Soft skills. Essential to support AI technology?

Often, the soft skills that help to build the connection between an employee, their job, their organisation, and their colleagues are seen as less important than the more tangible, technical skills that connect employees to the physical function of their jobs. But will the rise of AI with its increased demand for technical skills actually make soft skills more important in the ‘4th Industrial Revolution’?

Soft skills refer to personal attributes, communication abilities, and interpersonal skills that enable individuals to work effectively with others and its these skills that create the environment of belonging and purpose that increases employee engagement and productivity and reduces staff turnover. While AI technology primarily deals with data analysis, automation, and problem-solving, there are several areas where soft skills become valuable:

1.     Communication: AI professionals need to communicate complex concepts, findings, and insights to stakeholders, clients, and team members who may not have technical expertise so clear and concise communication ensures that AI solutions are understood, properly utilised, and aligned with the needs of the organisation or end-users.

2.     Collaboration: AI projects often involve multidisciplinary teams, including data scientists, engineers, domain experts, and business professionals so collaboration and teamwork are essential for integrating various perspectives, leveraging diverse expertise, and ensuring that AI solutions address the specific requirements and challenges of the organisation.

3.     Creativity and Innovation: While AI algorithms excel at pattern recognition and data analysis, creativity and innovation are still largely human capabilities. Soft skills related to creativity, ideation, and thinking outside the box can help AI professionals identify new ideas, explore innovative solutions, and envision AI applications beyond traditional approaches.

4.     Critical Thinking: AI systems often encounter complex issues, ambiguous problems, or unexpected challenges that require human intervention and decision-making. Critical thinking and problem-solving skills help in assessing AI outputs, identifying biases, interpreting results, and making informed judgments.

5.     Ethical considerations: As AI continues to advance, ethical considerations become increasingly important. Soft skills like ethical reasoning, empathy, and critical thinking can help in navigating the ethical implications of AI, such as data privacy, bias, and fairness and AI professionals must consider the broader social and ethical implications of their work.

6.     Adaptability: The field of AI is rapidly evolving, and professionals need to adapt to changing technologies, tools, and methodologies. Soft skills such as adaptability, flexibility, and a growth mindset can facilitate the learning and integration of new AI techniques and frameworks.

7.     User Experience: Soft skills like user experience, design, empathy, and user research are valuable in AI projects that involve human interaction. Understanding user needs, preferences, and behaviours can lead to the development of AI systems that are intuitive, user-friendly, and aligned with end-user expectations.

Soft skills are increasingly being recognised as crucial in the field of AI. While AI technologies excel at data analysis and automation, they still rely on human involvement for their development, deployment, and application. Soft skills complement the technical aspects of AI by fostering effective communication, collaboration, critical thinking, ethical considerations, creativity, and user-centric approach, all essential in successfully navigating the new world of work.