AI in Preconstruction: How the industry is using AI

Streamlining Implementation of AI in Preconstruction: Reducing Costs and Accelerating Project Take-Offs

The construction industry is no stranger to complexity, but few stages are more critical—or more chaotic—than preconstruction. As projects grow in scale and intricacy, so too do the challenges of documentation, estimating, and coordination. With 85% of construction projects exceeding budget expectations, the need for a smarter, more efficient approach is clear. Enter AI-powered software in preconstruction. In this article, we explore how artificial intelligence is transforming preconstruction workflows. It’s helping teams streamline documentation, reduce costly errors, and dramatically accelerate project take-offs. Whether you’re struggling with fragmented data, manual updates, or decision-making bottlenecks, AI in preconstruction offers construction firms a powerful path to greater accuracy, speed, and scalability.

The Biggest Preconstruction Challenges: Documentation & Bidding

Every construction project is unique in scope, and so is the preconstruction process. The more people, tasks, and elements involved, the more complex and riskier the process becomes. Propeller highlights in an article the widespread issue of cost overruns in the construction industry. The report reveals that a significant majority of projects exceed their initial budgets. A comprehensive review spanning 70 years and 20 countries found that 85% of projects experienced cost overruns. The average overrun was 28%. This stark reality underscores the persistent challenges of accurately estimating project costs. More emphasis on maintaining budgetary discipline in such a dynamic sector is crucial.

85% of projects experienced cost overruns, with an average overrun of 28%
Propeller Study

Cost overruns stem from underutilization of data. Other factors include inaccurate project estimates, design errors, unforeseen changes, administrative mistakes, poor communication, and underestimated project timelines. These are alarming statistics for an industry already burdened by the inherent complexity of its projects. This is further compounded by the fact that many construction teams approach each preconstruction process as a unique, standalone effort. Without a proven, repeatable process for managing documentation and bidding, cost overruns and dissatisfied clients become almost inevitable.

According to Engineering News-Record, the construction industry struggles with fragmented communication and inconsistent digital adoption. Only 34% of field respondents indicating cohesive digital efforts around implementing and using construction technology within their companies. Addressing these challenges requires a comprehensive digital transformation to enhance interconnectivity. By streamlining workflows and strengthening the communication chain construction projects are more set up for successful project completion.

Only 34% of field respondents indicating cohesive digital efforts within their companies.
Engineering News-Record

Teams must contend with the sheer volume and complexity of documentation. Not to mention version control challenges, fragmented communication, extended timelines, and delays in change management reporting, all of which demand extraordinary precision and coordination to avoid costly mistakes.

Given these inherent challenges in preconstruction documentation and estimating, what strategies can construction teams adopt? How do they streamline processes, improve accuracy, and reduce decision-making complexity at every step? Addressing these questions is key to overcoming one of the industry’s most persistent hurdles, especially as it relates to implementing ai in preconstruction.

Operational Pitfalls: Decision Making Complexity & Manual Updates

A recent paper by NACon.org delves into the complexity of engineering and construction programs, identifying over 70 key considerations across eight categories during the planning phase. The research emphasizes how project complexity escalates as the scale of the project increases.

When data is fragmented and numerous preconstruction professionals are involved, establishing a single source of data becomes a significant challenge. Who ensures that all perspectives are accounted for and that the documentation stays up-to-date? Ideally, the process should begin with baseline data acquisition, continue with creating a user-friendly environment where the team can easily interact with the data, and conclude with generating accurate documentation and bidding estimates. Unfortunately, this often doesn’t happen in a streamlined or repeatable manner.

As a result, countless decisions must be made during every preconstruction process, increasing the likelihood of human error. Limiting the number of decisions required and ensuring that all data and collaborator inputs are captured is foundational for success. Imagine cutting the preconstruction process, including documentation and estimating, by half. How many more projects could your team bid on and secure each year? Would finding ways to incorporate ai in preconstruction change the way the industry looks at generating reports?

The Value of AI in Preconstruction: Four Ways to Accelerate Project Take-Off

Artificial Intelligence is revolutionizing the construction industry, impacting every phase from data collection and aggregation, planning and bidding to project management and post-analysis. However, perhaps no stage benefits more from AI’s capabilities than the preconstruction and bidding process. AI enables preconstruction teams to create more accurate bids, allowing them to participate in more projects and capitalize on initial opportunities. While there are numerous benefits to integrating AI in preconstruction, this article highlights four of the most impactful:

95% of construction data remains entirely unused
Autodesk and FMI Consulting

1. Capturing and Aggregating Data into a Single Source

A joint study by Autodesk and FMI Consulting revealed the staggering impact of poor data practices on global construction projects. Even more striking, an astonishing 95% of construction data remains entirely unused, leaving a vast reservoir of potential insights untapped during both preconstruction and active construction project management phases.

Success begins with having accurate, timely, and exhaustive data as the foundation for decision-making. However, the vast array of data management tools, often operating in silos, makes it challenging for teams to connect the dots across multiple platforms.

AI eliminates this challenge by analyzing vast amounts of data, agnostic to format or type. It consolidates information into one cohesive platform, highlighting interdependencies, conflicts, and solutions. This ability to unify and contextualize data ensures that teams have a single source of truth for their preconstruction planning process, empowering better decisions with fewer errors.

2. Reducing Decision-Making Complexity and Volume

Fragmented data leads to a cascade of poor decisions, as explored earlier. Fortunately, AI significantly reduces the number and complexity of decisions humans need to make during preconstruction. Picture a team of AI agents analyzing millions of data points, identifying patterns, and handling “easy and obvious” decisions.

For humans, processing such vast quantities of information is overwhelming and error-prone. AI, however, thrives in this environment, reducing the volume of decisions required and minimizing human error during estimation and bidding. This allows teams to focus on strategic, high-value tasks while relying on AI in preconstruction to handle repetitive and data-intensive operations .

3. Enabling Real-Time Change Management

The preconstruction and bidding process is filled with changes as potential customers review plans, concepts, and designs, providing feedback that must be incorporated. Traditionally, this results in labor-intensive and error-prone workflows to update all models and platforms accurately.

AI in preconstruction transforms this process by enabling real-time change management. It processes feedback immediately, updates all related assumptions, models, and decisions, and provides instant insights into how changes impact overall costs and final bids. This streamlining reduces turnaround time and ensures that updates are accurately reflected across all documentation and disciplines, enabling preconstruction teams to work smarter and free up valuable operational bandwidth.

4. Lightning-Fast Construction Documentation

AI dramatically accelerates the creation of essential construction documentation. It can generate Bills of Quantities, proposals, 3D models, aerial imagery, and 2D drawings at lightning speed, tasks that traditionally take days or weeks. Not only does this save time, but it also ensures greater consistency and accuracy across all documentation. AI in preconstruction enables automation to free up construction teams to focus on strategic planning and problem-solving rather than time-intensive administrative work.

Leveraging AI-powered software during the preconstruction process ensures that your data is clean and consolidated, reduces the volume of operational decisions, empowers you to analyze the impact of plan changes in real-time, and enables seamless input and output of essential documentation. By offloading repetitive but critical tasks, AI allows your team to concentrate on strategic objectives and challenges. In a competitive industry where efficiency and accuracy can make or break success, AI is no longer a luxury but an indispensable tool for streamlining preconstruction and driving better outcomes.

Scaling Efficiency: AI in Preconstruction as a Catalyst for Growth in Construction

Together, we’ve explored the state of construction project documentation and its significant ripple effects, how inaccuracies and inefficiencies negatively impact bidding precision and ultimately lead to cost overruns during the construction phase. We’ve also delved into the transformative ways AI in preconstruction is reshaping and improving accuracy, simplifying complexity, and accelerating processes.

Now, you might be wondering: just how transformative can AI be in the preconstruction phase? How can its impact be measured in terms of improving your processes and empowering your team to accelerate project take-offs? The results speak for themselves.

AI-powered preconstruction tools, as we’ll see in the following case study, have demonstrated the ability to reduce the number of decisions required from teams by a staggering 80%. One specific AI in preconstruction tool streamlines project estimates, cutting tasks that used to take hours or even days down to mere minutes and slashing take-off times by an impressive 90%.

This transformation doesn’t just eliminate costly errors, it leads to more comprehensive and accurate documentation and unlocks the ability to bid on and win significantly more projects per year with more confidence in your estimates. By embracing AI, construction teams can shift from managing inefficiencies to scaling opportunities.

Now, let’s dive into a real-world example: the remarkable results achieved by a US-based Tier 1 Construction Engineering & Design Company.

Case Study: Unlocking Efficiency with AI—90% Faster Estimates and a $150M Pipeline

A US-based Tier 1 construction engineering and design company specializing in repeatable, productized designs faced significant challenges in scaling operations, particularly in their growing energy sector. The company’s expertise in developing power stations and productized substation designs was hindered by a project pipeline that far exceeded their team’s capacity, leading to a lengthy backlog and limiting growth potential. Processes were inconsistent, relying heavily on siloed expertise and multiple, disconnected systems, which created inefficiencies and inconsistent outcomes.

To address these challenges, the company implemented Slate’s AI-driven preconstruction platform, Generate, which provided a single source of truth and a streamlined, productized process. Slate harnessed data from diverse systems such as Autodesk, AutoCAD, Procore, and historic project datasets, connecting and contextualizing the information into one cohesive platform. The platform enabled the team to contribute their expertise collaboratively, speeding up estimation, revisions, and documentation.

Using Slate’s predictive AI and parametric computational design, the company achieved transformative results:

90% reduction in time from take-off to estimating
70% overall design time saved
320 hours saved on a single configuration

In addition, Slate automated documentation generation in various formats, including Bills of Quantities, 3D models, and 2D drawings, while capturing real-time collaborator inputs. This is used to update project documentation seamlessly. By identifying seven critical “alpha questions” that had the most significant impact on design and estimating, the platform enabled the team to focus on high-value decisions.

The operational improvements delivered remarkable business results. The company increased the number of bids per year by 10x, unlocking an impressive $150 million in potential new revenue annually. Slate Generate not only accelerated preconstruction workflows but also positioned the company to scale operations, improve consistency, and achieve better outcomes across its entire project portfolio.

This case study illustrates how AI-driven solutions like Slate’s Generate product empower construction teams to overcome operational bottlenecks, enhance efficiency, and unlock exponential growth opportunities.

Read the entire case study and download it here: Takeoff and Estimating Case Study for Leading Construction Engineering & Design Company by Slate.ai

From Challenges to Solutions: AI as the Force Behind Preconstruction Innovation

The challenges facing the construction industry, particularly in the preconstruction phase, are significant. From fragmented documentation and complex decision-making processes to persistent cost overruns and inefficiencies, traditional methods often fall short. However, as explored in this article, the integration of AI has introduced transformative solutions that are revolutionizing preconstruction workflows.

AI-driven tools address the core issues of the preconstruction phase by creating a unified source of truth. It can also automate repetitive tasks and significantly improving the accuracy of bidding and documentation. By reducing the number of decisions required from teams by up to 80% and cutting takeoff times by 90%, these tools not only eliminate costly errors but also enhance collaboration, streamline data management, and improve real-time change management.

These advancements underscore the immense value of adopting AI in preconstruction. By enabling teams to focus on strategic objectives rather than manual, time-consuming tasks, AI empowers the construction industry to scale operations, reduce inefficiencies, and achieve better outcomes. For construction firms looking to remain competitive and drive growth, AI is no longer optional—it’s essential.

About Slate Technologies

Slate Technologies offers specialized AI solutions tailored for real estate and construction industries, delivering powerful data-driven insights uniquely suited to each sector. For real estate, Slate’s platform empowers investors and developers with advanced tools for market analysis, risk assessment, and forecasting, helping them identify high-potential opportunities and optimize investment strategies with data precision. In construction, Slate’s digital assistant enhances project management by improving cost control, boosting productivity, schedule reliability, and providing dynamic decision support throughout the construction lifecycle. Backed by a team of top software engineers and industry experts, Slate is transforming both industries through targeted, AI-driven intelligence.