The level of digitalization in German engineering firms is increasing significantly: the use of BIM, project management and collaboration solutions is part of the standard digital infrastructure, particularly in young engineering firms. Nevertheless, the complexity of content and project organization still requires a high level of manual effort for often repetitive tasks, the automation of which could lead to a significant reduction in the workload of specialists and thus to a significant optimization of resources. Generative AI offers new, simple digitalization options for efficient, cross-system work with both unstructured and structured data and is already increasing the productivity of innovative engineering firms.
Most Wanted: Increasing productivity through generative AI
Engineering firms are facing numerous challenges: According to the VDI to a loss of value added of up to 13 billion euros*.
In order to increase the productivity and innovation potential of engineers and the next generation of skilled workers, the intelligent use of technology is crucial. The focus here is particularly on time-consuming administrative and management tasks. Everything that has to do with communication – the procurement, preparation and communication of information – can now be automated by AI assistants.
Use cases for AI assistants in engineering offices
Implicit knowledge in documents can be utilised in a variety of ways using generative AI, adapted for corporate use. The use cases include
- Quick access to all types of project information
- Onboarding support for new colleagues
- Creation of rough concepts for projects, project documentation and conformity checks
- Analysis and optimisation of design data and schedules
- Automated customer communication for frequently asked questions
One of the reasons why generative AI is considered disruptive is that the technical implementation of these and many other use cases is up to 90 per cent faster than with previous search, analysis and information management technologies.
Central AI platform instead of tool overload
Since the official introduction of OpenAI ChatGPT In 2022, the market for AI tools has exploded. While some companies are waiting to see how the use of AI develops, others have already implemented several partial solutions and recognized the need to scale artificial intelligence. With the aiStudio of Kauz.ai, companies of all sizes have the opportunity to develop and manage their AI assistants without programming knowledge. This means that highly specialized AI agents can be trained on the platform by subject matter experts for their work requirements and, if necessary, merged into more comprehensive AI assistants to map holistic process chains in the company.
State-of-the-art technologies: Further development of large language models
The power of large language models enables completely new ways of working by combining them with a company’s own data. And yet we are only at the beginning of this new technological era: isolated AI tools are not only disadvantageous in terms of maintainability. Companies in all sectors should ensure that their AI platform technology-agnostic is designed. For example, aiStudio can be used to test and deploy various large language models. Depending on the use case, better response results can be achieved, but Kauz.ai also optimizes the model efficiency and cost models of LLM providers for company-specific use for the customer.
Start simply. Increase process complexity and granularity.
Generative AI democratizes process automation and creates scope for innovation. In fact, for most companies, the first step is to simply start with the credo first use cases to start. This usually requires neither comprehensive strategy workshops nor high investment budgets – but above all entrepreneurial pragmatism to specifically identify and automate repetitive tasks.
Traditionally, simple customer inquiries via the website or internal knowledge management are often initially automated and dynamized by AI chatbots in all industries. In many cases, the simple implementation motivates companies to continue seamlessly with the AI transformation of common working methods.
In a second maturity level, companies not only focus on automating central processes, but also dare to leverage productivity potential at individual employee level. For example, a time-consuming certificate check for new employees can be automated through cooperation with the chambers of crafts and trades and simple integration, significantly relieving the only internal HR resource.
Customized AI workstations for engineering offices
A no-code platform like aiStudio allows employees to create their own AI agents, while companies can manage them centrally. Depending on the specialist role, user-centric interfaces to third-party systems such as BIM, CAD or CRM software can be released and contribute to intelligent workflows through working tools integrated into aiStudio such as email, text editors and engineering tools.
Generative AI can be used multimodally, meaning it can analyze data, texts, images and videos. Assistance systems that reveal new design possibilities, carry out practical material analyses with synthetically generated data or accelerate prototype development by reusing, merging and adapting existing CAD plans will offer engineers new creative design options in the future.
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*VDI Association of German Engineers & German Economic Institute. (2024). VDI/IW Engineer Monitor – 1st Quarter 2024. Retrieved from https://www.vdi.de/ueber-uns/presse/publikationen/details/vdi-iw-ingenieurmonitor-1-quartal-2024