12 June 2025

As artificial intelligence (AI) continues to evolve, a new wave of innovation is reshaping how organizations approach automation. Enter Agentic AI—a fast-emerging paradigm that combines the power of generative AI with autonomous decision-making. According to the new whitepaper “Agentic AI: The Next Level of Automation” by Lufthansa Industry Solutions (LHIND), the Germany-based industrial automation company, this next step in AI evolution enables companies to automate complex, multi-step tasks with unprecedented intelligence and autonomy.

MoveTheNeedle.news spoke exclusively with Julian Staub, Business Director for Intelligent Process Automation at LHIND, to understand what makes agentic AI so important, and how companies can prepare to embrace it.

What Is Agentic AI—and Why Now?

Agentic AI refers to AI systems that don’t just react to instructions, but plan, decide, and act independently within defined boundaries. These systems, often powered by large language models (LLMs) like GPT-4 or Claude, can reason through tasks, interact with APIs or databases, and carry out entire workflows without human hand-holding.

Unlike traditional automation—think RPA bots following a script or chatbots offering predefined replies—agentic AI operates more like a digital coworker. It can handle dynamic inputs, make context-based decisions, and adapt in real time.

“What makes it urgent now is the convergence of powerful LLMs, mature APIs, and the accelerating digitalization of business processes,” says Staub. “We’ve moved beyond experimentation. Agentic AI is enterprise-ready.”

🚀 From Task Support to Task Ownership

One compelling use case is in travel operations. Staub gives the example of a travel assistant agent that not only understands a customer’s intent to rebook a flight but also takes action—authenticating the traveller, checking the booking, comparing alternative flights, and completing the rebooking. No human intervention required. So beyond providing faster answers, agentic AI is about full-cycle task execution—from request to resolution.

Why Agentic AI Matters Now

The timing for agentic AI couldn’t be better, Staub emphasises. Organizations around the globe are facing:

• Labour shortages and rising personnel costs
• Increased customer expectations for instant service
• Growing complexity in operations, supply chains, and compliance
• A shift from digital transformation to AI transformation

Agentic AI offers a practical response to all of these pressures.

Real-World Applications from LHIND

Lufthansa Industry Solutions and its partners, including Cognigy, are already implementing agentic AI across several domains:

• ✈️ Travel & Logistics: Automating the Mail2Booking process and real-time package tracking
• 📞 Customer Service: Intelligent chatbots that resolve entire service tickets
• 🔄 Supply Chain: Reordering systems that autonomously track inventory and trigger resupply
• 🌐 IoT: Agents that interpret sensor data and take proactive action

Across the board, results show faster processing times, reduced manual workload, and more consistent service delivery.

Which Teams Benefit First?

Staub notes that agentic AI offers the most immediate value in areas characterized by repetitive, high-volume tasks. These include:

• 🧑‍💼 Customer Service – Automated handling of inquiries, bookings, and follow-ups
• 🧠 HR – Digital agents for onboarding, leave requests, and internal Q&A
• 📈 Marketing & Sales – CRM updates, lead qualification, and email outreach
• 🧑‍💻 IT & DevOps – Code generation, bug fixing, infrastructure support
• 🏭 Supply Chain & Operations – Demand planning, inventory tracking, and logistics coordination

How to Get Started with Agentic AI

For organizations ready to explore agentic AI, Staub offers four clear steps:

1. Build Internal Know-How
   Train leadership and teams on generative and agentic AI capabilities and risks.
2. Digitize and Structure Business Processes
   Ensure data and systems are accessible, standardized, and API-ready.
3. Establish Governance
   Set up safeguards, access controls, and define when human oversight is required.
4. Start Small, Scale Smart
   Identify repetitive use cases, estimate potential ROI, and run scalable pilot programs.

Looking Ahead: Specialized AI Agents Across the Enterprise

Staub believes that in just a few years, organizations will have dedicated AI agents for every major department—CFO agents managing budgets, HR agents onboarding staff, IT agents resolving incidents. These agents will be tightly integrated with enterprise systems and will act in coordination with humans. “Human-AI interaction will become more intuitive, helpful, and natural. Companies will look back at today’s manual workflows as inefficient and outdated. Agentic AI will not replace human relationships but will reshape how people collaborate with machines.”

Final Thoughts

Agentic AI represents a transformational leap in enterprise automation. It’s not just about speed—it’s about intelligence at scale. With tools now mature and the use cases multiplying, businesses that move early can create significant competitive advantages.