Agentic AI and the Insurer of the Future: A Conversation with Hyland's Malte Dieckelmann
Insurance runs on decisions - claims, underwriting, service. The problem isn't a lack of data; it's too much of it scattered across legacy systems, scanned PDFs, emails, and policy docs. We spoke with Malte Dieckelmann, Senior Vice President at Hyland, about how agentic AI turns that chaos into context and what a practical path to AI-readiness looks like.
The content and data problem: context is the constraint
Insurers are drowning in data but starving for context. Critical details sit in disconnected systems, so teams spend hours searching rather than deciding.
The leaders treat content as a strategic asset. They unify, structure, and surface the right information at the right time - and they build for compliance from the start, reducing risk while improving speed.
From scripts to reasoning: automation grows up
Traditional automation sped up repetitive clicks. Agentic AI adds judgment. It can read, interpret, apply logic, and act within a workflow.
In claims, agents review documents, flag gaps, and escalate edge cases in real time. In underwriting, they synthesize applicant and policy data to sharpen risk selection and pricing. In customer service, AI-driven content intelligence brings full policyholder context to every interaction.
What makes agentic AI different
Rules-based bots follow instructions. Agentic systems understand the task, evaluate context, and take next steps on their own.
Example: a bot extracts fields from a claim form. An enterprise agent reads the claim, cross-checks policy details, spots inconsistencies, requests missing evidence, and routes exceptions. Hyland is enabling this via Content Intelligence inside its cloud-native Content Innovation Cloud - turning unstructured content into decisions that improve over time.
What "AI-ready" really means
AI-readiness isn't a plug-in. It's data quality, governance, ethics, security, and people. You prep content, modernise the ecosystem, and set clear rules on how AI operates.
This groundwork pays off right away through interoperability and visibility across systems. Then, when you add agentic AI, outcomes improve faster and with less friction.
For a useful governance reference, see the NIST AI Risk Management Framework here.
Where ROI shows up first
Claims, underwriting, and customer service see the quickest gains because they depend on unstructured content and judgment-heavy workflows.
- Claims: Straight-through processing for clean cases, automatic flagging of incomplete or inconsistent files, faster cycle times.
- Underwriting: Faster risk assessment, fewer manual lookups, more accurate pricing, shorter time to quote.
- Customer service: Instant context, consistent responses, and fewer handoffs.
The real win: your teams spend more time with customers and complex decisions, less time chasing documents.
Why cloud-native matters
Cloud-native architecture gives insurers the scale and flexibility agentic systems need. Models and workflows can be updated continuously instead of in disruptive waves.
It also simplifies oversight. Centralised logging, audit trails, and policy controls make it easier to meet regulatory demands while improving agility.
The insurer of the future
Think agentic, data-driven, and customer-centric. Operations run in near real time: claims triage, risk evaluation, and communications all guided by content intelligence.
AI handles the heavy lifting behind the scenes, surfacing insights and suggesting next steps. People focus on strategy, empathy, and relationships. Costs drop. Satisfaction rises. The gap widens between organisations that connect content, automate workflows, and add reasoning - and those that don't.
Where to start
Begin with your content. Map where critical information lives, how it flows, and who can access it. Then pick decision-heavy workflows - claims review, underwriting, compliance checks - and pilot intelligent automation there.
Small gains compound. Set up governance early, upskill your teams, and build momentum with measurable wins. For structured upskilling paths, explore role-based AI learning options here.
Bottom line
Agentic AI isn't about replacing people. It's about giving insurers the context and reasoning they've been missing. Unify content, modernise the stack, and let AI handle the grunt work - so your teams can do the work that actually moves the business.
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