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"AI Summit Symposium"

Date/Time: Wednesday, June 04, 2025 | 11:00 AM Eastern Daylight Time

Summary

AI has become a critical part of the overall CSP organization. Omdia’s AI Applications Software Market Forecast predicts that the value generated by artificial intelligence (AI) applications in telecoms will reach $8.7bn by 2027, increasing by a factor of eight compared to immediate pre-pandemic levels. We examine multiple facets of the AI revolution; how the scale, agility, and programmability of the telco are dependent upon AI, including securing operations, creating and launching new digital services, and incorporating AI into business processes, systems, transport networks, and mobile infrastructure.

Session 1 - Cloud - OPEX vs CX Use Cases

11:00 AM Session One - Cloud - OPEX vs CX Use Cases

Up until now, our surveys examining AI implementations show that CSPs have leaned towards customer experience automation versus operator OPEX. Or have they? The most popular CX use cases for automation today are customer self-service and customer center support (e.g. chatbots). These use cases are squarely targeted at lowering customer support costs, i.e. OPEX savings, not so much at enhancing the customer experience. “Customer journey management”, structured and unstructured data, is a more complex use case – but moves the needle from OPEX savings to revenue generating by enabling individual customer-focused use cases like “upsell/cross-sell” and “personalized offers/bundles”. This session will examine how rapidly CPSs are maturing their AI usage from an implementation philosophy of “Lower my Costs (quickly) ” to “Build New Revenue Streams” and what, in terms of cost, time, and complexity may be placing a drag on this transition.

The low-hanging fruit – how dedicated are the CSPs to OPEX focused CX automation and when will they move in the direction of customer journey management?

What are the largest obstacles standing between OPEX-focused AI implementations and new revenue streams based on an AI foundation?

Who in the CSP organization is making the AI investment decisions?

Are CSPs challenged with establishing a positive ROI for new revenue-generating AI-based use cases? Are OPEX-focused use cases that much easier to justify and move on?

How are CSPs Improving agility and flexibility with AI-enabled granular, vertical-specific use cases?

And how are they optimizing network resources and performance, and ensuring reliable connectivity with AI?

11:00 am ET – Opening Remarks (10 mins)

11:10 am ET – Service Provider Keynote (15 mins)

11:25 am ET – Sponsor Keynote (15 mins)

11:40 am ET – Panel Session (40 minutes)

12:00 pm ET – Q & A (10 mins)

12:10 pm ET – End

Session 2 - Optical Networks - Practical Applications of AI in Transport Networks

12:45 PM Session Two - Practical Applications of AI in Transport Networks

AI and ML have major roles to play in the transport network and, in fact, are already being used to deliver network health and predictive analytics and other advanced functions. There is much more to come in these areas. But, amidst the hype, operators must not lose sight of the practical applications of these technologies. This session seeks to move beyond the hype to focus on the practical use cases for AI and machine learning in the transport network. Topics will include:

Primary AI and ML use cases in transport networks – current and planned

Operators benefits and challenges of adopting AI/ML

Where are operators applying generative AI today, and what are they looking to do in the future?

How network automation both enables and is enabled by AI/ML

12:45 pm ET – Opening Remarks (10 mins)

12:55 pm ET – Service Provider Keynote (15 min)

1:10 pm ET – Sponsor Keynote (15 mins)

1:25 pm ET – Panel Session (40 mins)

2:05 pm ET – Q & A (10 mins)

2:15 pm ET – End

Session 3 - Mobile - AI RAN

11:00 AM Session Three - Mobile - AI RAN

AI/ML-derived algorithms are already routinely applied in mobile networks and devices. And now there are initiatives underway – in 3GPP and in the AI RAN Alliance – to use AI more deeply in the RAN. The trend is towards what is called “AI-native RAN” or simply “AI RAN”. Among the topics, this session will address:

How AI RAN is enabled by open programmable RAN

Using AI to optimize RAN functions & operations

The impact of AI-enabled endpoints and services on RAN design

Hosting AI workloads at the network edge and deeper into the RAN to improve performance and monetization

The path towards AI native RAN in 6G

11:00 am ET – Opening Remarks (10 mins)
11:10 am ET – Service Provider Keynote (15 mins)
11:25 am ET – Sponsor Keynote (15 mins)
11:40 am ET – Panel Session (40 minutes)
12:00 pm ET – Q & A (10 mins)
12:10 pm ET – End