Case 19 / Strategic operating outcome

Mapping AI Automation Around Real Operational Risk

The useful AI opportunities were not the flashiest ones. They were the repetitive points where missed data could cost enquiries, time or payment.

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Client: Global leading height access platform manufacturer
Sector: Multi-department industrial business
Capability: AI roadmap, workflow design, marketing operations
Evidence: Strategic operating outcome

Platforms & tools

HubSpot Workflow and reporting
Smartsheet Quality workflow
LinkedIn Reporting source
Meta Reporting source

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Evidence note: Results retain the supplied evidence label and reporting context. Attributed or estimated results describe the available record, not an unsupported claim of causation.

The Challenge

The manufacturer had manual work across website testing, campaign reporting, catalogue checks, engineering project setup and ISO 9001 non-conformance reporting. The business wanted an AI roadmap, but unstructured experimentation could create security risk, disconnected tools and automation that nobody owned.

What I Did

I mapped the work before recommending technology. Commercial website journeys were broken into repeatable tests across product pages, carts, quote forms, emails and regional sites. Marketing reporting was mapped across Meta, LinkedIn, Google, Microsoft and HubSpot. Engineering intake, print-data validation and quality reporting were analysed for repetitive entry, missing-field follow-up and management escalation.

How I Did It

01: Prioritised use cases by business risk, frequency, effort and data sensitivity.
02: Separated safe monitoring and data work from higher-risk code or payment-system changes.
03: Designed human review points for claims, prices, SKUs, engineering data and AI scoring.
04: Mapped a mobile non-conformance capture flow from HubSpot to SmartSheet, reminders, management review and the business risk register.
05: Defined measurable pilots before considering wider automation.

The Result

The engagement produced a prioritised automation map tied to real operating pain rather than a list of novelty tools. It identified an immediate route for website journey monitoring, consolidated performance reporting, structured internal idea scoring and mobile quality capture. The business also gained a clear boundary: AI could accelerate collection and analysis, but high-risk technical and compliance decisions would retain controlled review.

Why It Matters

I approach AI as workflow and risk design. The model is only useful when the data, decision and owner are clear.

★★★★★ 5.0 Average from 5 Google reviews

“attentive to our needs as we grow”
David Patrick O’Riordan, RSGx Google review

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Next step

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