self-care apps, contact centre automation tools, chatbots, better ways to monitor network coverage and so on.

This year, quite a few conference sessions and exhibiting vendors mentioned Blockchain. It definitely wasn’t as high-profile as AI and machine-learning, but it provoked a lot of curiosity. A year ago, few attendees would have heard of it, much less thought it relevant to telecoms. Now, there is an internal working group, a panel session linking Blockchain & IoT, at least one Catalyst project, and a significant number of TMForum’s members who are taking an interest. I spoke at a smaller event TMForum ran in Portugal a few months ago, outlining my thoughts about applications, and had a significant amount of interest.

The main use-cases being discussed for telecoms blockchain included:

• Device identity & authentication, especially in IoT. There was a Catalyst exhibited (link) which used a Microsoft blockchain to create unique identities for medical sensors (wearable patches), via an Ericsson IoT platform, and also involving AT&T and others. This was also used for data time-stamping and asset management.
  
• Smart contracts, both as a possible new "Contract-as-a-service" play for enterprise-facing telcos, but also as a way to offer and manage SLAs (service level agreements) for CSPs' own network services.
• Mobile banking and micropayments, including for IoT-type use cases such as smart electricity grids. Again, blockchains might be used by telcos to either build complete "vertical" services for end-user, or as Enabler-as-a-Service wholesale/API plays for domain specialists.

I also had private discussions with vendors in Nice that covered a lot of other possible use-cases, including ones around NFV monetisation, fraud prevention, wholesale reconciliation and data-integrity protection. Another one that I've talked about before is use of distributed databases for new shared-spectrum usage and localised private radio networks - and that was independently mentioned by a speaker at another recent conference, the Wireless Broadband Alliance's congress in London.

All of these areas, and others, will be discussed at the Telecoms Blockchain & AI workshop I'm running on May 31st in London. There are still some spaces available - you can sign up here (link) or email me at information AT disruptive-analysis dot com.

My general sense is that development of blockchain applications in telecoms is taking a rather different evolution path to AI. There are some big “framework” plays around telecoms AI, including massive shared “data lakes” relating to customer data, network status and other variables. These can help drive more-reliable operations, better planning and happier customers who are prepared to spend more. Conversely, interest in blockchain and distributed ledgers is (for now) much more dispersed. Individual projects and functions are looking at these as solutions for “point problems” – cheaper registries and databases, ways to secure identity, whether smart contracts could help create enforceable SLAs and so forth.

As such, it’s harder to see telcos developing a centralised, coherent “blockchain strategy” – it’s probably going to be used tactically in very isolated niches, for the next 1-2 years at least. There will be a lot of pilots and prototypes – and each domain will also have a wide range of alternative options to consider. We might see more strategic use in IoT in future, as that seems to be a focus of quite a lot of work. This fragmentation of effort also means that multiple vendors, integrators and blockchain platforms (private, but also potentially public blockchains) are likely to be relevant. As yet, there is no real centralisation of effort for telecom blockchains in the same way there is for banking and healthcare. That may be a next step, beyond the TMForum's own working group.

I'm interested in others' views about this - and it's something that the May 31st public workshop (the first I'm running) should shed further light on. (Workshop details here).