AEC companies come in all shapes and sizes, from just a handful of employees to tens of thousands that span several continents. This variability is part of what makes the industry special; there are endless opportunities to find a niche focus, become a full-service provider, or partner with other companies to build a reputation in a specialized field. Although larger firms may have more resources to easily adopt new technology, smaller firms can also implement emerging technologies like AI and Machine Learning (ML) without a large, upfront investment.
Common Challenges in AI Adoption
For many firms, resources and materials costs are a drain on the budget, and adopting AI may seem daunting. Some challenges include:
- High-powered computing infrastructure to accelerate processing. Complex AI models and large datasets may require a significant investment in specialized hardware and/or cloud infrastructure, which is both expensive to acquire and time consuming to maintain.
- Accessing and managing quality data. Since developing ML models requires large volumes of training data, finding and curating data is a time-consuming and potentially expensive process.
- Hiring and/or outsourcing talent. Building ML models in-house requires specialized expertise that may not exist within your current team. Organizations must either develop internal capabilities or outsource to experienced third parties.
- MLOps. A Machine Learning Operations team is needed to manage and maintain models, retraining them over time to be responsive to current conditions, learn from new data, and correct any bias or drifting over time.
- Security/regulatory compliance. Models need to be secured from malicious attacks and kept in compliance with global and industrial operating policies, at a minimum. Data privacy breaches can irreparably damage a company's reputation, and many small firms don't have the resources to defend their data ecosystems.
So, what's the answer? When it isn’t realistic to build AI solutions, small to mid-sized firms can look for incremental investments that can make the most positive impacts.
Focus on the Biggest Pain Points
First, identify promising AI use cases by focusing on internal challenges first, exploring applications in a specific domain. For example, a small architecture firm that struggles to respond to incoming RFIs and the changing volume of project-related documents would benefit from a natural language processing (NLP) tool to add extra capacity and speed in reviewing language, flagging potential concerns, or highlighting time-sensitive information like submission deadlines. Or, if a construction project team is struggling to maintain a client's aggressive inspection schedule, a machine learning model can offer significant support, providing detailed analysis of project data to create an accurate picture of the project status, predict any delays, and keep the team on track.
Other Ways to Maximize AI Wins on a Budget
- Consider user-friendly solutions. Models that require minimal training and/or customization are the easiest way to integrate AI into your current business processes, reduce training needs, and save dollars that are needed elsewhere.
- Research flexible purchasing options. Instead of building an AI model from scratch or hiring expensive consultants to customize a solution, firms can easily integrate cloud-based, pretrained models with no set up required and pay-as-you-go licensing flexibility.
- Join AEC industry-focused consortiums. Organizations like buildingSMART International and Partnership on AI establish guidance, training, and engagement opportunities for architecture, engineering, and construction (AEC) professionals who want to improve their craft. These groups can facilitate connections with tech providers that specialize in delivering AI solutions for AEC firms.
For smaller engineering firms looking for easy and cost-effective access to AI, look to BRYX, which offers pretrained machine learning, computer vision, and computational models for numerous AEC use cases. Check out our catalog for more on our current and upcoming offerings.