BY ANNE HUNT, DIRECTOR OF DATA & ANALYTICS, TRIMBLE
Technology has transformed construction accounting practices, streamlining processes that were once time-consuming and error-prone and helping companies navigate tight profit margins amid economic and market uncertainties.
With the emergence of artificial intelligence (AI), particularly Generative AI, construction businesses have a tremendous opportunity to unlock new levels of efficiency and automation. Despite concerns that AI will replace humans, the reality is that those who use AI will replace those who don’t. The technology is more accessible than ever, making now the time to lean into it.
Understanding the Fundamentals of AI
AI is evolving rapidly, making it difficult to stay on top of advancements for a technology that still seems relatively new. Understanding the key components of AI and how they work is an essential first step.
AI is driven by a set of technologies, such as machine learning and natural language processing, that enables a computer or computer-controlled machine to perform tasks commonly associated with intelligent beings. With these technologies, AI can perform tasks that typically require human intelligence faster and, in most cases, with greater accuracy. The main technologies underpinning AI are:
Machine Learning: A subset of AI that allows machines or software to use data and algorithms to imitate how humans learn. Over time, the performance of machine learning systems improves as they are exposed to more and more data. This ability to learn and adapt is a core aspect of machine learning. There are four types of machine learning techniques: supervised, unsupervised, semi-learning and reinforcement.
Deep Learning: An advanced form of machine learning that uses artificial neural networks to enable digital systems to learn and make decisions based on unstructured, unlabeled data. Deep learning emulates how the human brain learns through networks of connected neurons. It is designed to function like a human brain, allowing it to recognize patterns, make decisions, and perform tasks like object and activity recognition and image segmentation.
Natural Language Processing: The part of AI that enables computers to understand, interpret and communicate in human language.
Large Language Models (LLMs): Deep learning models that are pre-trained on vast amounts of existing data sources. They use complex algorithms to identify patterns and relationships within data. LLMs are a type of Generative AI that creates new content, such as audio, images, text and videos. LLMs are considered the jacks of all trades, meaning they are good at many things. LLMs quickly comb through massive amounts of data and interpret and learn from it to generate original content.
While many LLMs are available today, most people are familiar with Open AI’s GPT. The most recent version, GPT 4.0 was released in 2023 and is trained on 100 trillion parameters. The more parameters a model has, the more data it can process, learn from and generate. GPT is one of many foundational models that can be adapted to achieve specific tasks.
Most people interact with LLMs using chatbots, such as Chat GPT. LLMs understand multiple languages but require prompts as guidance. Creating prompts is known as prompt engineering. Using a chatbot, a user types a description of what they want the LLM to deliver. Writing a good prompt doesn’t require technical expertise or stellar writing skills. A good prompt is all about clarity and specificity. The more specific a user is about what they want the LLM to deliver, the better the results will be.
Applications of AI in Construction Accounting
There are many ways AI can benefit construction accounting teams. Most commonly, AI can:
- Automate Processes – AI can take the manual burden of data entry and verification off the accounting department by automating repetitive processes. For example, it can turn paper and PDF invoices into validated, unapproved invoice entries for faster, more accurate workflows that save time, effort and money. Another example is using AI to automate the generation of 1099s or assist with month-end closing tasks.
- Extract Data – Construction businesses have no shortage of data, from RFIs to contracts. However, most of this data is unstructured, meaning it doesn’t fit into a standardized format for easy analysis. AI can extract and summarize data in a fraction of the time it would take a human to do it. For example, AI could analyze legal contracts and surface specific information, such as indemnifications, empowering anyone in the business to review contracts.
- Analyze Data – LLMs can analyze large amounts of data in seconds to identify trends and anomalies that a manual review might miss. For example, an LLM could analyze financial data and deliver the variance of cash in versus cash out, how forecasts compare to actuals, which projects are being billed on time and whether or not they are profitable. LLMs can create detailed financial reports for real-time insight into the financial health of the business.
- Enhance Forecasting and Planning – LLMs can analyze historical data to identify risks and opportunities and forecast financial outcomes. They can assist in creating detailed forecasts and budgets.
A Starting Point for Using AI Responsibly
Although AI is a powerful tool, it comes with challenges that accounting teams can easily overcome with the right processes in place.
When first exploring AI, it’s typical to wonder, “Can I trust what the AI is saying?” AI models can generate incorrect or misleading results, also known as hallucinations. The risk of hallucinations can be drastically reduced by providing the AI with data from credible sources. Users can ensure the results are based on trusted information by uploading documentation and data specific to their company.
Data privacy is also a common concern that can be alleviated by using a trusted platform in which the data uploaded into the AI system remains in the user’s environment. Be sure that you’re aware of how your data will be used within the AI model, including whether that data will be shared publicly or not. This information should be explicit and is also typically included within each AI vendor’s privacy policy.
Construction businesses ready to explore AI often find that their cloud platform offers AI capabilities. For example, Microsoft Azure users can use Azure Studio to accelerate the development of production-ready AI copilots to support enterprise chat, content generation, data analysis and more. Users can explore, build and test APIs and models for specific use cases.
Regardless of where you are in your AI journey, the technology has immense potential to transform construction accounting workflows. Even in the most basic applications, AI can bring more efficiency, accuracy and productivity to processes, freeing accounting teams to focus on more strategic tasks. AI will no doubt continue to play an important role in the future of construction and, for those who use it, redefine and elevate essential business processes for happier teams, profitable projects and future growth.
Anne Hunt currently serves as the director of the Trimble Data and Analytics team. With a passion for revolutionizing the construction industry, Anne and her team deliver cutting-edge data-first services that drive meaningful advancements.