Arup and GHD pitch automation and AI

October 20, 2025|Kim's Blog, Marketing, Property, Selling|

Artificial Intelligence (AI) is having a fundamental impact on marketing and business development. Not least in the area of tendering and pitching. This post is based on an article in PM Magazine Winning work in the age of AI -How professional services firms are transforming proposal generation (July 2025) which is accessible to PM Forum members. It explores how Arup and GHD have used AI to transform their tender processes. Property marketing case studies: Arup and GHD pitch automation and AI.

This post reflects on the increased volume of pitches and RFPs while MBD teams remain the same – sometimes tackling dozens of pursuits each month. It is based on an article written by Mark Bilson, Chief revenue office at ikaun ikaun – Start automating your proposals and win more work today the AI powered pitch and proposal platform. The platform is also used by law firms Gowling WLG and Cohen & Gresser LLP.

A 2024 McKinsey report reported that over 70% of professional services buyers say the quality of the proposal has a “significant impact” on their selection decision. At the same time, Gartner data shows that the average proposal team spends over 60% of their time on manual content assembly and formatting – time that could been invested in strategic messaging, competitive intelligence or tailoring the submission to the client’s needs. The increased volume means MBD professionals must often choose between speed and quality. The reliance on outdated and fragmented processes means there is a structural bottleneck – costs real revenue and undermines their ability to scale.

Arup AI pitch automation

Arup Arup – Planning, designing, engineering the future – Arup – an 18,000 strong engineering and design consultancy was producing over 10,000 bids a year across its global offices.

Each bid required dozens of bespoke CVs and tailored project descriptions – much of the information sourced manually from legacy systems, shared drives and individual desktop files. The firm would spending millions annually in staff time just to assemble submissions.

Arup People is a global system used by more than 18,000 professional staff to manage CVs, project histories and areas of technical expertise. It integrates data from multiple legacy sources and enables real time collaboration across borders and business units.

CV generation is now semi-automated. Proposal teams can assemble complex, interdisciplinary submissions with unprecedented speed and precision.

For Arup, the AI capability has had a measurable impact. The time available for tailoring CVs has doubled, enabling deeper alignment between each submission and the client’s expectations. The quality and competitiveness of bids has improved, not by adding resources but by eliminating inefficiencies.

GHD AI pitch automation

GHD, GHD | Engineering, Architecture & Construction Services another global AEC firm with 11,000 professionals and operations across five continents faced a similar problem.

With more than 400 proposals submitted each month – teams were forced to rely on regionally siloed content, inconsistent templates and fragmented review processes. There was no scalable system to deploy that knowledge across opportunities.

At GHD the transformation focused on bid standardisation. The firm created a modular content library that allows proposal managers in Canada, the US, Australia and elsewhere to generate regionally compliant responses using a share foundation of approved content.

Each module, ranging from methodology statements to QA processes to bios, can be adapted by AI to reflect the specific client, jurisdiction or sector.

The team now begins each proposal with 60-80% of the content already drafted and contextually aligned.

Use of artificial intelligence (AI)

AI plays a pivotal role in these platforms, as a set of targeted, high impact capabilities.

Generative AI enables the rapid creation of bios, capability statements, project summaries and executive summaries by synthesizing structured firm data. This accelerates the content development process while ensuring consistency and accuracy across submissions.

Agentic AI ( see CIM’s hype-free guide to AI agents for marketers – Kim Tasso) goes further, It applies rules and patterns to automate complex decisions such as:

Bid/No bid analysis based on historic win rates, client behaviour and proposal complexity
Identification of gaps in credentials or compliance criteria
Pricing recommendations based on past engagements and sector benchmarks
Real time formatting of output to match specific client templates or procurement systems

AI pitch system choice and implementation

Both firms build these systems with adoption in mind. Templates, content library, expert finder tools and multilingual search features are embedded into workflows and not lawyered on top of them. That design principle has driven engagement, allowing these platforms to become core infrastructure rather than options add-ons.

Both Arup and GHD invited in modern experience platforms – centralised systems designed to manage people, projects and expertise as structured, queryable data. Treating proposal content as a collection and a living knowledge asset.

Both firms did not use the 1990 procurement lens – issue RFP, pick the feature richest vendor and then spending 18 months configuring for every hypothetical scenario. Arup and GHD started small, proving value and scaling based on outcomes not assumptions. Each began with a tightly scoped pilot. Each showed ROI early. Each treated the initial rollout as a proof of value rather than a final implementation

The agile, outcome-oriented model is more than a deployment tactic – it’s a cultural shift. It prioritizes adoption over perfection, speed over scope and results over risk aversion.

It was not about technology but orchestration. People, process and technology.