Agentic AI

Agentic AI: The Next Frontier in Business Transformation

The AI Maturity Gap: A Wake-Up Call for Businesses

Despite massive investments in AI, only 1% of companies believe they’ve reached full maturity, according to recent data. Even with billions poured into Generative AI, Capgemini reports that just 24% of organizations have scaled it across most functions—meaning 76% are still experimenting without significant impact.

Enter Agentic AI—the next evolution in artificial intelligence. Unlike today’s reactive, prompt-dependent AI, Agentic AI systems operate autonomously, making decisions, adapting to changes, and executing workflows with minimal human intervention. These agents combine reasoning with automation, transforming not just customer experience (CX) but also revolutionizing how employees work.

From firsthand experience in developing proof-of-concepts (PoCs) for incident management, we’ve seen how Agentic AI enhances employee experience (EX), which in turn drives better customer outcomes. The link between EX and CX has never been stronger—improvements in one directly fuel progress in the other.

The Internal Revolution: Elevating Employee Experience

Agentic AI shifts from rule-based automation to goal-driven autonomy. These agents learn from outcomes, adapt in real time, and make decisions within defined parameters—freeing employees from repetitive tasks and enabling strategic work.

Transforming Incident Management

We recently worked with a client to develop an Agentic AI solution for Major Incident Management (MIM)—a critical process where delays can lead to revenue loss and reputational damage. The goal? Reduce root-cause identification and resolution time for high-priority incidents (P1/P2).

While full results remain confidential, early indicators show:

Technical Gains

✔ Faster detection & response
✔ Consistent troubleshooting
✔ Preserved institutional knowledge
✔ Parallel task processing

Efficiency Improvements

✔ Reduced Mean Time to Resolution (MTTR)
✔ 24/7 operations without fatigue
✔ Automated documentation
✔ Optimized human resource allocation

Business Impact

✔ Better EX & CX
✔ Lower operational costs
✔ Reduced risk exposure

Beyond Incident Management: Vodafone’s AI Leap

Vodafone’s hybrid GenAI strategy is already unlocking efficiencies in network management, with AI agents like VINA enabling autonomous operations. Partnering with Google Cloud, Vodafone uses GenAI for network automation, including image-based site assessments for solar panel installations.

Additionally, Vodafone is deploying Agentic AI with ServiceNow to predict and mitigate service disruptions, improving both employee workflows and customer service.

The CX Cascade Effect: How Internal AI Elevates Customer Experience

When internal processes become smarter and faster, customers reap the benefits—through faster resolutions, proactive support, and seamless service.

The Cascade in Action

Faster incident resolution → Improved service reliability
Automated escalation → Reduced downtime & wait times
Predictive issue detection → Proactive customer notifications

Vodafone’s £140M investment in SuperTOBi (a GenAI-powered chatbot built on Microsoft Azure OpenAI) has cut response times and enhanced answer quality. Meanwhile, AI tools analyzing call success rates are helping create “super agents” who improve with each interaction.

Other companies seeing success:

Wiley: 40% improvement in self-service efficiency with Agentforce Service Agents
The Adecco Group, OpenTable, Saks: Deploying Agentic AI for CX automation

This shift toward anticipatory service—where AI predicts issues before they arise—is becoming a competitive necessity.

The Future: Orchestrating AI Agents at Scale

The next frontier is connecting multiple AI agents across internal and customer-facing workflows, enabling end-to-end automation.

A Framework for Orchestration

Detection & Response: AI anticipates and resolves disruptions.
Seamless Human Handover: Full context transfers when escalation is needed.
Continuous Learning: AI improves with every interaction.

Real-World Success Stories

Dreamforce 2024: Over 10,000 autonomous agents deployed, achieving:
- 15% faster case handling (Engine)
- 70% autonomous chat resolution (1-800Accountant)
- 22% retention boost (Grupo Globo)
Telcos (Vodafone, Lumen, Telkomsel): Using Microsoft 365 Copilot for integrated customer support

Lessons from the Field: How to Succeed with Agentic AI

While enthusiasm is high, most companies struggle to extract real business value from GenAI. Agentic AI requires a new mindset. Here’s what works:

✅ Start with well-defined processes (high-volume, measurable tasks)
✅ Maintain human oversight (security, compliance, risk mitigation)
✅ Prioritize change management (training, communication, overcoming resistance)
✅ Build governance frameworks (role-based access, audit trails)

Preparing for the Agentic Future: Strategy Over Scale

Agentic AI adoption is accelerating fast (Slack reports 233% growth in AI usage in six months). Companies must act strategically:

🔹 Pilot First: Vodafone & Google Cloud’s 2024 hackathon generated 13 real-world use cases—proving rapid experimentation works.
🔹 Invest in Platform Capabilities: Pre-built agent skills speed deployment.
🔹 Focus on Business Outcomes: This is not just efficiency—it’s transformation.

Some firms are even exploring “zero-FTE” departments (fully AI-operated). But the real opportunity lies in human-AI collaboration, not replacement.

Final Thoughts: The Competitive Edge Goes to Early Movers

Agentic AI isn’t just an incremental upgrade—it’s a paradigm shift toward autonomous, intelligent workflows. Companies that adopt early will outperform competitors in both employee productivity and customer satisfaction.

The future isn’t about managing AI—it’s about collaborating with AI agents that think, act, and optimize in real time.