Implementing or optimizing Applied Epic is rarely a plug-and-play project. Customization is often necessary to align the system with your agency’s unique workflows, compliance needs, and customer service models. But with great flexibility comes complexity—especially for project managers tasked with balancing stakeholder expectations, technical constraints, and timelines.

Data migration is one of the most critical—and often most underestimated—components of any Applied Epic project. Whether you're moving from a legacy system like TAM or migrating from another platform entirely, mishandling the transition can lead to lost records, operational downtime, and compliance risks.

Applied Epic is the cornerstone of operations for many insurance agencies, providing a unified platform to manage customer relationships, policy administration, accounting, and reporting. For project managers leading system implementations, migrations, or enhancements involving Applied Epic, a solid understanding of its capabilities and challenges is crucial for delivering successful outcomes.

Digital transformation can unlock tremendous value—improved customer experience, operational efficiency, and innovation. But for every success story, there are many more that fall short due to avoidable missteps. Having led enterprise transformation programs across industries like healthcare, finance, and manufacturing, I’ve seen the common traps companies fall into—and how to steer clear of them.

Digital transformation isn’t a one-time initiative—it’s a continuous evolution. As technology, customer expectations, and market conditions shift, organizations must become more responsive, resilient, and adaptable. That’s where Agile and DevOps come in. When properly implemented, these two practices form the engine of continuous digital transformation—turning strategy into speed, and vision into value.

Digital transformation is no longer just a technical initiative—it’s a business imperative. But while the buzzwords fly, executives often ask one critical question: “What’s the ROI?” Having led enterprise transformation programs in industries from healthcare to finance, I’ve seen the difference between projects that inspire executive confidence—and those that don’t. The key? Measurable outcomes.

The promise of digital transformation is exciting: agility, scalability, innovation, and improved customer experiences. But the path from legacy systems to cloud-based platforms is rarely a smooth ride. Having led large-scale digital transformation initiatives across healthcare, finance, and industrial sectors, I’ve seen firsthand the challenges—and the rewards—of migrating from on-premise legacy systems to modern, cloud-native solutions.

Digital transformation has evolved beyond buzzwords—it’s now a survival strategy. But despite significant investment, many organizations still struggle to realize the full value of their digital initiatives.  As someone who has led cross-functional digital transformation programs across industries—healthcare, finance, energy, and manufacturing—I’ve seen what works (and what doesn't). In 2025, success isn’t just about technology; it’s about integrating the right mindset, methodologies, and measurable outcomes.

Daily standups, sprint reviews, retrospectives—Agile ceremonies are vital for maintaining rhythm, accountability, and transparency across development teams. But let’s face it: these meetings can easily become repetitive, disorganized, or unproductive. That’s where AI is stepping in—not to replace these touchpoints, but to make them smarter, faster, and more focused.

For years, the Project Management Office (PMO) has played a vital role in aligning project execution with business strategy. But as organizations scale and complexity grows, traditional PMO tools and processes can become bottlenecks. Enter Artificial Intelligence (AI)—not just a support tool, but a strategic asset reshaping how modern PMOs operate.

Artificial Intelligence (AI) is no longer just a buzzword—it’s becoming a competitive advantage in project management. Whether you’re overseeing complex software delivery, orchestrating marketing campaigns, or managing enterprise-wide change initiatives, AI is transforming how we plan, execute, and deliver projects.

Project management has always been about driving results through structure, coordination, and communication. For decades, tools like Gantt charts, WBS diagrams, and critical path analysis served as the backbone of delivery. But today, we’re entering a new era—one where artificial intelligence (AI), particularly generative AI, is reshaping the very nature of how projects are conceived, managed, and delivered.