The rise of AI has sparked fears of mass job displacement. But in reality, the future of work isn’t about who gets replaced, but how people skills need to be enhanced to work in tandem with AI, writes Cranfield School of Management’s Steve Macaulay.
The proliferation of AI is only pushing the importance of soft skills further into view.
Cranfield School of Management’s Steve Macaulay delves into the myriad reasons why the two should be viewed as essential partners.
HR leaders focused on the future of work should be developing their action plan to maximize returns on both AI and soft skills in tandem.
Human skills neatly complement AI: AI excels at automating tasks, freeing us to focus on what machines can’t replicate: human ingenuity and flexibility.
This isn’t science fiction; it’s the reality unfolding before us and presents a key challenge for HR professionals.
Soft skills – communication, empathy, critical thinking, creativity – are the cornerstone of human interaction and innovation.
They have the potential to open up new possibilities if skills can work harder and more successfully, for example in strengthening:
Customer Centricity: Building trust and rapport with clients is essential in a competitive landscape.
AI can’t replicate the human touch that fosters loyalty and satisfaction.
Teamwork and Collaboration: The ability to work effectively across departments and backgrounds is crucial for tackling complex challenges.
Soft skills are the glue that binds diverse teams into a high-performing unit.
Leadership and Inspiration: Motivating and guiding others is a uniquely human strength.
AI can analyze data, but it can’t inspire a team to achieve that extra effort.
Strategic Problem-Solving: The world throws curveballs.
Critical thinking and creative problem-solving are essential for navigating unexpected challenges and finding innovative solutions.
HR and L&D leaders can help their teams develop ‘soft skills superpowers’ to thrive alongside AI.
This implies:
Rethinking recruitment: Look beyond technical skills. Prioritize candidates with strong soft skills who can thrive in a fast-paced, collaborative environment.
Ongoing development: Soft skills need regular practice. Integrate continuous development programs into performance management, linking them to personal and company goals.
Real-world learning: Create cross-functional project teams where employees can practice communication, collaboration, and problem-solving in real scenarios.
Mentorship and coaching: Pair experienced employees with high-potential individuals to share knowledge and accelerate soft skill development.
Learning culture: Offer workshops and training programs focused on specific soft skills like communication, conflict resolution, and creative thinking.
Investing in soft skills offers substantial benefits.
Employee engagement: Employees who feel valued for their soft skills are more engaged, productive, and less likely to leave.
Innovation: A culture that nurtures creativity produces new ideas, keeping your company ahead of the competition.
Employer branding: A reputation for developing well-rounded employees attracts top talent and strengthens your brand.
Developing soft skills is challenging.
Key factors include:
Subjectivity: Unlike technical skills, soft skills are subjective and context-dependent.
Lack of clear metrics: Measuring soft skills is difficult without standardized metrics.
Continuous practice: Soft skills require ongoing practice and adaptation to different situations.
Feedback and guidance: Obtaining specific feedback on soft skills can be challenging due to their complex nature.
Collaboration between humans and AI presents unique challenges:
Communication: Effective communication between humans and AI is crucial. Misunderstandings can arise due to AI’s limited understanding of nuances in human language.
Modelling human behavior: AI systems need to understand human behavior, which is complex and variable.
Long-term interactions: Maintaining productive long-term interactions between humans and AI requires AI to adapt to changing human roles and preferences.
Scalability: Scaling AI-human collaboration across larger teams or different domains while maintaining efficiency is challenging.
Safety: Ensuring the safety of human collaborators in environments where they work alongside AI is critical.
Privacy: Collaborative AI systems often require access to sensitive data, raising privacy concerns.
Ethics: AI systems must align with ethical standards, ensuring fairness, accountability, and bias mitigation.
Metrics and benchmarking: There is a lack of standardized metrics for evaluating AI-human collaboration, making it difficult to measure success.
Human wellbeing: AI systems can impact the social and psychological well-being of humans, especially if they replace roles that provide a sense of purpose.
We believe energy must be applied in these areas to ensure AI is successfully married with enhanced people skills.
We have suggested example actions to get this partnership between soft skills and AI embedded into the organization.
Communication:
Modelling human behavior:
Long-term interactions, scalability, safety, and privacy:
Ethics, metrics & benchmarking, human wellbeing, and AI agency:
By addressing these challenges, organizations can create environments where AI enhances human abilities and fosters essential soft skills.
For HR and L&D leaders, the future isn’t about who gets replaced by AI, but who gets left behind. It would be a mistake to leave soft skill/AI partnerships to others.
Investing in your people’s soft skills is key to thriving in the AI era, turning your workforce into a powerful asset.
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Learning development associate
Steve Macaulay is an associate of Cranfield Executive Development.
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