Using AI to Enhance Business Operations: The Executive Framework for Setting Your AI Strategy
Using AI well comes down to three decisions: which class of AI you buy, whether it runs on one platform or many, and which workflow you start with. Get those right and the program scales; skip them and it stalls like most pilots do. Slug: using-ai-to-enhance-business-operations
AI in Finance: Use Cases, Case Studies, and Where It's Going Next
AI in finance spans very different maturity levels. Fraud detection and trading are already mature, but the operational core, AP, payroll, treasury, compliance, and claims, is where autonomous agents are running in production today, and it's the fastest place for most finance leaders to prove value first.
The State of AI in Logistics: Use Cases, Case Studies, & Trends
Physical-network AI in logistics (routing, robotics, autonomous trucks) is a multi-year capital bet. Back-office AI, quoting, track and trace, freight audit, and customs, runs on existing systems and reaches production in weeks, which makes it the faster place to start.
AI In Supply Chain: Use Cases, Case Studies, and Trends
The physical side of supply chain AI (robotics, forecasting) is capital-intensive and multi-year. The faster win is the back office, quoting, track and trace, freight audit, and customs, where agents reach production in weeks and pay off almost immediately.
What is Enterprise AI? The Executive's Guide to Practical, ROI-Positive AI Deployments
Most "AI agents" still need a person to babysit them when something falls outside their training. Enterprise AI is different: it escalates what it's unsure about, turns corrections into policy updates through two learning loops, and gets more accurate over time instead of drifting.
Your Engineers Should Not Be Building Invoice Agents
For a serious engineering organization the question is never whether it can build an agent, it is what maintaining that agent costs in years two and three. Reindeer argues the right model is to buy the platform and keep ownership of the operation: the context, the policies, the evaluation criteria, and the decision to promote a revision to production.
Your AI Agents Have No Air Traffic Control
Enterprises are deploying AI agents faster than they're building the oversight to manage them, and Reindeer argues this calls for a new discipline, Agent Operations, built the same way air traffic control was built once the skies got too crowded for pilots to self-coordinate.
Enterprise AI Is Built for the Wrong Moment
Reindeer builds agents to handle the part of the work that comes after go-live, catching exceptions as they happen and revising their own logic as the underlying workflow changes, instead of freezing in place like traditional automation.
Reindeer Now Enables Agentic Automation for AS/400 Green Screens
Reindeer agents can now operate IBM i green-screen applications through the 5250 protocol, reading real field structure to automate legacy workflows that previously required manual work or custom integrations.
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