The Other Side of AI : Human Capabilities as Infrastructure

Artificial Intelligence (AI) is transforming our economies in many ways. It is changing the way we work, how value is created and even what we value. Organisations across almost all industries are finding themselves in the midst of or preparing for business transformation towards a new AI-human collaboration model.

Despite a general consensus that the future of work includes significant AI-human collaboration across most parts of the economy, this is yet to be translated into real resource allocation. Attention and investment are primarily poured into technical infrastructure, licensing and subscriptions. Public and corporate discussions focus on the latest technology capabilities, adoption rates, efficiency and productivity gain and the ROI on AI investment. Or, conversely, on expected negative societal level impacts, such as increased unemployment and job displacement. 

But little attention is being paid to the other side of that collaboration - the humans. Uniquely human capabilities, such as critical thinking, judgement, collaboration, creativity and effective leadership, are taken for granted, poorly understood and left unnurtured. Investment into fostering workforce skills is often overlooked and un-budgeted beyond the technical skills to use those AI tools.

In the meantime, there is a body of evidence that suggests that human capabilities are at the risk of erosion due to increasing dependency on AI technologies. For example, Gerlich (2025) identified ‘a significant negative correlation between frequent AI tool usage and critical thinking abilities, mediated by increased cognitive offloading’. We are outsourcing critical thinking. Like any muscles, without regular exercise, our cognitive abilities quietly decline. Some suggest that such erosion could be more significant in younger generations due to higher levels of AI usage.

All these suggest that inaction leads to a steady decline in the workforce capability and potentially to a cliff edge in the future talent pipeline. Human capabilities require a long time to develop and can be lost quickly with poor management and neglect. As a significant portion of strategic assets, the matter requires urgent attention at a senior level of every organisation as well as policy makers.

Many organisations are now at a crossroads. AI brings an opportunity to transform organisations to become genuinely agile, resilient and innovative. Those who understand and manage the AI-human dynamics well will secure their positions as industry leaders; whereas those who continue to focus primarily on technology and to underestimate the required organisational changes will find themselves wasting resources and struggling to remain competitive in the long run.

The Missing AI Enabler 

AI adoption is not optional for most organisations. While organisations are rightly treating AI initiatives as the highest priorities, many are still struggling to see clear signs of ROI (return on investment). The data vary across reports but the key message is consistent - across many geographies and sectors, fewer than half of organisations report material AI benefits. For example, McKinsey’s study (2025) revealed that 39% reported EBIT (Earnings Before Interest and Taxes) impact at the enterprise level.

Equally consistent is the report that human factors are the major root cause. Effective AI adaption requires redesign of workforce structure and workflows, underpinned by a clear sense of business purpose and vision. Boston Consulting Group (BCG) advocates 10/20/70 rule for successful AI adoption (BCG, 2024). 70% of a company’s efforts should be focused on people and processes, 10% on algorithms, and 20% on data and technologies. In the current reality, however, these figures in budget allocations are reversed, if not worse. According to Deloitte’s study (Deloitte, 2025), as high as 93% of AI transformation budget goes to tech and mere 7% to people.

Clearly there is a gap between what is required for successful AI adoption and business performance improvement and what organisations are prioritising. At the heart of it are human capabilities, such as critical thinking, judgement, effective communication, collaboration, creativity, agility and ethical judgement. These are essential infrastructure for the successful AI initiatives along with the physical infrastructures, such as utilities, data centres and IT systems. These human capabilities need to be prioritised and invested accordingly.

Source of Differentiation  

As AI tools become ubiquitous, human capabilities will become the primary source of competitive advantage. The same set of tools is available to your competitors - how value is created across organisations is what differentiates them. That heavily depends on how well humans bring their unique capabilities - contextual understanding, innovating, collaborating effectively and building trust of clients or customers.

Yet human capabilities are often managed inadequately, let alone invested in beyond the point of initial recruitment. Once individuals are within an organisation, there is rarely a systematic way of developing their capabilities continuously beyond technical qualifications, sporadic workshops or obligatory training modules on compliance. Particularly in the age of AI where business landscapes are changing fast across the whole global economy, any capable person would need constant upskilling to adapt to the change.

The skills gap within organisations is costing organisations and the wider economy. BCG reported in 2020 that the skills mismatch cost the world economy $8 trillion in lost productivity, which, albeit dated, shows the magnitude of impact and missed opportunity. Another study by Perceptyx (Killham, 2026) suggests poor management costs the U.S. economy $500 billion annually and estimates even 5-point improvement in manager effectiveness could save the US economy approx. $32 billion a year. The potential loss for organisations and economies from neglecting the skills gap is material and cannot be ignored. 

The cost of neglecting human elements extends beyond day-to-day performance and is a major cause of business transformation failures (Bain & Company, 2024). Understanding capabilities both in terms of existing workforce and future requirements is critical for successful organisational transformation - from transformation strategy development to implementation phases that often span multiple talent cycles.

Investment in human capital enhances organisational performance across sectors and scales (Garavan et al., 2021; Kim et al., 2025). Organisations will benefit from treating human capabilities as a critical infrastructure of the business and incorporating them into strategic planning and resource allocations accordingly.

Driving Transformation 

Organisations leading the business transformation in the AI era are beginning to realise the strategic importance of human capabilities and treating them as infrastructure. The successful business transformation hinges on the clarity of enterprise strategy, including a competency strategy for the AI era. That needs to be informed by a deep understanding of existing human capabilities within the workforce and by a blueprint of where it should be and the gaps to be filled. Organisations require a systematic way of assessing, developing, nurturing and recognising human capabilities both to leverage AI to its full potential beyond simple tool adoption and to carry the organisation through the transformation ahead.

This is not a small task but it is an urgent one. It requires as much attention and resources as AI tools, if not more, and close collaboration across organisation, technology and people domains. 

Where to start? One can start by asking the following questions:

• What exactly are the objectives of your business transformation? 

• How can you make the most of your workforce for value creation?

• How can you create a high performing culture?

• How can you measure this, both at an individual and an organisational level?

• And how can you identify, nurture and elevate exceptional practitioners across your organisation?

If these questions resonate with you, let’s discuss more. 

References

Burke, M. 15 April 2024. 88% of business transformations fail to achieve their original ambitions; those that succeed avoid overloading top talent. Press release, Bain & Company. 

Gerlich, M. AI Tools in Society: Impacts on Cognitive Offloading and the Future of Critical Thinking. Societies 2025, 15, 6. 

BCG, 12nd December 2024. The Leader’s Guide to Transforming with AI. BCG. 

Deloitte Insights, 10th December 2025. Tech Trends 2026. Deloitte Development LLC. 

Hoteit, L. et al., 2020, Alleviating the Heavy Toll of the Global Skills Mismatch, BCG. 

Killham, E. 25 February 2026, 2025 Special Report, The Great Management Meltdown: Why 58% of Leaders Want Out and What It Means for Business, Center for Workforce Transformation by Perceptyx

Singla, A. and Balakrishnan, T. et al. The State of AI in 2025: agents, innovation, and transformation. November 2025, McKinsey & Company.

Slagt, P., et al. 15 April 2024. The Three Common Transformation Talent Mistakes and How to Avoid Them. Brief. Bain & Company.  

Garavan, T., McCarthy, A., Lai, Y., Murphy, K., Sheehan, M. & Carbery, R. (2021). Training and organisational performance: A meta-analysis of temporal, institutional and organisational context moderators. Human Resource Management Journal, 31(1), pp. 93–119.

Kim, J., Chang, H. & Bell, B.S. (2025). Organizational-level training and performance: A meta-analytic investigation. Journal of Management. DOI: 10.1177/01492063251327588