Artificial intelligence (AI) is becoming a central tool worldwide, transforming approaches, including in design and engineering. Its use not only automates routine tasks but also opens up new opportunities for creating more complex and unconventional (classical, conservative) solutions. Design and engineering companies in Ukraine that aim to compete in global markets and have an undeniable advantage in Ukraine’s engineering sector must already consider global trends, their development, and the implementation of new technologies, seeking ways for their practical application.

Examples of AI usage in design and engineering that have already been implemented in practice. These examples clearly demonstrate how technology helps automate tasks, optimize processes, and improve results.

Automation of routine tasks

Previously, engineers spent hours on calculations, drafting, and selecting materials. Now, these processes can be automated. For example, the **Generative Design** platform from **Autodesk** allows obtaining dozens of optimized design options in just a few minutes, considering weight, materials, and cost. This technology is already being used in the design of automotive parts and construction structures.

Optimization of engineering processes

Beyond automating design processes, machine learning technologies help optimize complex and comprehensive engineering tasks, such as implementing construction projects, including actual design, equipment and material supply, construction, and installation work. According to an article in the **Automation in Construction** journal (2022, Vol. 140, Article No. 104304), researchers from **the University of Twente** developed a machine-learning-based algorithm for analyzing data from completed projects. The algorithm allows predicting possible delays and budget overruns with 90% accuracy, which is already being applied in construction projects in Europe.

Engineering simulations

Another area of application is modeling. **Siemens** is actively implementing AI in this field. For example, within the **Simcenter project (2023)**, neural networks are used to optimize aerodynamic calculations in the design of wind energy systems. These technologies reduce the time required for complex simulations from days to hours (**Journal of Wind Engineering, 2023, Vol. 167, pp. 1-15**).

BIM technology support

The integration of AI into **Building Information Modeling (BIM)** systems allows for identifying potential conflicts already at the design stage. **Bentley Systems** has implemented artificial intelligence in its **iTwin** platform, which automatically analyzes engineering networks and detects intersections or inconsistencies. This approach was successfully applied in the **Sydney International Airport reconstruction project (Bentley Systems, 2023)**.

Key directions of current AI developments in engineering

According to experts from **TPS Engineering LLC**, a representative of the **Association of Design and Engineering of Ukraine**, the development of AI in design and engineering will follow these directions:

Development of digital twins

Digital twins are becoming an increasingly powerful tool in engineering practice. **General Electric** is actively developing this technology for gas turbine management. According to the **GE Digital White Paper (2023)**, research in the field of digital twins has led to a **15% reduction in operating costs** and a **20% increase in equipment lifespan**. Work in this area continues, and digital twins are expanding into new industries.

Robotics and automation

**Boston Dynamics**, in collaboration with **MIT** researchers, continues to develop a system where AI-powered construction robots autonomously coordinate tasks on construction sites. These technologies are being tested within the **smart construction project in Dubai (Boston Dynamics Press Release, 2023)**, with further research aimed at improving robot control algorithms and their integration into complex construction processes.

Predictive analytics

Predictive (forecasting) analytics algorithms enable the prediction of structural behavior and the assessment of operational risks, making them indispensable in project management. For example, according to a study by **McKinsey (2023, “Artificial Intelligence in Construction”)**, the use of such algorithms has already **reduced unforeseen costs by 25%**. This area is particularly important for the engineering services market, as it minimizes financial risks, optimizes developer expenses, and improves the accuracy of material property predictions throughout their operational lifespan, offering reliable and, most importantly, highly efficient solutions.

Generative design

Generative design, developed by **Autodesk, Dassault Systèmes**, and other companies, allows for finding optimal engineering solutions in the shortest possible time. For example, the use of **CATIA** in an **Airbus project** for the development of lightweight parts for the **A350 airliner** allowed for a **10% reduction in aircraft weight (Dassault Systèmes Report, 2022)**. This area is particularly promising for engineering services, as it reduces design time, lowers material costs, and opens access to innovative structural solutions.

Environmental design

The **BuildAI startup** applies AI to optimize the carbon footprint of buildings, using computer vision algorithms to assess different construction options. In one of its projects in **London**, CO₂ emissions were reduced by **30% (BuildAI Sustainability Report, 2023)**. This area is critically important for the engineering services market, as clients are increasingly oriented toward environmental standards. Companies implementing such technologies gain a competitive advantage by offering environmentally friendly solutions.

Here is a list of some resources that may be of interest and applicable in the field of engineering and design:

1. Generative design and conceptual planning

· Autodesk Forma (formerly Spacemaker AI) – AI for urban planning and volumetric design.

✅ Features:

Optimization of building placement on a site.

Analysis of lighting, wind flows, and noise pollution.

Selection of the optimal building shape.

2. BIM and structural design

· Autodesk Revit + Dynamo AI – automation of structural design.

✅ Useful for:

Generating load-bearing structures.

Automatic selection of materials and joints.

Optimization of concrete, steel, and reinforcement volumes.

3. AI for engineering calculations and structural optimization

· Dassault Systèmes CATIA Generative Design – AI for automatically selecting optimal structures.

✅ Useful for lightweight and strong structures (e.g., truss frames).

4. Optimization of construction processes and planning

· Alice Technologies AI – AI for optimizing construction schedules.

✅ Generates an optimal sequence of work to reduce time and costs.

AI has already significantly changed approaches to design and engineering. In the coming years, its role will only grow, providing new opportunities in areas such as:

· Digital twins, whose integration accelerates and reduces the cost of both entire construction projects and individual equipment maintenance.

· Generative design, which enables finding the best engineering solutions in minimal time.

· Environmental design, crucial for achieving sustainable development goals, among many others.

Ukraine, as an integral part of the civilized world, along with its engineering and design companies that are already implementing AI, is gaining tangible advantages by reducing costs, improving project quality, and increasing efficiency. Given the number of destroyed and damaged buildings due to Russian aggression, the **Association of Design and Engineering of Ukraine** believes that without implementing advanced engineering processes and tools, restoring the country’s economy in the near future will be impossible. Given the scale of reconstruction required, AI remains one of the defining factors for success in this challenge, and its impact on the industry is inevitable.

 

General Director of TPS Engineering LLC, Dmytro Neznamov