AI, blockchain and edge computing – a dizzying mix for telcos

Photo by Motortion

Three hot tech buzzwords in the telecom sector right now are edge computing, artificial intelligence (AI) and blockchain. But what happens when you put them together? No one’s sure, exactly, but at the very least it will give communications service providers (CSPs) a potentially lucrative place in the digital ecosystem.

During a panel session at Digital Transformation Asia in Kuala Lumpur Wednesday, industry experts discussed the potential of multi-access edge computing (MEC), AI and blockchain. Shekeb Naim, Associate Director of ICT Research & Consulting, MarketsandMarkets Research, said combining the technologies will create a $10 billion opportunity across the value chain – specifically, application providers, hardware infrastructure providers, middleware providers, and network and systems integrators. Likely use cases include smart cities, transportation and logistics, and energy and utilities.

Panel, from left: 
Shekeb Naim, Associate Director of ICT Research and Consulting at MarketsandMarkets Research
Utpal Mangla, head Telecom, Media and Entertainment Industry at IBMDr. Gadi Solotorevsky, Chief Evangelist, Revenue Guard at Amdocs
Sunny Nirala, head of Big Data at Celcom
Mathews Thomas, Master Inventor and Innovation Executive Architect at IBMPaul Morrissey, Global Ambassador; Head of the Data Analytics and CX Group at TM Forum

CSPs will be in a good position to serve those markets, but the first thing they’ll have to do is accept that they will participate in ecosystems of partners rather than control them, said Utpal Mangla, Head of Telecom, Media & Entertainment Industry, IBM.

“The edge use cases and 5G use cases cover various industries, so it’s impossible for telcos to own so many industries and become a custodian of that ecosystem,” he said.

Whether telcos are ready to play in that ecosystem depends who you ask, he added – to include different departments in the same telco.

“I think they are struggling internally among themselves,” Mangla said. “For very large carriers for example, when we talked to the B2B side of their business, they’re all in. When we talk to their consumer side, they’re reluctant. And at the end of the day, the decisions have to be made at the very top whether they’re going to do it.

“Also, revenue sharing remains a sticking point for many CSPs,” he continued. “What percentage you will get? What’s your level of involvement? Those models are not mature yet. So, it does create tension.”

Each has its own challenge

Meanwhile, a problem for CSPs is that each of these technologies comes with its own challenges even before you attempt to combine them. With blockchain, for example, fragmentation is an issue. There are several distributed-ledger technologies available, but they do not interoperate. That will likely change over time, but telcos have to make decisions now.

That means having an idea of what you want to do with blockchain – or, more to the point, how your customers or partners might want to use – and then selecting the right technology to fit that purpose, said Naim of MarketsandMarkets.

“For example,” he explained, “in an industrial IoT [internet of things] scenario, Hyperledger is appropriate because it’s secure, private and fast, whereas with something like Ethereum everybody has the right to accept or reject the transaction. You have data duplication and so the network becomes very slow.”

AI – along with big data analytics in general – comes with its own baggage, from bias and data governance to privacy, transparency and ethics. Regulatory compliance issues notwithstanding, dealing with all those issues boils down to a combination of awareness, best practices and a good sense of ethics.

Sunny Nirala, Head of Big Data, Celcom, remarked that getting the ethics component right is a matter of remembering that customers and business partners are all humans, just like you.

“Strangely as it sounds to say this, we’re all humans at the end of the day,” he said. “So, the whole ethical nature of dealing with that data means we’ve always got to place ourselves into other people’s shoes and think, ‘If a business had my personal data, what would I want them to do with it’?”

This article was first published on TM Forums’ Inform

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