Client

The client is a leading Middle East airline operating an extensive global network and serving millions of passengers annually through a rapidly expanding digital and operational footprint. With strong year-over-year growth, rising passenger volumes, and increasing service expectations, the airline is prioritizing a transformation of customer experience. 

To support this scale, the organization needed to modernize its customer case-management capabilities and adopt AI-driven tools that improve responsiveness, personalization, and service consistency across channels.

Market Trends in the Middle East Aviation Sector

Middle East airlines are projected to lead global profitability in 2025, driven by strong demand for premium travel, expanding route networks, and record hub traffic at major airports in the region. At the same time, delivery delays and capacity constraints are putting pressure on service operations to handle higher volumes efficiently.

As competition intensifies, carriers are prioritizing AI in customer service automation, omnichannel engagement, and AI-enabled service platforms to enhance traveler experience and operational agility. In this environment, modernizing customer case management has become crucial for airlines seeking to maintain service excellence while expanding their global operations.

                 Need for Change

As passenger volumes and service expectations increased, the client required a modern, scalable approach to managing customer requests across various channels. The legacy case-management process was slow, manual, and inconsistent, making it challenging to deliver timely resolutions, personalize interactions, or maintain compliance.

To strengthen customer satisfaction and support a growing global operation, the airline required a digital, AI-enabled platform that could streamline workflows, improve accuracy, and provide unified visibility across service teams.

                     Key challenges

• Lack of automated case creation: Manual conversion of customer requests into cases reduced agent productivity and increased the likelihood of errors.
• Slow and inconsistent routing: Without intelligent routing, requests were manually assigned to agents, delaying responses and impacting customer experience.
• No unified customer view: Disconnected systems prevented agents from accessing centralized customer data, limiting their ability to provide personalized support.
• Inability to track requests effectively: The absence of a tracking mechanism led to repeated SLA non-compliance and difficulty ensuring timely follow-ups.
• Scattered email communication: Handling cases through individual mailboxes made it impossible to maintain a complete conversation history for each request.
• Limited visibility into performance: Without real-time dashboards, leaders could not assess individual or team performance or identify process bottlenecks.
• No centralized knowledge repository: Agents lacked easy access to articles or guides, slowing down case resolution and reducing efficiency.
• Absence of self-service options: Customers had no portal to find information independently, increasing agent workload and dependency on human support.
• Missing chatbot and virtual assistant capabilities: The organization could not deliver instant responses or handle routine queries at scale, further slowing service delivery.

                LTM Solution

LTM partnered with the client to modernize its legacy customer case-management process by implementing an AI-powered solution on Microsoft Dynamics 365 Customer Service.

The goal was to streamline case handling, improve response quality, and enable service teams to manage rising volumes with greater accuracy and speed. The new platform created a single, connected environment for creating, routing, tracking, and resolving customer cases across all service channels.

Implemented automated case creation and intelligent routing

Used D365 to automatically convert customer requests into cases and route them to the right agents based on skills, availability, and workload, improving speed and reducing errors.

Enabled proper omnichannel support

Consolidated email, chat, voice, SMS, and social interactions into a unified platform. AI helped agents deliver consistent and personalized responses across every touchpoint.

Strengthened SLA compliance

Introduced automated tracking of response and resolution times with alerts that notified teams of potential SLA breaches, improving overall accountability.

Enhanced agent efficiency with AI assistance

Delivered AI-driven case summarization, communication highlights, and contextual recommendations, helping agents resolve issues faster and with more accuracy.

Built a centralized knowledge base

Created a searchable repository of articles, FAQs, and guides. AI-powered search surfaced the most relevant content to support quicker case resolution.

Introduced AI-based email drafting

Enabled AI agents in customer service to generate personalized email responses using case details, customer history, and knowledge-base content. Multi-language support and template suggestions improved consistency and reduced effort.

Enabled real-time collaboration

Integrated Microsoft Teams and automated approval workflows so agents could collaborate across departments for faster resolution of cross-functional issues.

Delivered predictive insights and sentiment analysis

Used embedded AI to analyze tone, recommend follow-up actions, and highlight trends in customer issues.

Launched a self-service portal

Allowed customers to find answers independently using AI-powered search. This reduced agent workload and improved overall satisfaction.

Improved performance visibility

Rolled out real-time dashboards and AI-based insights to help leaders monitor agent performance, track case trends, and optimize staffing decisions.

           Business Benefits

LTM’s AI-enabled case-management solution delivered measurable improvements across customer service, operational efficiency, and agent performance. The centralized Dynamics 365 platform, combined with embedded AI, automation, and real-time insights, enabled the client to scale its service operations while enhancing the customer experience.

Higher customer satisfaction

Achieved a 15–25% improvement in customer satisfaction (CSAT), supporting stronger loyalty and positive referrals.

Better first-contact resolution

Delivered a 20–30% increase in first contact resolution (FCR), improving agent efficiency and reducing repeat interactions.

Improved agent productivity

Realized a 25–40% boost in productivity through AI-powered guidance, automated workflows, and contextual data access.

Faster case resolution

Reduced case-resolution times by 20–35% through intelligent routing, AI recommendations, and real-time collaboration.

Greater operational efficiency

Achieved a 20–30% improvement driven by process automation, centralized data, and AI-driven analytics.

Increased self-service adoption

Saw a 30–50% rise in self-service usage due to the AI-enabled knowledge base and customer portal.

Improved SLA compliance

Enhanced SLA adherence by 10–20%, reducing escalations and improving service consistency.

Higher customer retention

Delivered a 10–15% improvement in retention through faster, more consistent support.

Lower cost per case

Reduced the cost per case by 15–25%, driving significant operational savings.

Faster insights and decisions

Improved decision-making speed by 20–30% through AI-powered dashboards and real-time performance insights.