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AI Agent
An AI agent is an autonomous software system that uses large language models to perceive its environment, make decisions, and take actions to achieve goals. Unlike chatbots, agents can execute multi-step workflows, use tools, and learn from feedback.
Usage context
This term is used across 0 Marshall Tech knowledge surfaces. Use the related resources below to move from the definition into proof, implementation detail, and commercial context.
Related resources
See this term used in guides, case studies, services, and decision support.
Insight
Data Hygiene Guide: Getting Your Data AI-Ready
Data hygiene is the practice of ensuring your business data is accurate, consistent, complete, and accessible. It's the prerequisite for AI implementation, reliable automation, and trustworthy reporting. Businesses with poor data hygiene waste 20–30% of employee time on manual data wrangling and get unreliable results from any AI or automation tools they deploy.
Updated 26 Feb 2026
Open resourceCase study
Adapt Health: Fractional CTO & AI Integration
Adapt Health needed senior technical leadership to guide new product development and integrate AI and automation into their health technology platform. Marshall Tech provided fractional CTO services, architecting new features, building custom AI workflows, and establishing technical processes that allowed the team to scale efficiently.
Updated 26 Feb 2026
Open resourceExpert
Nick Hugh
Nick Hugh, AI Expert & Fractional CTO at Marshall Tech, Sydney
Updated 9 Apr 2026
Open resourceInsight
AI Agents Explained: What Australian Businesses Need to Know in 2026
AI agents are software systems that can plan, reason, and take actions to accomplish goals with minimal human supervision. Unlike chatbots, agents can use tools, access databases, call APIs, and chain multiple steps together. In 2026, they deliver real ROI in customer support, data processing, content workflows, and internal knowledge management.
Updated 26 Feb 2026
Open resourceInsight
MCP Explained: What Model Context Protocol Means for Your Business
Model Context Protocol (MCP) is an open standard that lets AI agents connect to external tools, databases, and APIs through a universal interface. Think of it as USB for AI: one protocol, any tool, any model. MCP eliminates vendor lock-in and enables businesses to build tool integrations once and use them across any AI platform.
Updated 26 Feb 2026
Open resourceExpert insight
On data quality as a prerequisite for AI
Before you invest in AI, automation, or a new CRM, answer this: is your data clean enough to be useful? If your team maintains shadow spreadsheets, the answer is no. Fix data first, then automate.
Updated 18 Jan 2026
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