AI and cultural intelligence: The future of intercultural leadership

In today’s globalised world, intercultural skills are becoming increasingly important for top management leaders to manage cultural differences, understand the needs of all stakeholders, and create an inclusive environment. As artificial intelligence (AI) becomes more prevalent in the workplace, it’s important to consider its impact. The question lies with how AI will shape the awareness and management of cultural differences.

This article explores the intersection of AI and intercultural leadership and the implications for organisations and leaders.

AI refers to the ability of machines to perform tasks that typically require human-level intelligence. This includes things like speech recognition, decision-making, and problem-solving. AI systems can be trained to learn from data and adapt to new situations, making them highly effective in a variety of applications. Some examples of AI-powered technologies include chatbots, self-driving cars, and image recognition software.

How can AI technology help individuals and organisations better understand and navigate cultural differences? By analysing large amounts of data on cultural norms, behaviors, and values, these systems could provide insights that may help leaders understand their own perspectives and the perspectives of others, which could lead to more effective communication and collaboration. They could also offer personalised experiences based on cultural preferences, improving user engagement and satisfaction.

A Deloitte report states that “AI can help organisations identify the cultural drivers of productivity, such as communication styles, work habits, and decision-making processes, and then use this knowledge to build more effective teams.”

AI can also help leaders identify and address cultural biases in the workplace. In a study conducted by Harvard Business Review, researchers found that “AI tools can help eliminate bias in the hiring process by identifying patterns of bias in job descriptions and resumes.”

According to an article by Simplilearn, some ways AI can help eliminate bias in hiring include: pinpointing troublesome language and gender-coding in job descriptions so organisations can leverage inclusive, gender-neutral language; focusing on specific skills and excluding identifiers like gender, names, titles, and education; and expanding the recruiting process to a broader pool of candidates who might be outside-of-the-box, but bring a unique, fresh perspective to a role  

This is important because bias in the hiring process can lead to a lack of diversity in the workplace, which can be detrimental to business performance. However, together with the opportunities, come the challenges and the actual reality of AI technologies.

Is AI unbiased?

Insight by  Deloitte highlights that there is a “risk of AI-compatible cultural bias, which could lead to the exclusion of certain groups of employees or customers.” It is important that leaders ensure their AI systems are designed and implemented to avoid any bias towards certain cultural groups. This requires a deep understanding of cultural differences and an awareness of the potential impact of AI on different cultural and marginalized groups.

Regarding the use of AI in recruitment, one major challenge is that AI algorithms are only as unbiased as the data they are trained on. An example mentioned in an article on Enterprise Talk states that if an AI algorithm is trained on historical hiring data that contains bias against certain groups of candidates, then the AI may also exhibit bias against those groups.

A very interesting documentary (now available also on Netflix), Coded Bias points out how recruiting can be highly biased. AI, driven by the concept of Machine Learning, has the remarkable ability to continuously learn and adapt based on the data it receives. However, this process is not immune to the unconscious biases that exist within human society. Unfortunately, during the development of such technologies, these biases can find their way into the algorithms, leading to skewed outcomes and unintended consequences.

One prominent example of this issue can be found in facial recognition software. Many of these systems were trained using data sets that predominantly consisted of certain ethnic groups, inadvertently excluding or limiting the accuracy of recognition for other groups. This bias can have far-reaching implications, from discriminatory surveillance practices to false identification.

Similarly, another notable case involves Amazon’s AI recruiting tool. The tool, developed predominantly by male engineers, exhibited a bias against female candidates. This bias arose from the training data, which was based on historical hiring patterns that favored male applicants. Recognising the inherent flaws and ethical concerns, Amazon rightly made the decision to abandon the use of this software.

These instances highlight the importance of addressing biases within AI systems. It is crucial to ensure that the data used for training is diverse and free from discriminatory patterns.

To build AI systems that are fair, inclusive, and unbiased, organizations need to invest in diverse teams and promote inclusive practices. By doing so, they can work towards creating a future where AI technologies empower and benefit all individuals, regardless of their background or identity.

Future Trends of AI in Intercultural Leadership

A report by Gartner predicts that “by 2025, 75 per cent of organisations will include diversity and inclusion metrics in their executive scorecards, and 50 per cent of those metrics will be enabled by AI algorithms.” This suggests that AI will play a key role in promoting diversity and inclusion in the workplace.

One potential application of AI in intercultural leadership is the use of chatbots to facilitate intercultural communication. Chatbots can be programmed to understand cultural differences and adapt their communication style accordingly. This can help to overcome language barriers and promote effective communication between individuals from different cultural backgrounds.

Another potential application of AI in intercultural leadership is the use of virtual reality (VR) to simulate intercultural interactions. VR can be used to create realistic simulations of different cultural environments and scenarios, allowing leaders to develop their cultural intelligence in a safe and controlled environment. It is possible that VR could be used for training, in combination with AI to create immersive simulations of intercultural interactions in the workplace. This can help with developing soft skills such as conflict resolution, teamwork and leadership.

In conclusion, AI has the potential to help leaders develop their intercultural leadership skills by providing insights into how people behave in different cultures and by identifying and  addressing cultural biases in the workplace. However, it is important for leaders to ensure their AI systems are designed and implemented to avoid any bias towards certain cultural groups. As we move into the future, it will become increasingly important for leaders at all levels to develop their cultural intelligence and intercultural skills to ensure they can effectively navigate cultural differences and promote inclusive workplaces. The key to effective Intercultural leadership in an AI-driven world is to strike a balance between leveraging the benefits of technology and maintaining a human touch in relationships.

The author would like to thank Akhil Nair, GMD intern, for his support in the research and writing for the present article.