Marshall Tech
workflows and automationaiData HygieneData QualityAI Readiness

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.

On data quality as a prerequisite for AI

Nick Hugh

Founder, AI Expert & Fractional CTO, Marshall Tech

Nick Hugh, AI Expert & Fractional CTO at Marshall Tech, Sydney

Last updated:

Related resources

Move from this quote into the person, proof, and longer explanation behind it.

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 resource

Expert

Nick Hugh

Nick Hugh, AI Expert & Fractional CTO at Marshall Tech, Sydney

Updated 9 Apr 2026

Open resource

Case 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 resource

Expert insight

On AI readiness assessments for Australian SMBs

AI readiness isn't about having perfect data. It's about having accessible data. Most businesses score 40-60% on their first assessment, and that's completely fine. The gaps become your implementation roadmap.

Updated 20 Feb 2026

Open resource

Service

AI Consultant Sydney

Marshall Tech works as an AI consultant in Sydney for small and growing businesses that want practical AI tied to operations. We assess readiness, select the right use case, build the workflow, and add guardrails so AI systems are reliable, measurable, and usable in production.

Updated 9 Apr 2026

Open resource

Insight

AI Readiness Assessment Checklist for Australian Businesses

An AI readiness assessment evaluates four dimensions: data quality and accessibility, process maturity, team capability, and infrastructure readiness. Most Australian businesses score 40–60% on their first assessment. The gaps aren't blockers. They're the starting point for a practical implementation roadmap.

Updated 26 Feb 2026

Open resource