The future is exciting – especially for engineers, because challenges and technology are becoming increasingly complex. And the future is not just about the hard technical skills of these professionals, but the seamless integration of selected soft skills to solve those very challenges. Let's take a closer look at this today.
AI Engineering?
Artificial intelligence is, obviously, the elephant in the room and is having a disruptive effect in all sectors and industries. In Industry 4.0, mechanical engineering in particular is changing fundamentally – and thanks to AI, productivity, efficiency and innovation are increasing. For example: AI-supported software can automate tasks such as the creation of precise and optimised design models, the analysis of construction plans, historical data or project requirements. Above all, the manual workload for engineers is drastically reduced. Let's take a look at this in a brief overview:
Increasing productivity and efficiency: AI automates repetitive tasks and allows engineers to focus on more complex and creative aspects of their work. This applies to all sectors and industries.
Design optimisation: AI algorithms can analyse data and create optimised design models – which in turn can lead to more efficient and cost-effective solutions.
Predictive maintenance: This technology has been around for a few years, but it is also constantly improving with greater precision. By analysing data from sensors and devices, maintenance requirements can be predicted.
Autonomous systems and robotics: AI plays a central role in the development of autonomous systems and robotics and enables advanced technologies for various industries.
Deloitte also concludes in its "Engineering and Construction Industry Outlook 2024" that advancing digitalisation and generative AI is one of five key areas that will help these industries into the future. Figure 1 shows a list of case studies and their application.
So what skills do engineers need to get involved in the field of artificial intelligence?
We can roughly break it down to three areas:
- Computer Science & Programming
- Maths & Statistics
- Expertise & business knowledge
And precisely with these areas, we find ourselves in the centre of the field of data science – because the development of AI models is also part of this field of knowledge. Engineers with data science skills are therefore the new rock stars of Industry 4.0.
But even focusing on just one of these three areas prepares future engineers sufficiently for the future. In terms of technical skills, these include the following topics:
- Programming: Knowledge of languages such as Python, R, Java and C++ is useful as these are often used in the development of AI algorithms.
- Machine learning and deep learning: An understanding of the principles of machine learning and deep learning, including neural networks, reinforcement learning and natural language processing.
- Data analysis and modelling: The ability to work with large data sets, prepare data and use data visualisation tools to interpret results.
- Robotics and automation: Knowledge of robotics, hardware and software is crucial for the integration of AI into physical systems.
Soft skills round off the picture
However, even if the dominant appearance and arrival of technology - above all artificial intelligence, of course - has upset some people, soft, interpersonal skills are now more important than ever. The future is the symbiosis of man and machine, because people will always work together with people. Even if technology is becoming increasingly integrated into our relationships.
The Harvard Business School recently listed 6 business skills for engineers - we basically agree with this, but add another important point to the list: adaptability and continuous learning.
Effective communication
Engineers often have to explain technical details to non-technical stakeholders. This happens, for example, when a new software architecture is presented to the marketing team - complex technical jargon has to be translated into easy-to-understand terms. In general, effective and above all clear communication ensures that everyone involved and stakeholders are always in the loop.
Management
Effective project management in engineering involves coordinating resources, schedules and personnel to achieve project milestones. Engineers leading a team in the development of a new product need to motivate the team, manage resources efficiently and overcome the challenges of the project. And, of course, they must be able to manage themselves first and foremost. Time management, for example, is often a separate soft skill.
Problem solving
Engineers generally solve problems through innovation and creativity. In the event of bottlenecks in production, for example, they are able to redesign the production process in order to increase efficiency, reduce costs or maintain production output. This is where both analytical and creative thinking come into play, both soft skills in their own category.
Business Operations
Understanding the financial implications of technical decisions is something engineers need to have on their radar. For example, they can use cost-benefit analyses to determine the most economical materials for a project, ensuring that the project stays within budget while meeting quality standards.
Research and critical thinking
The ability to research thoroughly and think critically is essential. This ensures they can recognise new opportunities, test ideas and make informed decisions in a technology-driven landscape. For example, when engineers are researching a new software tool that can automate processes and thus improve project results. At the same time, they are aware of the challenges that a potential solution may entail.
Leadership qualities
It is important to lead by example and adapt to change. For example, good engineers are able to lead a team through the transition to agile project management, guide the team through the learning process and tackle challenges with a positive, solution-oriented approach.
Adaptability and continuous learning
All areas of technology are evolving rapidly, and engineering is no exception. Engineers must commit to continuous learning in order to stay ahead of, or at least keep pace with, industry trends and technological advances. They link themselves to further training, take part in workshops or learn new software tools. As we wrote above, computer science, maths, statistics, business knowledge or the soft skills mentioned here could be particularly suitable.
For comparison – these soft skills fit seamlessly into the results that McKinsey has generally identified for the work of the future (see Fig. 3). Therefore, engineers are ideally positioned for the future by combining the hard and soft skills presented here.
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