In Dialogue with Michael Kolleger: Leadership 4.0 – AI in Transition

In Dialogue with Michael Kolleger: Leadership 4.0 – AI in Transition

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In dialogue with Michael Kolleger: Leadership 4.0 and AI in transition

In the kick-off of our new expert series “Leadership 4.0: Leadership in the Changing AI Era“, Data Scientist Michael Kolleger took the time for an interview with us. As part of this interview series, we want to get a clearer picture of artificial intelligence and talk about leadership over the next few years.

Read this interview to join us in broadening your digital horizons and gaining more insight into the complexities of AI transformation.

Hello dear Michael, thank you for taking the time for this interview! First of all, please introduce yourself. How would you briefly describe yourself and your profession?

As a Data Scientist in a senior position, I am responsible for leading a highly skilled team group specialized in data-driven solutions. My career field encompasses several key functions, including presales activities, product development, and initiating innovative ideas.

In presales, I am instrumental in convincing potential customers of our data-driven solutions. I analyze their requirements and present customized solutions to meet their business needs. In product development, I work closely with our technical team to design and develop data-driven products and services. Here, the focus is on using data to improve our products.

In addition, it is my job to foster creative ideas and innovative approaches to constantly explore new opportunities for data-driven solutions and further develop our company.

What would you say are three exciting projects you’ve worked on recently related to artificial intelligence?

• Energy Provider, Hong Kong: As a Data Scientist on this project, I had the challenging task of analyzing data from the energy sector in Hong Kong and developing intelligent solutions for the smart grid. Our work enabled us to use real-time data to predict power consumption and production and manage the network more efficiently.

• Automotive, Germany, Investigating Generation Z’s Opinion on Mobility: In this project, my team analyzed extensive data from social media to deepen Generation Z’s understanding of mobility and language preferences. These insights helped the automotive industry to develop targeted marketing strategies and better tailor products to the needs of the young target group in the future.

• Banking, Hong Kong, Developing New Financial Strategies with AI: In this exciting project, we supported a global bank in HK to break new ground by developing financial strategies using artificial intelligence. We analyzed market data, global economic trends, and business news to create advanced AI models. These models helped the bank make informed investment decisions, minimize risks, and optimize its portfolio management.

That sounds really exciting! But what exactly is artificial intelligence? Please describe this term as simply as possible.

Artificial intelligence (AI) is like a smart computer that tries to mimic human thinking. It learns from information, draws conclusions, and makes decisions, much like we humans do. But it’s important to understand that AI is not a panacea. Rather, it is a tool that can be used to solve very specific problems.

Think of AI as a toolbox full of specialized tools. Each of these tools is designed to tackle a specific task or problem. For example, one AI tool may be used to recognize images, another to translate text, and yet another to make predictions based on data.

The key to using AI effectively is to choose the right tool for the right task. AI can help perform complex calculations, identify patterns in data, and automate repetitive tasks. Overall, AI can help us solve specific problems faster and more efficiently, but it requires wise application and expertise to have its full impact.

In the context of artificial intelligence, some often worry that their work will be replaced by artificial intelligence. How do you see this danger? Above all, what then is the role of a leader in the use of AI?

The concern that artificial intelligence (AI) could replace human labor is understandable. In fact, some repetitive and data-intensive tasks in many industries can be automated through AI. This can lead to efficiency gains, but it also presents challenges and opportunities for the workplace.

A leader’s role in the use of AI is to provide strategic direction and accountability. Here are some important aspects:

• Strategic alignment: leaders need to understand how AI will impact their industry and company. They should define clear strategic objectives for how AI can help achieve business goals.
• Resource allocation: executives are responsible for allocating the necessary resources, including talent and technology, to successfully implement AI initiatives.
• Quality control: executives must ensure that AI applications are developed and deployed ethically and responsibly. This includes privacy, bias mitigation, and transparent decision-making by AI systems.
• Collaboration with AI: AI can complement human work by performing routine tasks while humans focus on more creative, strategic, and interpersonal tasks. Leaders should encourage the integration of humans and machines to achieve the best possible results.
• Crisis management: when job changes due to AI are imminent, leaders need to develop strategies for retraining and redeployment to mitigate the impact on the workforce.

Overall, the introduction of AI does not necessarily mean replacing workers, but rather shifting tasks and providing an opportunity to expand human capabilities. Leaders play a critical role in making these changes positive by finding the right balance between technology and human talent.

What skills must a leader have in order to use AI successfully? What technical skills are necessary?

In order to successfully deploy artificial intelligence (AI) in their area of responsibility, a leader should have several skills and attributes:

• Strategic vision: the ability to develop and communicate a clear vision and strategy for the use of AI in the organization.
• Understanding of AI fundamentals: a basic knowledge of how AI works, its applications, and its potential is essential.
• Technological understanding: knowledge of the technologies used for AI applications and their impact on the business.

How realistic is it that a portion of our executives will be made up of robots in the future?

Extremely unlikely.

So what would such a leadership style look like? One that consists solely of artificial intelligence?

A leadership style based solely on artificial intelligence (AI) would focus on data analysis, algorithm-based decision making, and automation. In this scenario, AI would continuously analyze large amounts of data to identify trends, patterns, and opportunities. It would generate recommendations for business decisions and make them based on objective data.

AI leadership would focus on efficiency, data optimization, and predictable operations. However, human leadership elements such as emotional intelligence, empathy and interpersonal relationships would be missing. This could lead to an emphatically rational and data-focused leadership culture that certainly neglects the creative and social aspects of leadership.

Where do you see advantages and disadvantages here? What can already be taken over by artificial intelligence, what should still remain human?

Challenges and limitations:

• Complexity of human interaction: leaders often need to manage complex interpersonal relationships, act empathically, and communicate strategic visions. This is a capability that AI systems have so far been limited in their ability to mimic.
• Creativity and innovation: developing new ideas, strategies, and creative solutions is an essential part of leadership that requires human intelligence and experience.
• Acceptance and trust: Acceptance of robotic leaders in the workplace and employee trust in such systems could be barriers.

Artificial intelligence (AI) has already demonstrated the ability to automate and take over human tasks in many areas. Here are some examples of tasks and work areas where AI is being used successfully:

• Image and speech recognition: AI systems can recognize and interpret images and speech, which is used in applications such as facial recognition, text translation and virtual assistants.
• Chatbots and customer service: AI-based chatbots can handle customer queries, solve problems and provide information.
• Financial and investment analysis: AI can be used in the financial industry for automated analysis of market and investment data.
• Medical diagnosis and imaging: In medicine, AI helps diagnose and analyze medical images such as X-rays and MRI scans.
• Manufacturing and robotics: robots with built-in AI are used in manufacturing to automate tasks such as assembly, quality control, and material handling.
• Human resource management: AI can assist in applicant selection, monitoring employee performance, and identifying training needs.
• Traffic control: in cities, AI systems are used for traffic monitoring and optimization to improve traffic flow.
• Cybersecurity: AI can help monitor networks and systems for threats and take quick countermeasures.
• Translation and speech processing: AI can translate texts in real-time and enable human-like speech in chatbots and virtual assistants.

Now that we’ve talked so much about artificial intelligence – what concrete first steps can companies/leaders take? How can we incorporate AI into our everyday work step by step?

• Education and training: Start with training and education for leaders and employees to foster a basic understanding of AI and its applications.
• Identify use cases: Identify specific areas or tasks in your organization where AI could add value. These could be tasks with high data content or routine tasks.
• Data preparation: make sure your data infrastructure is solid. Clean, high-quality data is critical to successful AI applications.
• Pilot projects: Launch small pilot projects to test the feasibility of AI applications in your organization. This allows you to gain initial experience.
• Partnerships and outsourcing: Consider working with AI experts and vendors to leverage expertise and resources without building everything in-house.
• Ethical guidelines: Develop ethical guidelines for the use of AI to ensure that the technology is used responsibly and in line with your values.
• Communication and change management: Make sure you inform your employees about the introduction of AI and demonstrate the added value for them. Consider fears and concerns.
• Measuring ROI: Establish clear KPIs to measure the return on investment (ROI) of your AI initiatives and ensure they are delivering business value.
• Scale: if pilots are successful, consider scaling up and expanding the use of AI in other areas.
• Feedback and adaptation: continuously gather feedback from employees and adapt your AI strategy accordingly for continuous improvement. 

One last question I’d like to ask all of our guests. What do you see as the biggest challenge for leaders in the next 5 years?

Overall, leaders in the next 5 years will face the challenge of balancing technological innovation, business growth, and social responsibility while facing a rapidly changing business environment and changes in the socio-cultural environment. The ability to adapt and use technology strategically will be critical.

• Digital transformation: leaders must successfully guide their companies through digital transformation, which means adapting business models, processes and culture to remain competitive.
• Change in the socio-cultural environment: Generation Z, born in the late 1990s and 2000s, is shaping the socio-cultural environment with new values and behaviors. Their influence has led companies to pay increased attention to social responsibility and adapt their marketing strategies to reach this target group.
• Talent management: attracting and retaining technology and data science professionals will be a challenge. Leaders must be able to build and develop talented teams.
• Rapid change: Technological developments and market changes occur rapidly. Leaders must be agile and adaptable to respond to unexpected events.
• Global uncertainties: Economic uncertainties, geopolitical tensions, and global crises could affect business operations. Leaders need to be resilient and develop risk management strategies.
• Sustainability: sustainability goals and environmental impacts are gaining importance. Leaders must develop strategies to be environmentally responsible.
• Workplace culture and employee well-being: Creating a positive workplace culture and employee well-being is becoming increasingly important to attract and retain skilled workers.

Thank you for this exciting interview, Michael!

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