Putting the Human Ahead of AI

Christa Swain • April 16, 2025

This article was originally published in the HRDirector


The Urgent Need for Workforce Upskilling 


AI enhances efficiency, but humans drive the strategy. While artificial intelligence can process vast amounts of data in seconds, it is human insight and strategic thinking that transform that data into meaningful decisions. The future isn’t just about machines... it’s about how we, as humans, leverage those machines to create smarter, more effective outcomes. 


HR leaders are at the forefront of this transformation. As AI, data, and digital technologies reshape industries, the real challenge isn’t just integrating these tools - it’s equipping people with the skills to collaborate effectively with them. Future-ready organisations understand that investing in human potential is just as critical as investing in technology. Businesses that fail to embrace the efficiencies of transformation risk falling behind, while transformation itself will falter without a mindset that embraces change and fosters adaptability, collaboration, and innovation. By cultivating a culture of continuous learning, organisations can drive successful transformation while enhancing engagement and retention. 


The Human Advantage in an AI-Driven World 


AI is revolutionising the way we work, automating tasks, streamlining processes, and providing insights at an unprecedented speed. Yet even the most advanced AI lacks the creativity, emotional intelligence, and strategic foresight that only humans possess. 


Human skills such as critical thinking, empathy, and communication differentiate successful teams from those that simply follow the data. AI can analyse information, but it takes human judgement to contextualise that data and make decisions that align with business goals and ethical considerations. 


"AI accelerates data processing, but it's human creativity and strategic thinking that transform information into actionable decisions." 

Phil Yeoman, CDO  


The Rise of Power Skills 


Technical expertise alone is no longer sufficient for achieving organisational success. The emphasis has shifted towards "power skills", formerly known as soft skills, which are pivotal in fostering effective collaboration and driving business growth. 


The Evolution from Soft Skills to Power Skills 


Historically, attributes such as communication, empathy, and adaptability were labelled as "soft skills", often perceived as secondary to technical abilities. However, recent insights underscore their critical importance, leading to their rebranding as "power skills". This shift highlights their role in empowering individuals and teams to excel in collaborative environments. 


A study by Pearson in 2022 revealed that the top five most in-demand skills across major job markets are human-centric, including collaboration and customer focus. This trend is projected to continue, especially with the growth in AI, emphasising the sustained value of power skills in the workforce. 


Cultivating Human Skills in the Workplace 


Recognising the importance of power skills, businesses are investing in their development to enhance collaboration and overall performance. 


  • Gamified learning and team simulations offer experiential learning that increases engagement, retention, and application. Who does not like learning through play? 
  • Mentorship programmes have emerged as effective tools in skill-building. Research highlighted by Reuters indicates that mentored individuals earn 15% more than their non-mentored peers, attributing this to improved confidence and teamwork abilities. 
  • The rise of "fractional twinning", where part-time executives share roles, underscores the demand for adaptability and emotional intelligence in leadership positions. This approach allows businesses to access specialised skills flexibly, fostering a culture of continuous learning and collaboration. 


In an era where technological advancements are reshaping industries, power skills remain the cornerstone of effective collaboration and business success. By prioritising the development of these skills, organisations can cultivate resilient, innovative, and cohesive teams poised to navigate the complexities of the modern workplace. 


Why We Learn Better Together 


Learning is often seen as a solitary pursuit, but research consistently shows that learning in social contexts significantly enhances understanding, retention, and application of knowledge. Whether through collaboration, simulation, discussion, or observation, social learning taps into our innate human tendencies to connect and share, making it a powerful tool for professional development. 


The Science Behind Social Learning 


Social learning is grounded in neuroscience and psychology. Studies indicate that when we learn in groups, our brains are more engaged, and we process information more deeply. Consider these key insights: 


  • Collaborative Learning Increases Retention: A study published in Psychological Science found that people who learn through discussion, group activities, or simulations retain up to 50% more information than those who study alone. 
  • The Role of Mirror Neurons: When we observe others performing tasks, our brain’s mirror neurons activate, helping us understand and replicate their actions more effectively. 
  • Boosting Cognitive Load Management: Group learning allows individuals to divide complex tasks, reducing cognitive overload and enhancing problem-solving efficiency. 

Social learning does not just help us remember facts, it helps us apply what we have learned in practical, real-world contexts, making it an essential approach for workforce upskilling. 


How Social Learning Shapes Professional Success 


In the workplace, social learning is a cornerstone of effective training and collaboration. Consider these statistics: 


  • 70:20:10 Learning Model: Research shows that 70% of workplace learning happens through on-the-job experiences, 20% through social interactions, and only 10% through formal training (Centre for Creative Leadership). 
  • Faster Skill Acquisition: Teams that engage in collaborative learning complete training programmes 30% faster than those relying on individual learning (Harvard Business Review). 
  • Knowledge Sharing Boosts Innovation: Companies that encourage peer-to-peer learning see a 25% increase in innovation due to the diverse perspectives shared in group settings (McKinsey & Company). 

By fostering a collaborative environment, organisations can upskill employees more efficiently while creating a culture of continuous improvement. 


Harnessing the Benefits of Social Learning 


Whether in classrooms or corporate offices, organisations can implement social learning strategies to maximise impact. Here is how: 


  • Encourage Collaboration: Use group projects, team brainstorming sessions, and peer feedback to foster interactive learning. 
  • Leverage Technology: Digital tools enable seamless collaboration, and simulation activities offer immersive, experiential learning that enhances retention. 
  • Create Safe Learning Spaces: Cultivate an environment where learners feel comfortable sharing ideas, asking questions, and learning from mistakes. 

By integrating social learning principles into your strategy, you can unlock higher engagement, deeper understanding, and better outcomes. 


The Takeaway 

Humans are social creatures, and our learning thrives when it is collaborative. Whether we are working on a group project, sharing insights with colleagues, or discussing ideas in a boardroom, social learning makes the process more effective, enjoyable, and impactful. 


“If you want to go fast, go alone. If you want to go far, go together.” 


The future belongs to those who lead it. By embracing the power of social learning and prioritising human skills alongside AI advancements, organisations can ensure they stay ahead and are future fit. 


By Christa Swain December 3, 2025
Executive Summary: AI, Ethics, and Human-Centred Design Our recent Leaders Advisory Board event - designed in partnership with Corndel - featured three engaging sessions that explored how AI impacts human cognition, customer experience, and fairness. Here's what we learnt: 1. Think or Sink – Are We Using AI to Enhance or Reduce Cognitive Ability? Speaker: Rosanne Werner , CEO at XcelerateIQ & ex Transformation Lead at Coca-Cola Roseanne opened the day with an interactive and thought-provoking session, firmly positioning AI: “AI should be your sparring partner, not your substitute for thinking.” Her research revealed a striking insight: 83% of people using LLMs couldn’t recall what they wrote, compared to just 11% using traditional search . The message? It’s not about avoiding AI, but using it in ways that strengthen thinking , not outsource it. Roseanne explained how our brains form engrams - memory footprints that enable creativity and critical thinking. Over-reliance on AI risks weakening these pathways, reducing retention and problem-solving ability. She introduced the Mind Over Machine Toolkit , six strategies to use AI as a thinking partner: Provide Context First – Frame the problem before asking AI. Use AI as a Challenger – Stress-test ideas and uncover blind spots. Iterative Co-Creation – Collaborate, refine, and evaluate. Document Your Thinking – Keep reasoning visible. Reflective Prompts – Support reflection, not replace judgment. Sparring Partner – Test assumptions and explore risks. Roseanne summed it up with a simple rule: use Sink for low-value, repetitive tasks, and Think for strategic, creative decisions. 2. Designing Chatbots with Human-Centred AI Speaker: Sarah Schlobohm , Fractional Chief AI Officer Sarah brought a practical perspective, drawing on experience implementing AI across sectors - from banking and cybersecurity to rail innovation. She began with a relatable question: “Who’s been frustrated by a chatbot recently?” Almost every hand went up. Through a real-world example (redacted out of politeness), Sarah illustrated how chatbots can fail when designed with the wrong priorities. The chatbot optimised for deflection and containment , but lacked escape routes , sentiment detection, and escalation paths - turning a simple purchase into a multi-day ordeal. “Don’t measure success by how well the chatbot performs for the bot—measure it by how well it performs for the human.” Sarah introduced principles for better chatbot design: Human-Centred Design – Focus on user needs and emotional impact. Systems Thinking – Consider the entire process, not just chatbot metrics. Escalation Triggers – Negative sentiment, repeated failures, high-value intents. Context Awareness – Detect when a task moves from routine to complex and route accordingly. The takeaway? Automation should remove friction from the whole system - not push it onto the customer. 3. Responsible AI and Bias in Large Language Models Speaker: Sarah Wyer , Professional Development Expert in AI Ethics at Corndel “When we create AI, we embed our values within it.” She shared her journey tackling gender bias in large language models , from GPT-2 through to GPT-5, and highlighted why responsible AI matters. AI systems reflect human choices - what data we use, how we define success, and who decides what is fair. Real-world examples brought this to life: facial recognition systems failing to recognise darker skin tones, credit decisions disadvantaging women, and risk assessment tools perpetuating racial bias. Even today, LinkedIn engagement patterns show gender bias! Sarah made the point that simple actions - like testing prompts such as “Women can…” or “Men can…” - can reveal hidden disparities and spark vital conversations. To address these issues, Sarah introduced the D.R.I.F.T framework , a practical guide for organisations: D – Diversity : Build diverse teams to challenge bias. R – Representative Data : Ensure datasets reflect all user groups. I – Independent/Internal Audit : Test outputs regularly. F – Freedom : Create a culture where employees can challenge AI decisions. T – Transparency : Share processes without exposing proprietary code. Wrapping up the final session - before we opened the floor to panel questions and debate - Sarah created the opportunity to discuss how we address AI bias within our organisations by stepping through the DRIFT framework. Shared Themes Across All Sessions AI is powerful, but context matters . Human oversight and ethical design are critical . Use AI to augment thinking , not replace it. Measure success by human outcomes , not just automation metrics. We've had such great feedback from this event series - especially around the quality of speakers and the opportunity to have meaningful conversation and debate outside of functions. Definitely more in the events plan for 2026! If you'd like to be part of the conversation please navigate to our LAB events page to register your interest .
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