Telecommunication Industry - Sophia Training & Consulting

AI Solutions

Consulting

Telecommunications

We partnered with one of Italy’s largest telecommunication providers to implement SOPHIA’s AI Ecosystem, driving digital transformation and responsible AI adoption across the organisation. Our approach was designed to directly address the telecom sector’s core challenges: reducing customer churn, managing high volumes of customer service inquiries, and enabling effective upselling.

Employees Trained

Satisfaction Rate

Tailored Trainings Delivered Across Departments

AI Agent MVPs Launched

Defining the Problem

The telecom sector faces increasing pressure to innovate while ensuring compliance, data security, and operational efficiency. Our client needed a scalable, responsible AI strategy to address these challenges—especially customer churn, high service volume, and upselling—and unlock new value streams.

Our Solutions

By implementing SOPHIA’s AI Ecosystem, we provided a holistic, step-by-step framework that:

* Raised organisational AI literacy

* Delivered targeted, actionable training

* Established ethical and regulatory guardrails

* Enabled rapid prototyping and deployment of AI solutions (including predictive churn models and AI agents for service and marketing)

* Fostered a culture of continuous improvement and responsible innovation

SOPHIA AI Ecosystem

A framework for overseeing this collaboration

Step 1: Awareness Training

We began with comprehensive awareness sessions across all departments to establish a shared understanding of AI and its practical value for Telco pain points. Training covered:

* The fundamentals of AI, including distinctions between machine learning and generative AI

* How AI can be leveraged to predict and reduce customer churn, automate customer service, and drive upselling

* Practical applications of AI within telecom, such as network optimisation, customer experience, and predictive maintenance

* Risks and challenges associated with AI adoption, including customer trust and regulatory compliance

* An overview of AI regulations worldwide and their impact on telecom operations

* Best practices for establishing internal AI governance frameworks

Step 2: Tailored Departmental Training

We designed and delivered customised training programs for each department, focusing on how generative AI could enhance their specific roles and address key pain points.

This targeted approach ensured every team could identify and implement AI solutions directly tied to their business objectives.

* Marketing: Leveraging AI for personalised upselling and cross-selling campaigns

* Consumer Commercial: Using AI to identify churn risks and automate retention offers

* Customer Service: Integrating AI agents to handle high inquiry volumes and improve response times

* Legal & Compliance, HR, Finance, Strategy & Business Development, Maintenance and Operations: Identifying relevant AI use cases and confidently integrating AI tools into daily workflows

Step 3: Internal Chatbot Development & AI Governance

Working closely with the IT team, we developed an internal knowledge-sharing chatbot. This solution leverages a blend of open-source and proprietary technologies, using advanced semantic techniques to maximise accuracy and minimise hallucinations.

Future Roadmap: The chatbot infrastructure is designed to be extended to customer-facing roles, enabling automated handling of common inquiries and supporting customer service teams during peak loads.

Key considerations included:

* Ethical development standards, such as avoiding web scraping and prioritising data privacy

* Ongoing collaboration with the compliance team to establish and document robust AI governance policies

* Training employees on ethical AI use and governance best practices

Step 4: AI Agent Pilots

We are now piloting AI agents within the Marketing, Finance, Accrual, and Maintenance teams. As these MVPs (Minimum Viable Products) become operational, our next focus will be on integrating and coordinating these agents across business units for even greater impact.

These pilots are designed to:

* Marketing: Automate upselling and retention campaigns using customer data and predictive analytics to target at-risk customers and personalise offers

* Customer Service: (Planned) Integrate AI agents to handle high inquiry volumes, providing instant, accurate responses and freeing up human agents for complex cases

* Churn Prediction: Develop predictive models that identify customers at risk of churning, feeding this data to AI retention agents for proactive outreach

* Finance & Maintenance: Automate routine processes and enhance decision-making

Change Management

Change management has been integral throughout this process. We worked closely with managers and employees to address concerns, build trust, and ensure smooth adoption of new AI-driven workflows, especially in customer-facing teams where AI agents will have the most visible impact.

Impact

* Accelerated AI adoption across all key business functions

* Improved knowledge sharing and collaboration through a secure, ethical chatbot

* Strengthened compliance and governance, reducing regulatory risk
* Laid the foundation for scalable, integrated AI solutions across the enterprise

* Piloted and operationalised three AI agents (Marketing, Finance Accrual, Maintenance), delivering measurable improvements in efficiency, decision-making, and customer engagement