Technology and Organisational Readiness: The Two Forces That Decide Your Agentic AI Future If you followed the first article in this series on agentic AI maturity, you now have a mental map of how organisations move from basic text generators to fully autonomous systems. The model is deliberately simple: five stages of maturity, each with […]

Prologue The confusion is understandable. In less than three years, we’ve progressed from AI systems that simply predict the next word in a sequence to intelligent agents that observe environments, form plans, execute complex workflows, and make autonomous decisions. The terminology has exploded: chatbots, copilots, agents, agentic AI, autonomous systems. Each term carrying different implications […]

Agentic AI is a new class of digital coworkers that can understand goals, reason across steps, and execute actions. This article explores how COOs can redesign operations for human-agent collaboration. Originally published on Brainfood Training.

End-of-year review on how agentic AI is reshaping customer contact, service, sales and marketing based on 2025 research and reports. Originally published on Brainfood Training.

Analysis of the NVIDIA-Palantir partnership and its impact on enterprise AI deployment and competitive dynamics in operational AI. Originally published on Brainfood Training.

Organisations leveraging AI for augmentation achieve 3x higher revenue growth per employee than those pursuing pure automation. Yet the headlines focus on redundancies, not on the organisations building stronger teams through human-AI partnership. The Strategic Choice There are two paths: Directive (AI takes over) or Augmentative (AI supports humans). The choice matters profoundly for long-term […]

The trouble with LLMs is their inconsistency. In one experiment, researchers asked an AI the same question 1,000 times and got 80 completely different answers. This isn’t about creativity—it’s a real technical problem that impacts reliability. The Root Cause Researchers at Thinking Machines discovered that LLM inconsistency depends on how many other people are using […]

GenAI impact on entry-level contact centre roles: How organizations can protect early-career pipelines through intentional augmentation strategy.

Understanding the 5-stage Agentic AI maturity model helps distinguish true autonomous agents from rebranded automation and clarifies realistic implementation timelines.

Vulnerable customers often prefer AI for sensitive topics like debt collection because of reduced shame and judgment—revealing new rules for customer contact strategy.

Humanizing language about AI misleads decision-makers. Understanding the technical reality behind AI capabilities prevents unnecessary fear and enables better strategic decisions.

Agentic AI will transform customer contact through autonomous agents, proactive engagement, and self-evolving workflows—a comprehensive roadmap for 2025-2030.