Artificial intelligence (AI) has played an important role in the construction industry for years, particularly in the design-build side of the business, where virtual tours, drone-enabled inspections and similar kinds of capabilities can be found in the tech toolbox at many firms.
Lately, that role has expanded as the range of AI-driven capabilities grows, as the large language models behind these capabilities learn, and as firms become more knowledgeable and comfortable with using these tools inside their business.
One of the areas where AI shows the most potential for delivering value to a firm is in the intricacies of managing a project throughout its lifecycle, from initial proposal, to preconstruction, right through to final delivery.
With its ability to surface insight to improve decision-making for both projects and pursuits, and to automate manual processes so project teams work more efficiently, freeing them to focus on the higher-value work that produces better outcomes for clients and owners, AI can be a true difference-maker for a construction firm.
Some AI capabilities your firm may already have in-house, likely as part of an enterprise resource planning (ERP), project management (PM) or customer relationship management (CRM) system. The key to maximizing the value of whatever AI capabilities you may already have or are considering adding to your firm’s tech toolbox is to apply them to use cases that align to your business goals and resolve a business issue for you or your clients.
But first you need to ensure you have a strong foundation in place. And that foundation starts with data. From my experience working with companies across the architecture, engineering, and construction (AEC) industries, the firms that tend to get the most bang for the buck from their AI investments are those whose data is fresh, trusted and readily accessible, not only to people but to the systems that use AI.
Because the models behind AI depend on data to learn and yield insight, the fresher, more reliable your data is, the more value your AI capabilities are likely to produce.
AI can sharpen and streamline the processes behind proposal creation, with the ability to quickly cull content, and drop it into intelligent proposal templates, minimizing manual effort and ensuring consistency and accuracy.
Beside a strong handle on your data, it’s also important to have a clear plan for piloting AI within specific areas of your business, with KPIs in place to measure and assess the results of those pilot initiatives. Then use those results to inform decisions about scaling your AI usage more broadly across the business.
With a strong foundation for AI in place, your firm can begin climbing the AI maturity curve shown in the graphic below, uncovering new business use cases for AI along the way.
Here are six compelling use cases for AI in the context of managing a construction project:
1. An elevated client experience from the outset with a superior, highly tailored proposal
By making a positive first impression with your proposals, you set the tone for a healthy working relationship with your clients and owners. AI helps in that regard, giving firms tools to ensure their bids track precisely to the nuanced requirements of each and every RFP.
Meanwhile, AI also can sharpen and streamline the processes behind proposal creation, with the ability to quickly cull content, and drop it into intelligent proposal templates (hopefully your firm has access to these within its CRM or proposal-generation solution), minimizing manual effort and ensuring consistency and accuracy.
What’s more, by identifying trends, patterns and correlations from past project data, AI can provide proposal teams with predictive insight into costs, resource requirements, expected profitability and other key performance indicators.
2. On-point estimating, minus the manual work
Estimating is another area where firms can put AI to work, with its ability to augment the takeoff process so it’s less manual, faster and more accurate.
3. Simplified, smart resource management
Who among your labor resources (staff and contracted) are available and have the appropriate skills for a particular project? How does resource availability match with projects in the pipeline? What’s the likelihood of a labor squeeze? AI-driven predictive capabilities not only can alert you to a potential labor shortage, they also can recommend optimal project team makeup based on an analysis of peoples’ skills, certifications and performance.
Meanwhile, smart AI-driven tools also can automate resource scheduling with percent, frontload, mid-load or back load logic. If your firm’s ERP system lacks these tools, it could be worth switching to one that does.
4. Automating accounts receivable functions and other key finance & accounting processes
Using AI capabilities embedded within a modern ERP system, firms can automate AR collection processes to encourage steady cash flow, while also using AI-driven posting and reconciliation to keep close tabs on how projects are tracking financially.
5. Forecasting to give project managers clear, real-time insight into project progress
AI-driven predictive modeling tools can give PMs an on-demand look at how every aspect of a project is tracking relative to specific timelines, budget line items and other KPIs. Based on these forecasts, PMs can make better informed decisions about potential adjustments to resource scheduling, timelines, etc., to keep a project on track in terms of profitability and desired customer outcome.
6. Improved relationship tracking
For PMs and business development teams alike, relationships—and relationship awareness—play a pivotal role in new business pursuits. AI can help ensure that everyone in the company is on the same page by automatically scanning emails and other publicly available sources for up-to-date contact information about prospects as well as existing clients, then updating the contact database accordingly.
This gives firms the most current contact information so they don’t miss out on opportunities, and also provides important context to interactions with prospects. In my work with construction companies, this kind of awareness has literally helped win millions of dollars worth of business.
These handful of use cases for AI in a project management context only hint at AI’s vast potential value to a construction business. Firms that bring an explorer’s mindset to their adoption of AI, with a willingness to push boundaries, test new use cases, build on successes and learn from missteps, put themselves in a great position to consistently deliver projects that surpass expectations from both the firm and customer perspectives.
Lucas Hayden is Senior Director of AEC Strategy for Unanet, a leading provider of project-based ERP and CRM solutions purpose-built for architecture, engineering, and construction firms, and government contractors. https://unanet.com/
