Microsoft Expands AI Customer Service with L&G Contact Center Deal
Legal & General is partnering with Microsoft to build an AI-enabled customer service platform for 12.4 million customers. The system runs on Dynamics 365 Contact Center with Copilot built in, giving agents a real-time view of each customer and guiding the next best action in the flow of work.
Phase one covers workplace savings, retail protection, and annuities, with more product lines to follow. The goal is clear: simplify service, reduce hand-offs, and improve outcomes for customers and agents.
What this means for support teams
- Single workspace: Fewer tools, fewer transfers. Agents get a consolidated view of accounts, history, and context across channels.
- Live guidance: The platform analyzes conversations, highlights relevant tools or content, and suggests next steps while the call is in motion.
- Sentiment and vulnerability cues: Tone analysis flags potential risks or sensitive situations - crucial for pensions and insurance.
- Admin offload: Copilot handles transcription, case summaries, and follow-up prompts so agents can stay with the customer instead of toggling screens.
- Channel outreach: Outreach prompts match the customer's preferred channel to keep momentum after the interaction.
Why this deal matters
L&G is already modernizing service - including a fully digitized claims process that cut average claim times by nearly two weeks and a top-rated pensions app. This move extends that effort into frontline operations with AI embedded at the core.
Microsoft's Rob Smithson described Copilot as the interface that ties business apps together and said the contact center is "being built with generative AI from the ground up," noting improvements in measures like net promoter score inside Microsoft's own care operations.
For L&G and peers, that means agent assistance, sentiment analysis, and summaries aren't add-ons - they're standard. As Darren Hardman of Microsoft UK & Ireland put it, the goal is more personalized, efficient, and secure support at scale.
The bigger picture: Microsoft's CX approach
Microsoft is positioning Copilot as the connective layer across Dynamics 365 and ERP. The vision: an agent-led, human-directed model where digital agents handle complexity behind the scenes and people focus on empathy, problem-solving, and proactive engagement.
Smithson summed up the customer impact: the worst experience is repeating yourself to a company that doesn't recognize you or why you're calling. With richer data and context, agents can respond faster and with confidence.
How to put this into practice
- Pick a pilot slice: Start with one product line (like L&G's workplace savings) and a defined set of workflows.
- Wire your data: Connect CRM, policy/admin systems, knowledge bases, and call transcripts to feed real-time context.
- Define risk flags: Set clear rules for vulnerability detection, escalation paths, and compliance notes.
- Rewrite your QA: Use AI-generated summaries to audit outcomes, not just handle time. Calibrate prompts and guidance with senior agents.
- Measure ruthlessly: Track AHT, FCR, transfer rate, NPS/CSAT, escalations, and agent effort. Compare AI-assisted vs. non-assisted interactions.
- Train for live co-piloting: Teach agents how to accept, adapt, or override AI guidance during calls, and how to correct summaries.
Key takeaways for support leaders
- Consolidation beats customization: fewer tools, clearer workflows, faster onboarding.
- Real-time guidance reduces cognitive load and increases consistency.
- Sentiment signals are only useful if tied to clear action and escalation logic.
- Admin automation frees minutes per interaction - reinvest that time in outcomes, not wrap-up.
If you want a quick primer on Microsoft's approach, see Microsoft Copilot and Dynamics 365.
Planning to skill up your team for AI-assisted support roles? Explore role-based training options at Complete AI Training.
Bottom line
L&G's move with Microsoft signals where contact centers are heading: context-rich, AI-assisted, and human-led. The winners will combine strong data foundations, tight workflows, and agent coaching to deliver faster, more human customer support at scale.
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