Kaitlin Marian

Special Guest Blog Post written by Parabola Founder & CEO, Alex Yaseen   Operators are under pressure. They’re expected to move faster, do more with less, and somehow keep everything running smoothly while their systems, tools, and data are a mess. Now, AI is adding a whole new layer. On one hand, it’s exciting. The potential is real. On the other, a lot of teams feel stuck. They know they should be using AI, but they’re not sure where it fits into their day-to-day work. These are the five questions I get asked most often—whether someone’s trying to get started with automation, or trying to figure out how AI actually helps. 1. Can we automate this, or is it too messy? This question usually comes from someone deep in a spreadsheet that was never meant to scale. The short answer is: yes, you can probably automate it. But the longer answer is that you’ll need to rethink the process first. AI can help summarize, transform, and clean data—but it won’t fix a broken workflow. That’s on you. The best teams pair structured automation with lightweight AI to get leverage. Think: using rules and logic to standardize a workflow, and AI…

Artificial intelligence (AI) is rapidly reshaping supply chain operations. From improving demand forecasting and inventory management to increasing operational efficiency, organizations across industries are investing heavily in AI to gain a competitive edge. Yet many companies overlook a critical requirement for AI success: access to trusted, high-quality data shared across the supply chain ecosystem. Supply chains have always relied on collaboration among suppliers, manufacturers, distributors, and retailers. In the AI era, that collaboration must become more intelligent. Organizations need timely, secure data exchange, both upstream and downstream, to provide AI systems with the information required to generate accurate insights and recommendations. When suppliers share real-time information about inventory levels, delivery schedules, and raw material quality, manufacturers can improve planning, reduce risk, and respond more quickly to disruptions. Likewise, when retailers share data about customer demand, inventory positions, and satisfaction levels, manufacturers can better align production and distribution with actual market needs. The result is a leaner, more agile, and more profitable supply chain. Despite these benefits, many organizations are still hesitant to share data. Concerns about security, intellectual property protection, competitive exposure, and integration complexity continue to create barriers. However, these challenges can be addressed through strong data governance, clear…