- Digital fluency: Proficiency in cost estimation software (e.g. ConQuest, Causeway), BIM tools, and cloud-based collaboration platforms is essential.
- Data analysis: Estimators must interpret historical data, market trends, and predictive models to refine estimates and anticipate cost fluctuations.
- Regulatory knowledge: Understanding environmental regulations, safety standards, technical standards and permitting requirements helps estimators account for compliance costs and avoid delays.
- Communication and collaboration: Estimators must work closely with cross-functional teams, presenting findings clearly and negotiating scope changes effectively.
- Risk management: Identifying uncertainties – such as supply chain disruptions or labour shortages – and building contingencies into estimates is now a core responsibility.
- Data centres, with their massive energy requirements and need for uninterrupted power, often require direct connections at EHV on to distribution and transmission networks operating at 132kV and above. Estimators must understand the unique challenges of EHV installations, including specialised equipment, installation standards, and spatial constraints.
- Renewable energy projects, such as large-scale solar farms and offshore wind installations, increasingly feed into the grid at EHV distribution and transmission-level voltages. Estimators must be able to assess the cost and complexity of connecting these sources to existing infrastructure, often across remote or difficult terrain.
- Technological advancement: The rise of smart grids, renewable energy systems, and digital twins has introduced new variables into utility projects. Estimators must understand these technologies to assess their impact on cost and schedule.
- Sustainability and ESG: Projects are increasingly evaluated through environmental, social, and governance (ESG) lenses. Estimators must factor in carbon footprints, energy efficiency, and long-term operational costs.
- Economic volatility: Fluctuating material prices, inflation, and global supply chain issues require estimators to be agile and informed.
- Workforce dynamics: Skilled labour shortages and changing workforce expectations influence labour cost assumptions and scheduling.
Framework agreements: structure, scale, and standardisation
Framework agreements in telecommunications, often established with major network operators or government bodies, are designed to streamline procurement and delivery across multiple projects over a fixed term. For QSs working within these frameworks, the requirements tend to be:- Standardised processes and pricing models QSs must navigate pre-agreed rates, scopes, and commercial mechanisms. This demands a deep understanding of schedule of rates (SORs), KPIs, and performance-linked incentives.
- Volume-based cost management With frameworks covering hundreds or thousands of sites, QSs focus on trend analysis, cost benchmarking, and economies of scale. Accuracy in forecasting and reporting is critical.
- Collaborative stakeholder engagement Frameworks involve long-term relationships with clients, subcontractors, and internal teams. QSs must be adept at managing expectations, resolving disputes, and maintaining consistency across regions.
- Compliance and governance QSs are expected to uphold rigorous audit trails, adhere to framework-specific governance protocols, and ensure alignment with overarching commercial strategies.
Stand-alone projects: flexibility, focus, and forensics
In contrast, stand-alone telecommunications projects (such as bespoke fibre rollouts, network overlays, or large diversionary works) require a different QS skillset:- Tailored commercial strategy QSs must build project-specific budgets, negotiate bespoke contracts, and manage unique risk profiles. Flexibility and commercial creativity are key.
- Detailed cost planning and control With no standardised pricing, QSs must conduct granular cost analysis, validate supplier quotes, and manage change control with precision.
- Hands-on project involvement QSs often work closely with site teams, engineers, and clients, providing real-time commercial support and adapting to evolving project scopes.
- End-to-end lifecycle management From tendering to final account, QSs on stand-alone projects oversee the full commercial journey, requiring strong documentation and negotiation skills.
Bridging the gap
While both roles demand core QS competencies – cost management, contract administration, and stakeholder engagement – the context in which these skills are applied differs markedly. Framework QSs thrive on consistency, scale, and process optimisation. Stand-alone QSs excel in adaptability, detail, and strategic thinking. At JSM, we recognise the value of both approaches and invest in developing QSs who can pivot between frameworks and bespoke projects. This versatility not only enhances career progression but also strengthens our commercial resilience in a fast-evolving telecoms landscape. Check out the latest Quantity Surveyor vacancies at JSM“The best Quantity Surveyors will be the ones who learn to work with AI, not around it.”
Matt Lonergan – Commercial Director
Meet the Manager | Matt Lonergan on Artificial Intelligence and the Evolving Role of the Quantity Surveyor
Matt Lonergan is Commercial Director at JSM, a qualified Quantity Surveyor with over 35 years’ experience in the utility sector, predominantly in Power. He leads high-performing commercial teams on some of the UK’s largest renewables and data centre connection projects, delivering major net zero programmes through both traditional and collaborative contracting arrangements.
Artificial Intelligence (AI) and the JSM Quantity Surveyor
The role of the Quantity Surveyor (QS) is evolving rapidly, driven in part by the construction industry’s adoption of Artificial Intelligence (AI). At JSM, our work is especially rewarding because we design and build the infrastructure that enables AI to grow, scale, and deliver its benefits.
At JSM, we design and build electricity substations and high-voltage cable routes that bring power from the National Grid or renewable sources, such as wind and solar, to data centres, often through highly congested urban environments. We also deliver the digital infrastructure that connects data centres to high-speed fibre networks and, ultimately, to end users.
How Main Contractor Quantity Surveyors Are Using AI
The type of AI most commonly used in this space is the Large Language Model (LLM). Built around text analysis, summarisation, and drafting, LLMs are a natural fit for the document-heavy work of a QS. Artificial intelligence is beginning to make a practical difference for main contractor quantity surveyors, not by replacing commercial judgement, but by helping teams process information faster and manage risk more consistently. It is important to reinforce that AI is a tool. It supports the QS, but does not make commercial decisions on their behalf. On live projects, AI is being used to support tender analysis, subcontract procurement, cost reporting, change control, and document review. The biggest value is often in reducing repetitive admin so QSs can spend more time on decision-making, negotiation, and protecting margin.
Practical Examples on Main Contractor Projects
One of the most useful applications is tender analysis. AI can review several subcontractor quotations and quickly highlight pricing gaps, exclusions, qualifications, and areas where returns are not directly comparable, making it easier for the QS to focus on the real commercial differences rather than manually aligning every line. It can also help with cost reporting by turning project data into a first draft of Cost Value Reconciliation (CVR) commentary, identifying unusual movements in forecast cost, value, or margin for further review. In change control, AI can compare drawing revisions, scan email trails and instructions, and help build a clearer record of how a change arose and where the cost impact sits. It is also proving useful in subcontract management, where it can summarise contract clauses, draft commercial correspondence, and flag risks around payment, contra charges, delay, and final account exposure.
Why It Matters
For main contractors, the benefit of AI is speed, consistency, and earlier visibility of risk. It can cut down the time spent reviewing packages, searching through documents, and drafting routine reports, while helping commercial teams spot issues sooner. That said, AI still needs careful oversight. Main contractor QSs remain responsible for interpreting subcontract terms, checking entitlement, validating records, and making sound commercial decisions based on the project context.
Used properly, AI becomes an assistant for the main contractor QS: speeding up analysis, improving reporting, and helping teams stay closer to cost, value, and risk throughout the life of the project.
In many ways, this feels like a similar wave of excitement to the arrival of Excel in the 1990s, when many in the industry were reluctant to go digital and change the way they worked. AI is not going anywhere, and the QSs who embrace it as a tool, and take the time to learn how to work with it, will be the ones who benefit most.
As JSM continues to grow, we are actively recruiting Quantity Surveyors to support our expanding project portfolio. If you are a QS looking for your next opportunity, we encourage you to explore current roles at JSM.