• • • AI • • •
RETHINKING RAMS WITH AI: IMPROVING CONSISTENCY, COMPLIANCE AND OPERATIONAL EFFICIENCY
BY KEVIN BIRD, CEO, SHOCKING ENERGY R
isk Assessments and Method Statements (RAMS) remain a fundamental requirement for safe electrical work on site.
From infrastructure upgrades to renewable installations, they form the basis of how risk is identified, controlled and communicated. However, as project volumes increase and compliance expectations tighten, the process of producing RAMS is becoming progressively more difficult to manage using traditional methods. Across the sector, many teams still rely on a familiar workflow: adapting previous documents, manually updating risk assessments and managing revisions and approvals across email and shared files. While workable at low volumes, this approach can introduce inconsistencies and make it harder to maintain a clear audit trail, particularly when multiple projects are running in parallel.
It is within this context that artificial intelligence (AI) is beginning to play a more practical role. Rather than replacing competent persons or safety professionals, AI is increasingly being used to reduce administrative effort and improve consistency in documentation, allowing engineers and managers to focus more directly on site- specific risks and decision-making. Early use cases have focused on drafting, where AI can generate structured starting points based on job type, environment and known hazards. This reduces reliance on outdated templates and helps ensure that key sections are not overlooked. However, the direction of travel is moving beyond simple content generation.
A more notable development is the ability to take existing RAMS or PDF documents and convert them into structured, reusable templates. This approach shifts the emphasis away from AI producing content from scratch, and towards
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enabling organisations to formalise and standardise the documents they already use. By breaking these documents into controlled sections and fields, teams can maintain alignment with internal best practice while improving consistency across different projects, clients and work types. At the same time, the way site data is captured and used within RAMS is beginning to evolve. Traditionally, information such as photographs, test readings, certificates and signatures has been collected separately and then manually inserted into documentation. This can be time-consuming and increases the risk of discrepancies between what happens on site and what is recorded. More integrated approaches now allow this information to be captured as part of the job itself and linked directly to the relevant sections of the RAMS. In effect, the document becomes a reflection of verified site activity rather than a retrospective exercise. This has implications not only for efficiency, but also for the reliability and traceability of the documentation.
Consistency is also being addressed through the use of structured templates and controlled content. By defining required sections and standardising key elements, organisations can reduce variation between documents produced by different teams. This is particularly relevant for contractors carrying out repeat work types across multiple sites, where maintaining a consistent approach to risk assessment is essential. Alongside this, version control and approval processes, long-standing challenges in RAMS management, are increasingly being incorporated into more structured workflows. Instead of relying on email chains and manually tracked revisions, changes can be recorded with clear attribution and timestamps, creating a more transparent audit trail. Drafts, approvals and final outputs can be managed as part of a single process, rather than as disconnected steps.
The final stage of the process is also becoming more controlled. Once reviewed and approved, documentation can be issued in a consistent format, with each version clearly defined and traceable. This is particularly important in
regulated environments, where the ability to demonstrate how and when documents were created, reviewed and updated is critical. While standalone AI tools can support elements of drafting and review, their impact is more limited when used in isolation. The more significant shift is taking place where AI is embedded within wider operational systems, allowing documentation to be generated as part of a connected workflow that links site activity, data capture and compliance processes. Within the energy and electrical contracting
sector, this type of approach is beginning to emerge through purpose-built field service platforms such as
JobWay.AI, developed by Shocking Energy. These systems combine template management, guided data capture and AI-assisted document assembly within a single environment, with version control and approvals handled as part of the same process. This reflects a move towards treating RAMS not simply as documents, but as controlled outputs of a wider compliance workflow. Despite these developments, the role of professional judgement remains unchanged. AI- generated outputs do not have site awareness and cannot replace the expertise of a competent person. All documentation must still be reviewed and approved in line with established safety procedures.
What is changing, however, is the level of administrative burden associated with producing and managing RAMS. As projects become more complex and regulatory expectations continue to rise, the ability to produce consistent, accurate and auditable documentation at scale is becoming increasingly important.
In this context, AI is not a replacement for established processes, but a tool for strengthening them. By introducing structure, reducing duplication and improving traceability, it offers a practical way to support compliance while allowing engineers and safety professionals to focus on managing risk where it matters most, on site.
https://shocking.energy electricalengineeringmagazine.co.uk
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