AI Doesn’t Start with AI: What Entrust’s 16-Year Automation Journey Teaches About Enterprise Transformation
Artificial intelligence may dominate today’s technology conversations, but for Entrust, AI is the latest chapter in a much longer story.
During our recent webinar with Entrust’s Yannick Miaffo, Senior Director of Automation & E-commerce, and Russell Lane, Business Process Transformation Manager, they shared how Entrust spent more than sixteen years building the operational foundation that now allows the organization to scale AI with confidence.
Their message was refreshingly clear in that successful AI initiatives aren’t built on models, they’re built on process.
The Journey Started Long Before AI
When Entrust began its automation journey in 2009, the company wasn’t focused on generative AI. The challenge was much more fundamental.
Manufacturing operations relied heavily on paper-based processes, manual work instructions, disconnected systems, and long production lead times. Competitive pressure required the organization to improve efficiency while maintaining quality.
Rather than searching for a single transformational technology, Entrust focused on systematically eliminating friction across the business. That meant digitizing work instructions, connecting manufacturing equipment, integrating ERP systems, automating back-office workflows, and creating visibility into operations.
Over time, those incremental improvements created something much larger: a digital operating foundation.
Process Excellence Came First
One of the strongest messages from the webinar was that automation alone doesn’t create transformation. Rather than relying on whiteboards and sticky notes, Entrust uses process capture technology to document workflows directly from employees performing their work. Those processes are then optimized before automation begins.
This discipline creates several advantages:
- Standardized business processes
- Better governance
- Repeatable automation
- Higher-quality data
- Easier AI adoption later
As Russell noted, excellence is built “process by process” and sustained through executive sponsorship, governance, and continuous improvement.
Why AI Requires a Platform Strategy
As AI capabilities continue to evolve at an unprecedented pace, Entrust has deliberately avoided locking itself into a single model or vendor. Instead, the company has adopted what Yannick describes as a platform approach.
Rather than embedding business logic inside individual AI tools, Entrust keeps process orchestration at the center while integrating best-of-breed AI capabilities around it. This architecture provides flexibility to adopt new models as they emerge while protecting the organization’s core business workflows. It’s an approach that recognizes a simple reality: AI models will continue to change, but business processes shouldn’t have to.
Combining Automation with AI
One of the most practical examples shared during the webinar involved order booking.
Entrust had previously automated portions of the process using robotic process automation (RPA). While successful, the automation struggled when incoming purchase orders varied in format or quality. By introducing AI-powered document understanding, the company dramatically expanded what the automation could handle.
Instead of replacing automation, AI enhanced it. Deterministic automation continues handling structured, repeatable work while AI addresses ambiguity and exceptions. Human review remains part of the process whenever confidence falls below acceptable thresholds.
It’s a practical reminder that enterprise AI often succeeds by enhancing existing automation, not replacing it.
Governance Is Becoming a Competitive Advantage
Perhaps the most surprising takeaway was how much attention Entrust is giving to governance. Rather than racing to deploy as many AI use cases as possible, the team is investing heavily in:
- AI governance
- Security controls
- Cost monitoring
- Identity management
- Observability
- Human-in-the-loop validation
- Responsible AI policies
Yannick explained that understanding what agents are doing, measuring token consumption, monitoring cost, and implementing appropriate guardrails are becoming foundational capabilities for enterprise AI.
For organizations to move beyond experimentation, governance may become just as important as model performance.
Lessons for Organizations Beginning Their AI Journey
Entrust’s experience offers several practical lessons for organizations at every stage of AI adoption:
- Start with process, not technology.
- Build strong data and governance foundations.
- Invest in automation before expecting AI to scale.
- Treat AI as part of a broader business platform.
- Maintain flexibility by avoiding unnecessary vendor lock-in.
- Focus on measurable business value rather than technology for its own sake.
The Bottom Line
AI may feel like an overnight revolution, but sustainable transformation rarely happens overnight. Entrust’s sixteen-year journey demonstrates that organizations capable of scaling AI successfully are often the ones that have already invested in process excellence, operational discipline, and continuous improvement.
Technology may accelerate transformation, but foundations make it sustainable.
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