Human skills meet AI: Redesigning work and skills for future

The old playbook of periodic, standardised training no longer cuts it. Instead, companies should embrace continuous, personalised learning embedded within everyday work to keep pace with evolving demands. 

A survey from Mercer’s Global Talent Trends highlights a stark reality: about 60% of HR and business leaders in Asia acknowledge they implement new technologies without transforming how work is done, leading to productivity drains fueled by “too much busy work”. This disconnect points to a wider challenge facing companies worldwide, and technology adoption alone does not guarantee workforce readiness or well-being. 

Similarly, the World Economic Forum’s (WEF) report underscores that while 86% of employers in key European countries expect AI to become central to their operations by 2028, only about 15% globally are investing adequately in human adaptability and resilience, the very traits that will determine whether organisations flourish or falter. 

In this context, Demis Hassabis, Google DeepMind CEO and 2024 Nobel laureate, recently offered an insight during his keynote at the foot of Athens’ Acropolis: “The only thing you can say for certain is that huge change is coming.” He stressed that the most critical skill for the next generation will be “understanding how to learn”, the ability to rapidly acquire and apply new knowledge as AI continues to evolve at breakneck speed. 

These findings converge on a single point: organisations must rethink learning and development (L&D) from the ground up, creating agile, human-centric, AI-enhanced systems that equip employees to continuously reskill, upskill, and thrive.  

The first step toward building an adaptable workforce lies in work redesign, a strategic review and reallocation of roles, responsibilities, and tasks to better align talent with emerging organisational needs. According to Mercer's survey, over 50% of executives predict that AI and automation will lift productivity by 10%-30% over the next three years. Yet these benefits hinge entirely on whether companies can adjust their workforce models accordingly. 

Traditional talent frameworks, heavily focused on fixed job functions, often lack the flexibility needed in today’s fast-changing environment. Shifting to skills-based workforce models allows companies to uncover hidden skill gaps and better target training initiatives. For instance, Mercer’s data shows that 63% of HR professionals in Asia have already seen productivity gains from such work redesign efforts. 

McKinsey research reinforces these conclusions, emphasising that skills-centric workforce planning enhances organisational agility by enabling rapid team scaling or pivoting, and facilitates strategic deployment of talent freed from repetitive, automated tasks. 

While AI and automation reshape tasks, the human element remains paramount. KPMG’s analysis highlights that learning programmes must be designed with empathy, tailored to individual strengths, career goals, and learning preferences. Unlike generic one-size-fits-all approaches, personalised learning paths engage employees by allowing them choice and control over what, how, and when they learn. 

Further, KPMG urges companies to foster psychological safety, cultivating environments where employees feel secure enough to experiment, make mistakes, and ask questions without fear. This support is essential as many workers, especially those without deep technical backgrounds, grapple with the stress of mastering AI alongside daily responsibilities. 

Industry voices echo this sentiment. Experts describe AI-driven learning as a revolution comparable to the industrial era, with tools that can customise content and nudge learners back on track, minimising drop-offs while preserving human connection. 

The WEF further stresses that with AI handling routine tasks, emotional intelligence, adaptability, and critical thinking will become the critical human skills of the future. Companies, therefore, should ensure training balances technical proficiency with these soft skills to build truly resilient teams. 

Not all technology investments yield equal returns. Legacy learning management systems (LMS) may struggle to support the shift to skills-based development. According to KPMG, organisations can critically evaluate their current tools and adopt AI-enabled platforms capable of real-time skills assessments, predictive analytics, and seamless integration with existing workflows.

Mercer’s Skills Snapshot Survey reveals that over 75% of companies in Asia are already using or plan to use AI to identify skills gaps and forecast future talent needs, demonstrating a growing reliance on data-driven workforce planning. 

McKinsey highlights that the power of technology lies not only in tools but in embedding data insights into strategic decision-making, enabling leaders to anticipate skill demands and design targeted upskilling journeys that maximize both individual and organisational potential. 

The days of detached, classroom-style learning are numbered. AI now makes it possible to embed learning directly into daily workflows, delivering just-in-time training that supports productivity while building skills incrementally. 

AI-driven platforms enable personalised, adaptive learning paths that evolve with employees’ progress, ensuring relevance and engagement. This approach also integrates continuous feedback loops, allowing organisations to measure effectiveness and adjust offerings dynamically. 

Experts emphasise how AI-generated content drastically accelerates learning material production, from months to hours, allowing companies to respond in real-time to evolving business needs, regulatory changes, or product launches. 

Mercer’s findings also echo these advantages, showing that organisations embracing continuous, embedded learning experience stronger employee engagement, better skill retention, and enhanced productivity. 

Upskilling and reskilling are no longer just HR priorities, rather they are vital business imperatives. Mercer’s survey highlights that half of executives see employee development as the single most powerful lever for driving productivity in a machine-augmented future. 

KPMG’s AI-powered learning platforms allow organisations to design highly customised upskilling and reskilling programmes aligned with specific strategic goals, creating pathways for career mobility and talent retention. 

The WEF adds that these initiatives must be deliberate and data-informed, leveraging external industry trends to ensure the workforce possesses the right mix of digital and human skills to meet evolving challenges. 

Companies that successfully implement these strategies position themselves to outpace competitors not only in efficiency but also in innovation and employee engagement, securing a resilient future in an uncertain landscape. 

Demis Hassabis’ words resonate deeply: “You’re going to have to continually learn… throughout your career.” In the face of AI-driven transformation, the future belongs to those organisations that invest in people, equipping them with adaptive skills, human-centered learning experiences, and technology that amplifies rather than replaces human potential. 

As multiple reports converge, one truth stands out: thriving in the age of AI requires reimagining learning and work as an ongoing, integrated journey, not a one-off event. 

By redesigning work around skills, embedding AI-enhanced learning in everyday routines, and centering empathy and personalisation, companies can build the adaptable, resilient workforce that tomorrow demands.