Blog AI

GenAI Can Increase EBITDA by 31-57% for the Typical CSP. Here’s how.

Akil Chomoko

13 August 2024

With AI forecast to unlock more than $10.3 trillion in additional economic value by 2038 (Accenture, 2024), it presents a significant opportunity for the telecoms industry to solve long-standing business problems. One such problem is the volume of billing inquiries, with 40-60% of inbound calls to customer service centers relating to billing. In fact, if a customer makes just one call to a customer service center a month, it can render them unprofitable.

AI provides an opportunity for CSPs to minimize the cost impact of dealing with customer inquiries and complaints by drastically reducing the time it takes to handle calls, while boosting revenues through more effective upsell. Here at Aria, we wanted to know just how big an impact AI could have on CSP EBITDA (Earnings Before Interest, Taxes, Depreciation, and Amortization). So, always up for a challenge, we participated in a TM Forum Moonshot catalyst to prove that using AI to deliver smarter solutions, including copilots to boost call center performance, could boost EBITDA by up to 30% (spoiler alert: we smashed it.)

The catalyst

TM Forum catalysts bring together leading vendors and influential industry figures to co-create solutions that drive industry change through Open APIs, ODA (Open Digital Architecture), AI, and automation. Moonshot catalysts are a special type of catalyst that aim to tackle the biggest challenges in the telecoms industry.

Alongside Vodafone, Telecom Argentina, Converge ICT, Salesforce, Calvi, AWS, and Nespon, we developed a Moonshot catalyst called AI-driven EBITDA Mastery: Revolutionizing Customer Journeys. This catalyst set out to prove that by using GenAI to enhance customer service, optimize network management, and streamline various internal processes, CSPs can achieve a 30% increase in EBITDA.

We understood that to really move the EBITDA needle, CSPs need to address the high OPEX business areas that deal with complex and ever-changing data, such as billing, account information, and jeopardy management. This is a stretch for conventional GenAI solutions, which rely primarily on static information.

GenAI value across the customer journey

We started by selecting three key points in the customer journey that we identified as high-OPEX areas to target with our AI design. Next, we estimated the savings for each use case. These savings combined to deliver a whopping 31–57% EBITDA growth when applied to a broader set of use cases – completely smashing our 30% target. The use cases we targeted were:

  1. Reduce assisted support (15-40% reduction): By leveraging GenAI to curate personalized messaging using billing data, we were able to decrease reliance on assisted support, while proactively engaging with customers.
  2. Improve productivity of assisted support (40-70% improvement): Using a GenAI co-pilot, we increased the productivity of CSRs and field engineers by automating the analysis of customer billing data and field issues. This made our agents more efficient, reducing human-based OPEX and enabling them to handle complex issues more effectively.
  3. Improve Next Best Action (5–7% improvement): By implementing sentiment-based Next Best Actions, we maximized customer satisfaction and value. This involved identifying corrective actions during AI-assisted processes to optimize first-touch resolution, enhance customer satisfaction, and identify upsell opportunities.

Validation

Of course, it is easier to deliver impressive EBITDA gains in a controlled environment than in production, so we validated our results through combined time-motion analysis and business use case projections across the customer management lifecycle. This validation was conducted using a composable architecture that mirrored the common IT landscape of a CSP, complete with multiple systems and distributed data architectures.

We presented our catalyst to a panel of experts at Digital Transformation World 2024 and were delighted to win the 2024 TM Forum Moonshot Catalyst – AI Challenge award.

For full details, read the catalyst brochure or visit the catalyst website.

Some of the concepts behind this award-winning catalyst are included in Aria Billie™, a versatile AI co-pilot and self-care bot. Aria Billie, along with its framework, Aria Billie Connect™, boosts productivity and personalization at scale, using predictive and generative AI across service, revenue, and product operations. Book a demo today.

Akil Chomoko

VP Product Marketing, Aria Systems. Akil leads solution marketing at Aria, building go-to-market strategies and programs in key target industries. Akil has over 20 years of experience in the telecoms industry, serving most recently in senior product marketing and management positions at MDS Global, AsiaInfo and CSG (Intec & Volubill).

View Akil’s LinkedIn Profile