Insurance Edge speaks with Malte Dieckelmann, Senior Vice President at Hyland, about how AI and intelligent automation are transforming claims, underwriting, and customer service, and why the insurer of the future will be powered by agentic AI.
Q1. What are the biggest content and data challenges insurers face today?
Insurance organisations have no shortage of data; in fact, they’re drowning in it. The real challenge is context. Critical information is often spread across disconnected systems, legacy platforms, scanned PDFs, emails, and policy documents. The result is that teams spend too much time searching for information and not enough time using it to make decisions.
Insurers are also under constant pressure to conform to evolving regulations. When you combine fragmented content with complex compliance demands, inefficiencies and risks multiply. The organisations getting ahead are the ones treating content as a strategic asset; investing in platforms that unify, structure, and surface the right data at the right time.
Q2. How is AI changing the way insurers think about automation?
The insurance industry is moving beyond traditional process automation, which was about speeding up repetitive tasks. Enterprise AI agents now enable insurers to think about automation in terms of judgment and reasoning. These systems can understand information, apply logic, and make context-based decisions within a workflow.
When dealing with claims, enterprise agents can evaluate documents, identify anomalies, or flag missing details in real time, all without human input. In underwriting, it can rapidly analyse applicant data to identify missing information, policy data, and risk profiles to improve pricing accuracy and reduce manual workloads. Meanwhile, in customer service, AI-driven content intelligence allows insurers to respond to customer queries faster and more consistently, ensuring every interaction is informed by the full context of the policyholder’s history.
It’s intelligent automation that goes beyond “if X, then Y.” It’s reasoning at enterprise scale, and that’s a fundamental shift for the industry.
Q3. Many insurers already use automation – what makes agentic AI different?
Traditional automation follows a script; it simply does what you tell it to do. Agentic AI doesn’t need a script; it can interpret, learn, and act autonomously based on context. That’s a huge shift.
For example, in a claims process, traditional automation might extract data from a form and move it into a system. An enterprise agent goes several steps further: it can read the claim, assess supporting documents, cross-check data against policy details, identify anomalies, and even suggest next steps or escalate exceptions automatically.
At Hyland, we’re bringing these capabilities to life through our Content Intelligence technologies within the cloud-native Content Innovation Cloud. Our platform empowers insurers to harness unstructured data, apply reasoning, and combine it with intelligent automation to create workflows that evolve as business needs change.
Q4. What does being “AI-ready” really mean for insurance businesses?
AI-readiness starts with a strong foundation — ensuring enterprise data, infrastructure, and workforce are prepared for AI. This includes having high-quality data, robust governance, ethical practices, and upskilled teams to enable secure, responsible, and impactful AI implementation.
Insurers are realising that they can’t just plug AI into legacy systems and expect transformation. You need to prepare your data, modernise your content ecosystem, and build governance frameworks that ensure AI acts responsibly and adheres to compliance requirements.
The good news is that this readiness work isn’t abstract, it delivers a clear foundation for success, growth and measurable ROI. By improving interoperability and visibility across systems, insurers reduce operational drag right away. Then, when they deploy agentic AI, they’re already set up to see faster and more measurable results.
Q5. Where are insurers seeing the fastest ROI from AI and intelligent automation?
For insurers, adopting AI and intelligent automation is likely to bring rapid ROI to areas including claims management, underwriting, and customer service. These areas rely heavily on unstructured data, the perfect use case for AI-driven reasoning.
Take claims processing for example. Historically, it could take days for a claim to move through document review, validation, and approvals. Intelligent automation powered by agentic AI can support straight-through processing, reduce cycle times and identify incomplete or inconsistent data — routing exceptions automatically.
In underwriting, AI accelerates risk assessment by synthesising data from multiple sources, helping insurers price more accurately while reducing the time to quote.
But ROI isn’t just about speed or cost. The real impact comes from enabling staff to focus on higher-value, customer-facing work. At its heart, insurance is an industry dependent on people and exemplary customer experiences. Empathy, service, and relationship-building are the qualities driving organisations forward. AI amplifies that human capability.
Q6. How does the cloud fit into the future of AI and automation in insurance?
Cloud-native architecture is essential for any insurer that wants to scale AI securely and efficiently. It offers the flexibility and computing power needed for agentic systems, but it’s also the key to continuous improvement.
With on-prem systems, innovation tends to move in big, disruptive upgrades. In the cloud, AI models and automation tools can evolve in real-time, continuously learning from data, refining performance, and enhancing decision-making.
It also changes how insurers manage compliance and governance. When you build automation in the cloud, you can streamline reporting and support adherence to regulatory compliance rules. That ability is critical in a highly regulated industry like insurance.
Q7. What does the “insurer of the future” look like?
The insurer of the future will be agentic, data-driven, and customer-centric. It will operate in real time, using content intelligence to make proactive decisions, from claims triage, to risk evaluation, to customer communication.
AI will take on much of the heavy lifting behind the scenes, surfacing insights and opportunities automatically, while human teams focus on strategy and service. The workforce will be augmented, not replaced.
Ultimately, success will hinge on how well insurers connect their content, automate their workflows, and embed reasoning into their operations. Those that can bring all three together will reduce costs and improve customer satisfaction, whilst redefining what’s possible in the industry.
Q8. For leaders just starting their AI journey, what’s the best first step?
Kicking off your AI journey should always start with your content. Look at where critical information lives, how it flows, and who can access it. The most powerful AI strategy begins with visibility.
Then, identify decision-heavy workflows — claims review, policy underwriting, compliance checks — and explore how intelligent automation could improve them. Even small gains in these areas can deliver significant ROI.
Above all, think strategically. Getting AI-ready is not a one-time project; it’s an organisational mindset. At Hyland, we see agentic AI as a long-term evolution, one that helps insurers unlock the full potential of their people and their data.
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