AI agents require a process layer
Enterprises need an "AI-ready" process layer for AI agents to work effectively, or else even the best tools will only deliver incremental gains, analysts say.
AI agents require a process layer because they need to understand instructions, take action, maintain context, and coordinate complex, data-driven automation. AI agent workflows combine reasoning from large language models, retrieval from memory systems, and actions through APIs or applications. This allows an agent to analyze information, select tools, and update its plan as the workflow progresses. AI agents can collect information from multiple sources like emails, databases, documents, and user activities to understand the current situation and identify what needs attention. The system analyzes gathered information using machine learning algorithms, makes a decision, and then takes the appropriate action. Unlike traditional automation, AI agents process data continuously and adapt in real-time, using feedback to improve. Enterprises are using AI in post-production for VFX, editing, sound, color correction, localization and restoration. AI can assist with tasks like rotoscoping, rendering, dialogue cleanup, and scene assembly. AI-assisted grading and consistency matching are also becoming more common. The best post-production workflows involve humans collaborating with AI, where machines handle the heavy lifting and humans steer the vision. AI can generate base layers, suggest edits, and create fast drafts, but human oversight remains essential for quality control. This hybrid approach allows for faster turnaround times and cost-efficiency without sacrificing creative control.
