Jones
The Architecture and Engineering industry is at a key point in its digital transformation. Earlier technological changes, from manual drafting to AutoCAD, and later from 2D drawings to 3D modeling and BIM, were absorbed with limited disruption to fundamental ways of working or business models. Artificial intelligence (AI) and advanced digital platforms represent more consequential change with the potential to reshape design, construction and customer services.
In response, companies must develop clear, targeted and actionable digital strategies. These strategies must support efficient project delivery and enhance traditional services with digital offerings that create new value. Successful implementation will depend on the effective utilization of younger, digitally fluent staff, combined with the experience and judgment of senior professionals.
Emerging technologies in A&E
ChatGPT (released November 2022) and similar large language models have been widely adopted in the workplace. As a result, some reporting, data analysis and internal workflows have been streamlined. However, the full impact of AI is still unfolding. It is poised to further automate drafting, crash detection, quantity take-offs and design optimization and it is expected that generative design tools will soon be able to produce multiple design alternatives based on cost, performance and sustainability.
Major software vendors in the A&E space are investing heavily in hands-on AI and can be expected to bring AI-enhanced tools to market. Any A&E company’s digital strategy, recruitment plan, skills development priorities and business models must be developed in this context.
AI technologies are likely to increase efficiency, but at a significant cost. It is critical that companies look for opportunities to leverage these third-party platforms while adding value to their customers to cover costs, expand their role beyond traditional project delivery, and improve margins.
Implementation of third-party software: an opportunity for growth
Management consulting firms recognized their clients’ need for support in implementing, configuring, and customizing third-party software in the 1980s and 1990s as enterprise resource planning (ERP) and business software became more widespread. Over time, these companies evolved from business and strategy consulting to full-service technology consulting.
Typically, A&E companies did not exploit the same market. Only a small subset of the large A&E companies offered software implementation or configuration services. This usually happened when the software was directly linked to their engineering domain (GIS, asset management, digital twins, infrastructure modelling) or when the customer needed engineering expertise to configure the system (eg utility networks, transport models).
A handful of boutique companies carved out successful practices to implement niche environmental data systems. These examples suggest a broader opportunity for A&E companies to provide advisory services integrated with software implementation, particularly where domain expertise is essential to unlocking the full value of the technology.
Improvement of data interpretation services and decision-making support
Customers are increasingly challenged not by a lack of data, but by an overabundance of it. Models, monitoring systems, and reporting tools generate large volumes of information that customers don’t have the time or skill to interpret and act on. A&E companies are well positioned to translate this data into actionable insights with a combination of deep domain expertise and technology expertise.
A&E companies can increase revenue by improving their data interpretation, visualization and advisory services. This has the added benefit of allowing them to move upstream in the value chain. These services can support better client decisions and can lead to follow-up work for more traditional A&E services.
Internal Software Development: Lessons Learned
Although AI had not yet entered the public consciousness, some in the A&E industry recognized in the 2010s that the increasing efficiency of digital tools came at a significant cost in a profession still largely compensated by the hour. Seeing the potential for recurring revenue and higher valuations, some companies developed their own software. Many of these efforts have struggled to achieve financial success. Companies often underestimated the investment required to create secure and scalable products and overly customized solutions for individual customers, limiting repeatability.
More fundamentally, the traditional A&E business model does not align well with the economics of software development. Engineering companies prioritize predictability, profitability, and steady growth, while software companies focus on rapid scaling and a narrow product focus. Companies should take a “buy before you build” approach to technology, reserving any in-house development for cases where there is a clear strategic rationale and path to commercial success.
Management of digital innovation in the workforce
Recent graduates enter the profession with strong digital skills and expect to use modern technology in their day-to-day lives. Many are developing scripts, automations and lightweight applications to improve the efficiency and quality of service delivery and deliver services directly to their customers. Low-code, no-code, AI-powered platforms are accelerating this trend.
To capture the benefits while managing the risk, companies should consider formal “citizen development” programs. An effective citizen development program provides governance, training, guidelines, and tools to A&E professionals (citizen developers) who are developing software. Expertise is provided by experienced architects and software developers.
The benefits are that a catalog of tools developed by citizens can be generated. Effective tools can be standardized and distributed throughout the organization. Low value, duplicate and overly risky tools can be removed. Without this kind of structure, companies run the risk of investing in tools that are difficult and expensive to maintain, insecure, or unscalable.
From ad hoc adoption to strategic discipline
Technology adoption in many A&E companies remains opportunistic, driven by grassroots enthusiasm or demands for specific customer engagements. While this can encourage innovation, it can also lead to fragmented investments and tools that persist long after their strategic relevance has diminished or business value has been limited.
Effective digital strategies are specific, easy to understand and anchored by clear objectives and measurable key performance indicators (KPIs). They emphasize the selection of disciplined initiative and continuous assessment, while recognizing that meaningful learning occurs through execution. Organizations must maintain the flexibility to incorporate lessons learned, adapt to emerging technologies, and refine strategy over time. Trying to define every detail in advance is impractical and counterproductive.
Speed is critical. Leaders must enable informed and knowledgeable staff to make quick decisions, avoid unnecessary bureaucracy and actively support execution. A culture of learning, not blame, is essential.
Regular reviews help ensure technology investments stay aligned with business goals. Equally important is the willingness to discontinue initiatives that do not deliver sufficient value, regardless of sunk costs.
Architecture and engineering companies are entering a new phase of digital transformation. Unlike previous technological changes, AI and advanced digital platforms have implications that extend beyond productivity to service models and value creation.
The opportunity is to embrace the enthusiasm, curiosity and technological competence of younger and less experienced staff and combine it with the business expertise and more experienced professionals to identify niche opportunities with clients who are overwhelmed by the volume of data they receive and don’t have the time or expertise to interpret and act on it. The greatest return on investment will likely come from solutions that combine domain expertise with technology that can be codified into a standardized, repeatable framework that can be configured for a large number of customers.
Companies that manage innovation with discipline will be more likely to succeed. Just because something can be done doesn’t mean it should be done. Each potential opportunity must be evaluated with a clear understanding that both time and capital are finite and must generate measurable returns. It should focus on solutions that can produce repeatable revenue, strong margins and fast time to value and the discipline to cut losses and abandon those that don’t deliver on their promise. This will ensure that companies focus on offers with sustainable impact, clear market demand and alignment with the company’s growth objectives.
Alison Jones is a business and technology executive with over 30 years of experience in the architecture and engineering industry. He has led operations, digital transformation and global technology initiatives. Its goal is to align technology investment with business outcomes and customer value. Previously with Arcadis, Alison is currently the CEO of Order Penguin, an AI-powered equipment rental platform.
