Veeresh Shringari on AI’s role in Telecom customer journey

In this Worldwide AI Webinar session, Veeresh Shringari, Senior AI/ML Consultant at Amazon Web Services walked the audience through the telecom customer journey and the role AI plays in it.?

The recording of the whole session is now available on our website and YouTube! Check it out!

Key takeaways

Obstacles of AI/ML adoption in Telecommunications

As stated by Veeresh, telecom operators are grappling with a huge problem at the back end.?

Since we’ll be having over 2000 parameters per 5G node and each operation is getting 50 times more complex than before, the digital transformation is very much happening and telecom operators and communication service providers (CSP) will need to adapt AI/ML to solve the upcoming challenges.

However, AI/ML adoption in telecom isn’t without any obstacles. Mr. Shringari listed out the following four challenges:

1. Infrastructure
2. Workforce
3. Data quality
4. Data preparation

Picture 1: Obstacles to using AIML (Screenshot taken from Veeresh Shringari’s presentation)

A 2018 Interop survey pointed out that infrastructure is the biggest problem in AI/ML adoption. AI talents also pose an obstacle to overcome as cited by McKinsey.

Then, data accounts for the next two complications. Veeresh highlighted the importance of making data discoverable over merely storing them. Additionally, he emphasized that data preparation, which is time-consuming, expensive, manual, and inefficient, accounted for 80% of the work. Therefore, tools are being developed and used to decrease the preparation time.?

Benefits and use cases of technology in business

One of the key use cases of technology in business as detailed by Veeresh Shringari is visual voicemail. Customer voicemail calls can automatically be transcribed and the output text sent via text message to the target recipient, which is a value-added service provided by some CSPs. This helps make voicemail more accessible for sensory-impaired individuals. Some benefits obtained from this include:

• Transcription accuracy
• Auto language identification
• Multiple language support
• PII Redaction

Picture 2: Alexa for Care Solution (Screenshot taken from Veeresh Shringari’s presentation)

Then, he talked about Alexa for Care Solution. As Amazon has witnessed, customers want access to brands whenever and wherever they are, whether they are at home or in retail stores. The challenge for Amazon was figuring out how to remove friction from at-home or mobile interactions with Customer Care. They came up with the following solutions:

• Activating an Alex Skill and authenticating the caller
• Fulfilling the caller’s needs in an automated fashion based on their intent
• Adding seamless customer callback should the caller not achieve the in-channel outcome

Veeresh Shringari discussed a few more use cases of technology in business, particularly at Amazon Web Services so check out his session to learn more.

The future trends

In his personal point of view, facilitating horizontal spread will be an upcoming trend for CSPs to look out for. The challenge that might come with this is the need for fast and wide data availability. Veeresh suggested that to deal with this problem, the telecom industry should work with automotive, healthcare, or finance domains to offer hybrid AI solutions taking advantage of 5G.

A couple of other trends he mentioned are multimodal services which might enable transducing touch, sense, smell, and sound through communication, and remote services, which will solve the problem of technology not reaching remote areas in the world.?

Overall, the AI wave in telecom has enhanced customer purchasing habits, offered new channels for customer satisfaction, and given service providers new sources of income. AI plays an essential role in the telecom customer journey and this is a space to be on the lookout for!