How GoConnectIT Used Workshops to Introduce AI to Their Process Without Slowing Field Operations

However, as GoConnectIT targeted more countries, such as Germany, and the volume of installations surged, a new challenge emerged. Each photo submitted by subcontractors had to be manually reviewed by back-office teams to confirm correct cable placement, FTU installation, and compliance with standards. What started as a smart control mechanism had turned into an operational bottleneck.

Field technicians were uploading a large number of photos and reports daily. Verifying every image by hand would have stretched validation teams thin. The leadership team saw the danger: without automation, quality assurance could limit GoConnectIT’s ability to scale. They needed a way to validate installations faster and more reliably, without disrupting live operations or breaking a system that had worked for so long.

The company needed to automate parts of the validation process. But the “how” was less clear. GoConnectIT needed a structured way to explore what was feasible, what data was required, and how to integrate AI into their existing platform without jeopardizing ongoing fibre installations.

DAC.digital as a trusted partner for AI discovery and design

To tackle these challenges, GoConnectIT partnered with DAC.digital, so the stakeholders and employees could understand how AI could help and get a practical, low-risk roadmap for a full rollout. Instead of developing the AI model right away, the focus was on designing a scalable architecture to support the scale and ambitions of the business.

DAC.digital brought deep expertise in AI, Machine Learning, and cloud systems, combined with a solid background of understanding the business needs. The team helped GoConnectIT connect business goals, data readiness, and technology design, so the AI initiative would deliver operational value that was measured in ROI.

Structured exploration led to risk-free development roadmap

The collaboration started with a two-day AI Workshop that brought together stakeholders and experts.

Day 1: Team alignment and outcome plan

The team focused on using AI to accelerate approval cycles. Current processes and integration points were mapped to identify inefficiencies and decide where AI could deliver the greatest impact

Day 2: Solution design

Workshop participants explored high-value use cases, including:

• Photo validation: Automated checking of installation and inspection images, with confidence thresholds and human review for borderline cases.
• Appointment automations: Parsing customer replies to confirm or reschedule visits automatically.
• Standardized QA rules: Streamlining quality assurance and citizen-facing workflows.

Through structured discussions and rapid design sessions, the team converged on a Phase-1 pilot: automated photo validation for a select set of installation images. Supporting materials were developed in parallel, including a reference architecture, integration blueprint, and data evaluation plan, all aligned with GoConnectIT’s Google Cloud and Kubernetes environment.

By the end of the workshop, GoConnectIT had a de-risked, measurable plan for AI deployment, complete with KPIs, acceptance criteria, and a controlled rollout path—ready to move from concept to pilot with confidence.

The company got a predictable approach to AI adoption and gain clarity of what success means

By the end of the workshops, GoConnectIT had a validated roadmap for AI adoption, grounded in measurable outcomes and operational reality.

The team prioritized automated photo validation as the first pilot, focusing on installation images that consumed the most human review time. Together, they defined precision and recall thresholds, “borderline” handling logic, and a human-in-the-loop review path to ensure reliability from day one.

A reference architecture and integration blueprint detailed how AI validation would run as an independent service, connected via APIs to GoConnectIT’s internal backend.

Key KPIs established to measure impact

KPIs, or Key Performance Indicators, are measurable goals that track whether a solution delivers the intended results. Setting KPIs is essential in any innovation or AI project because they translate a vision into measurable outcomes. They define what success looks like. For GoConnectIT, KPIs focused on technical accuracy and operational goals. They were as follows:

• Precision and recall per photo class – how accurately the AI model identifies correct or faulty installations.
• Latency from upload to verdict – how quickly the system returns a validation result after a photo is submitted.
• Reduction in manual checks and technician revisits – how much time and rework the automation helps to save.
• Improved first-time-right installation rates across pilot regions – how many installations are completed correctly on the first attempt.

Because of those KPIs, the leadership team could make confident decisions on AI deployment based on a clear understanding of what success would look like and how to track it.

The collaboration continued with a full rollout

GoConnectIT left workshops with an execution-ready framework that enabled innovation in carefully measured phases, each tied to business KPIs.

The result is a future where AI is embedded in everyday fibre rollout operations, continuously improving reliability, reducing rework, and enhancing customer satisfaction. If you want to read about the full rollout, read our previous case study: Automated Installation Checks with AI and Computer Vision that Achieved 90% Accuracy.