Abstract
Recent advances in technology continue to reshape the workplace, and with them come ongoing concerns about skills gaps and the challenges organisations face in recruitment. The latest Manpower 2026 UK Talent Shortage report (https://www.manpowergroup.co.uk/uk-talent-shortage-2026/) shows that, although there has been a slight improvement compared with previous years, the problem remains significant, with 73% of organisations still reporting difficulty in filling roles.
Notably, while artificial intelligence (AI) remains high on the agenda, the report suggests that the greatest shortage is not in technical AI expertise itself, but in AI literacy and development. This points to a growing need for workplaces in which people and AI can work together effectively, supported by the right knowledge, confidence and organisational culture.
This challenge is not limited to the UK. Globally, 72% of businesses are also struggling to find the skilled talent they need. The information sector is similarly affected. Although it does not appear among the three most severely affected sectors, it ranks a close fourth, with 74% of organisations reporting difficulties in recruiting skilled staff. As technology continues to develop, organisations must do more than simply adopt new tools; they must also create working environments and development opportunities that enable staff to use them well.
A recent McKinsey & Company blog (https://www.mckinsey.com/featured-insights/mckinsey-guide-to-navigating-the-new-world-of-work/how-people-and-technology-can-achieve-more-together) reflects on this same theme, emphasising the importance of strong collaboration between people and technology. One of the most thought-provoking pieces linked from it, The future of work is agentic (https://www.mckinsey.com/capabilities/people-and-organizational-performance/our-insights/the-future-of-work-is-agentic), considers the growing role of agentic AI in organisations. The term “agentic” is associated with autonomy and self-direction, and in this context refers to AI systems that can take more independent action. Yet, as the discussion makes clear, such systems do not remove the need for human insight. Understanding organisational context, interpreting nuance and drawing on experience remain fundamentally human strengths.
This is particularly important when considering the depth of tacit knowledge held by experienced employees. While AI may support or extend aspects of work, it cannot easily replace the practical understanding built up over many years. The success of any new technology, therefore, depends not only on what it can do, but on whether organisations are able to support meaningful adoption. In that respect, the ability to understand, apply and work confidently with AI is becoming one of the most important capabilities in the modern workforce.
In this issue, several papers explore different aspects of artificial intelligence and its implications for the information sector, alongside wider concerns such as work–life balance and the changing value of information and knowledge over time.
Managing the work-life balance of nocturnal librarian in an Urban City, Oluwole Durodolu
This study examines the impact of night-shift work on librarians in three universities in Nigeria, with a particular focus on work-life balance. Drawing on qualitative evidence from interviews and focus groups, it highlights the considerable personal and professional strain associated with nocturnal working patterns. The paper presents a compelling account of how night work can undermine both staff wellbeing and the sustainability of effective professional practice.
Perceptions and use of big data analytics for information management among librarians in selected university libraries in Kwara state, Nigeria, Ismail Adeyemi
This paper explores how librarians in selected university libraries in Nigeria, are engaging with big data analytics for information management. It highlights the practical barriers that continue to limit wider uptake, including data quality concerns, the complexity of managing varied data types, and infrastructural constraints such as unreliable power supply. Overall, the paper offers a useful account of both the promise of big data analytics in university libraries and the challenges that must be addressed if its benefits are to be more fully realised.
Managing expiring knowledge: Temporal dynamics of business information, Mohammad Ishtiaque Rahman
This paper examines the idea that business knowledge does not remain useful indefinitely, but can lose its value as circumstances change. In the context of artificial intelligence and fast-moving organisational environments, it argues that information must increasingly be understood in relation to time. The author identifies different ways in which knowledge can expire, ranging from sudden changes triggered by events to more gradual decline or shifts caused by context and wider structural change and presents a framework for understanding how quickly different kinds of knowledge lose relevance and how often new knowledge emerges in their place. Drawing on examples from finance, technology, public policy and healthcare, it shows that the pace and pattern of knowledge expiry vary across sectors.
Contaminated corpora: How the retraction crisis is being silently encoded into AI scientific knowledge, Adebowale Adetayo
This paper addresses an important and emerging risk in the relationship between artificial intelligence and scholarly communication: the possibility that retracted research is being absorbed into the datasets used to train large language models. It argues that, through licensing agreements that give AI developers access to whole journal archives, flawed or withdrawn papers may enter training corpora without the safeguards that normally alert human readers to their retracted status. The article offers a timely warning about the integrity of AI-generated scientific knowledge and highlights the important role that library and information professionals can play in strengthening governance in this area.
The functions of management for building a learning organization in the AI age, Mostafa sayyadi
This paper considers how managers can use artificial intelligence alongside the traditional functions of management to create organisations that are better equipped to learn, adapt and respond to change. The article presents a practical framework for building a learning organisation in which technology supports, rather than replaces, human development.