Digitalization is affecting every industry—and software-driven processes have long since arrived in traditionally craft-based sectors such as construction. The additional integration of artificial intelligence in construction can raise efficiency and productivity to a whole new level. In fact, machine learning, LLMs, and generative technologies even provide a particularly easy entry point for companies in this sector, which still work in a relatively analog way compared to other industries. In this article, we'll show you what's possible, why AI is already so important for the construction industry today, and how to get started.
What is artificial intelligence in construction?
Artificial intelligence describes technical systems that can independently perform tasks that would otherwise require human thinking. These include recognizing patterns, evaluating large amounts of data, and deriving recommendations for action. Applied to construction, AI supports numerous processes throughout the entire project.
It is used, for example, in the monitoring of construction sites, automated documentation, project management, material analysis, resource planning, compliance with safety regulations, and long-term building management. Generative applications also significantly accelerate planning and organizational tasks.
Artificial intelligence in construction can therefore be summarized as follows:
Technology that automatically analyzes and specifically improves construction processes, for example through data-based evaluations, decision-making logic, or the largely independent creation of work and planning documents.
The overarching goal is to make processes faster, safer, and more resource-efficient. AI is no longer limited to use in planning software—it is increasingly being used directly on construction sites.
The current significance of digital technologies with AI in the construction sector
Artificial intelligence does not replace craftsmanship—human expertise will remain indispensable in the construction industry in the long term. Nevertheless, the use of appropriate digital technologies for the further development of existing working methods is already emerging as a logical consequence. Construction remains a craft, but is increasingly supported by data.
The reason for this lies in the complex – and in fact increasingly complex – structure of the industry. Construction projects consist of many individual steps, participants, and dependencies. Planning, execution, and operation are intertwined. Standards, technical requirements, and legal specifications are constantly growing. This diversity can hardly be managed efficiently by manual means alone.
Therefore: Human decisions set the direction that digital systems follow. Artificial intelligence complements this experience by structuring large amounts of data, revealing complex relationships, and/or organizing and executing processes. It is precisely at this interface that real added value is already being created today.
The use of technical aids is increasingly becoming a prerequisite for working economically. Without digital support, schedules, budgets, and quality quickly spiral out of control. AI acts here as a tool to ease the burden, not as a substitute for human competence.
Studies underscore this development. According to forecasts by Mordor Intelligence, the market for artificial intelligence in construction will grow at an average annual rate of 24.31 percent through 2029. This means that more and more competitors are integrating corresponding solutions. Those who get in early gain structural advantages.
Another driver is the increasing shortage of personnel, as there is still a lack of qualified specialists in many areas. Machine learning can help here by taking on repetitive tasks and even acting as a digital assistant – keyword “AI agents.” This relieves experienced employees and creates space for strategic tasks or other activities that artificial intelligence cannot take on.
Looking at these interrelationships, clear development priorities for AI in construction emerge:
• Automation of planning processes
• Taking over recurring processes
• Reduction of personnel costs (on construction sites)
• Improvement of occupational safety
• Long-term monitoring of structures
Not to be forgotten: Artificial intelligence can be operated intuitively, especially through large language models and integration into generative systems. Voice-based inputs or visual evaluations lower the barrier to entry. As a result, AI can even serve as a catalyst for digitalization in the construction sector. What may seem complex at first glance simplifies many processes of the (necessary) digital transformation in your company in the long term.
Where AI is already being used in the construction industry today
In fact, artificial intelligence can already be used in many areas of construction and can support virtually the entire construction cycle—from the design and planning phase to execution and long-term building management.
Design, planning, and coordination
You can benefit greatly from AI technologies, especially in the early project phases. Design and planning work involves numerous dependencies, individual framework conditions, and design ideas. Artificial intelligence is able to evaluate these factors in a structured manner and develop suitable solutions in a matter of hours that would have taken a team weeks to come up with on its own. This is based on clearly defined parameters such as budget, space utilization, statics, materials, legal requirements, and/or available human resources. The more detailed and specific the data, the more effective the result.
Typical tasks that AI already supports in this phase include:
• Analyzing different design variants.
• Checking technical and legal requirements.
• Evaluating cost, space, and material efficiency.
The generative design approach plays a central role. Instead of creating individual designs manually, automated systems examine many possible variants in parallel. The end result is proposals that precisely combine technical feasibility, usage goals, and efficiency.
For smaller components or standardized assembly work, AI can even take over simple planning tasks independently. This significantly reduces the time, material, and manual labor required. However, the greatest added value comes in complex projects such as urban or neighborhood development. There are so many factors involved that a purely manual evaluation is hardly practicable.
Machine learning is also used in project coordination: You can calculate schedules more accurately, coordinate trades better, and identify dependencies early on—all quickly, reliably, and verifiably, because it's data-based. Historical project information ensures more realistic forecasts.
During the project, AI continuously analyzes current construction site data, revealing critical bottlenecks in personnel, materials, or budget early on. With a solid data foundation, you even have the opportunity to simulate alternative scenarios, for example by adjusting supply chains or schedules.
This approach is particularly effective in combination with BIM and a common data environment:
• BIM maps the building as a digital twin.
• CDE bundles all relevant project information.
• AI quickly evaluates this data and reveals correlations.
An additional focus is on sustainability aspects. Climate protection, energy efficiency, and ESG criteria are increasingly influencing investment decisions. AI supports the selection of materials, the analysis of energy and resource consumption, and the planning of recycling and disposal concepts.
Construction and supervision
In construction, AI is beginning to be used in self-learning machines and robot systems that support repetitive or dangerous tasks. At the same time, logistical processes on the construction site can be optimized, for example through intelligent route planning or automated material provision.
Another field of application is drones, which capture construction sites from the air, document progress, and provide up-to-date data for project management. Digital inspections via virtual reality supplement this information and enable coordination without physical presence.
In connection with administrative tasks, AI assists with tenders, checks service specifications, compares offers, and supports calculations. Documentation requirements can be fulfilled automatically, which noticeably reduces the workload for project management.
Specialized chatbots are used for questions about regulations, standards, or technical details. These systems draw on stored technical information. Nevertheless, results should always be checked by humans. AI offers enormous assistance, but does not take on any responsibility.
In construction supervision, you can integrate artificial intelligence into the analysis of materials and components. AI-driven applications identify deviations or defects much faster and more reliably than the human eye. Early detection of errors prevents costly rework and serious hazards.
Safety in construction
The last sentence of the previous section brings us to the topic of safety, which naturally always plays a central role on construction sites. The need for new solutions is correspondingly great.
Artificial intelligence offers a lot of starting points for occupational safety in construction, for example:
• Cameras and sensors detect missing protective equipment or open danger areas.
• Drones monitor activities from the air and identify risk zones.
• Predictive analytics models evaluate accident data and enable preventive measures to be taken.
• Helmet cameras and body sensors warn employees directly of hazards or incorrect posture.
Such systems also help with the creation and updating of safety and health protection plans. Risks can be assessed based on data rather than relying solely on experience.
Building management
Once the construction phase is complete, long-term operation begins – and here, too, AI can help construction companies or operating companies. Building technology can generally be automatically controlled using smart systems to, for example, reduce energy consumption and/or increase comfort.
In addition, maintenance and renovation needs are identified at an early stage: AI analyzes condition data and points out potential weak points, for example in fire protection or technical systems. Intelligent drones take over inspections of areas that are difficult to access, such as roofs or facades.
A key application is in predictive maintenance, where AI continuously evaluates operating data to determine the perfect maintenance time in real time. This reduces unexpected downtime and allows for better planning of running costs. The construction project thus remains optimally economical in the long term.
Checklist: How can AI be integrated into construction companies?
Of course, we cannot provide you with a comprehensive plan for integrating artificial intelligence into your business here. This requires individual AI consulting that is precisely tailored to the respective circumstances. However, as a first step, you should note the following phases, which must be completed in most projects in one form or another. In practice, this always involves a significant change process that requires time, clarity, and professional support.
1. Analyze the current situation: First, existing processes, data sources, and existing digital tools are recorded. The goal is to understand where manual work dominates today and where data is already available. Without this foundation, you cannot exploit the potential of AI in the construction industry.
2. Define suitable use cases: Not every process is immediately suitable for AI support. Tasks with a high degree of repetition, large amounts of data, and/or clear decision-making rules are particularly useful. Typical starting points are planning, documentation, or project management.
3. Prepare the database: Artificial intelligence requires structured and sound data. In this phase, information is collected, cleaned up, and made accessible. The quality of the results depends directly on the quality of the database.
4. Implement pilot projects: Instead of large-scale changes, manageable pilot projects are launched first. This allows the benefits, costs, and acceptance to be realistically assessed without jeopardizing ongoing operations.
5. Involve and train employees: Another fundamental prerequisite for truly valuable AI is the creation of acceptance and comprehensive understanding. Training and transparent communication help to break down reservations and establish the necessary practical application skills.
6. Evaluate and scale results: After successful tests or pilot projects, the existing solutions are expanded in a targeted manner. Adapt the processes step by step, open up new fields of application, and link your systems together more and more extensively.
An experienced AI agency will accompany you on this journey, ensure realistic goals are set, and help to harmonize technical, organizational, and economic aspects in a meaningful way.
Conclusion
Artificial intelligence is no longer a topic that exclusively concerns tech companies or digital startups. AI in construction can have a noticeable positive impact on almost all project phases. In an industry that is still largely analog in many places, the development opportunities are greater than many expect.
Planning, execution, safety, and long-term operation all benefit equally. However, to achieve real added value, realistic, systematic implementation must be ensured. No company will automate all areas immediately. It makes more sense to start with clearly defined pilot projects and gain experience.
Long-term market forecasts clearly show that early steps create competitive advantages. At the same time, in many cases, artificial intelligence even lowers the barrier to entry into digitalization because it makes processes easier to understand and control.
As an experienced AI agency, Bakedwith is happy to support you in identifying a suitable strategy for your business and implementing a structured entry.
FAQ
How can AI be used in construction?
Among other things, AI supports the planning, control, monitoring, safeguarding, and long-term operation of construction projects. It evaluates data, recognizes patterns, and helps to make more informed decisions. Its strengths are particularly evident in recurring routine tasks and complex analytical processes.
What can AI achieve in architecture and construction planning?
During the planning of construction projects, AI is particularly helpful in developing and evaluating design variants, optimizing time and cost schedules, and coordinating trades. Generative design makes it possible to examine many solutions in parallel and identify the most suitable options much more quickly.
How can construction companies successfully get started with AI?
A successful start begins with an analysis of existing processes and clearly defined pilot projects. A clean database and the involvement of employees are crucial. External support, i.e., AI consulting by a proven AI agency, is useful to ensure a systematic process, minimize risks, and realistically assess the benefits.
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Jens ist Mitgründer von bakedwith, einer Boutique-Beratung für smarte Automatisierung und KI. Er unterstützt mittelständische Unternehmen und Konzerne dabei, Prozesse zu optimieren, manuelle Arbeit zu reduzieren und durch effiziente Workflows Wachstum zu erzielen. Zuvor war Jens Growth Lead bei OMR und begleitete als Freelancer zahlreiche Unternehmen bei der Optimierung ihrer CRM- und Automationssysteme. Seine Leidenschaft gilt der Verbindung von Wachstum und Effizienz – damit Teams sich auf das Wesentliche konzentrieren können.
