Tag: AI Frameworks
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Model Context Protocol (MCP) is the missing link between AI tools and real business data. Instead of building dozens of custom integrations, teams use MCP to connect AI systems to CRMs, databases, and APIs through a single standard. This guide explains how it works, why it matters, and how leaders can use MCP to speed…
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Most companies stall in pilots, treating AI agents as side projects. An effective AI Agent Strategy integrates agents into workflows, aligns them with KPIs, and governs their use. This article outlines five principles leaders need to move beyond experiments and deliver business results that scale with confidence.
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In this AI case study, I show how I applied automation at Lia’s Flowers to move from gut-based planning to a structured system built on forecasting, delivery optimization, and dashboards. My approach reduced waste by 20%, improved on-time deliveries by 15%, and freed staff to focus on design and service. The result demonstrates my ability…
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AI is no longer optional, but adoption often fails when workflows break down, budgets scatter across too many tools, and trust erodes. This article outlines a six-step AI workflow process that helps leaders integrate systems, target the right tasks, measure trust, and assign accountability. Learn how to turn AI from a bolt-on feature into a…
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The problem wasn’t the AI model – it was the lack of continuity. Each interaction started from scratch, with no structured way to carry forward knowledge, context, or organizational intelligence. Without memory or role awareness, the system failed to evolve with your business. The result? Fragmented answers, hallucinated logic, and user frustration.
