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It is important to implement artificial intelligence (AI) because it can simplify and solve complex problems faster than humans. Because AI learns about people and their behavior from the first purchase, AI marketing can boost marketing efforts by leveraging data to target extremely precise consumer groups. There is a debate about the efficacy of AI marketing due to the constraints and limits imposed by the system's nature. This chapter presents insights from published studies regarding the relationship of AI with marketing and how AI can affect marketing. A real-world example of Netflix's usage of AI in marketing has been demonstrated. Then, consumer attitudes regarding AI were revealed. Then, several ethical considerations concerning AI were highlighted. Finally, the anticipated future of AI marketing was addressed. This chapter demonstrated the significance of firms implementing AI marketing to get a competitive advantage. Although some of the difficulties mentioned in this study need to be resolved, AI marketing has a bright future. There are ethical concerns about bias and privacy that should be addressed further. This chapter will encourage firms to use AI systems in marketing, and it will open the door to concerns that will need to be investigated academically in the future.

Introduction: The pandemic era has given rise to emerging VUCA factors, characterised by volatility, uncertainty, complexity, and ambiguity. Navigating the impact of these challenges is essential for adapting and thriving in a post-pandemic world; therefore, it is important to identify VUCA factors.

Purpose: The purpose of this study is to identify and analyse the VUCA factors that emerged during the COVID-19 pandemic, focusing on sectors such as hospitality, tourism, education, construction, manufacturing, Information Technology, healthcare, and automobiles.

Need for the Study: Analysing emerging VUCA factors is crucial for businesses to prepare for unforeseen events. While VUCA factors were previously studied during significant events like the Greater Recession, BREXIT, and demonetisation, the pandemic has presented unprecedented challenges, making the identification of emerging VUCA components crucial.

Methodology: The methodology involves reviewing articles and research papers to understand the pandemic’s impact on various sectors. The findings provide insights into prominent VUCA factors and their implications for businesses, contributing to existing knowledge.

Findings: This research uncovers the challenges organisations encountered in the pandemic’s VUCA environment, offering insights into uncertainties and strategies for survival. It highlights the importance of adaptability, resilience, and innovation in overcoming VUCA’s negative impacts and establishing a new business paradigm.

Practical Implications: This chapter is essential in providing valuable insights for organisations, policymakers, and businesses on crisis preparedness, emphasising the significance of agility, robust contingency planning, and sector-specific considerations. Reviewing operations and implementing backup plans, businesses can develop effective strategies for long-term resilience and success in the face of unforeseen disruptions.

Knowledge management (KM) is an important topic in the age of big data, and this study adds to the existing body of literature by providing a novel KM perspective on the technological phenomenon of artificial intelligence (AI). This study aims to discover how AI might facilitate knowledge-based business-to-business (B2B) marketing. In this chapter, the authors take a close look at the building blocks of AI and the relationships between them. Future research directions and also the effects of the various market information building components on B2B marketing are discussed. The study’s approach is theoretical; it tries to provide a framework for characterising the phenomenon of AI and its constituent parts. Additionally, this chapter provides a methodical analysis of the three categories of market information crucial to B2B marketing: knowledge of customers, knowledge of users, and knowledge of external markets. This research looks at AI through the lens of the conventional data processing framework, analysing the six pillars upon which AI systems are founded. It also explained how the framework’s components work together to transform data into actionable information. In this chapter, the authors will look at how AI works and how it can benefit B2B knowledge-based marketing. It’s not aimed at AI experts but rather at general marketing managers. In this chapter, the possible effects of AI on B2B marketing are discussed using examples from the real world.

Running an organization in a rapidly changing world is no easy task. Members of supervisory or executive boards must take the interests of all stakeholders into account. From shareholders, employees and suppliers, to customers, and beyond. Yet reaching the boardroom is equivalent to running a Spartan marathon. At a time when complexity is increasing and technological developments are hard to keep up with, the stakes for organizations and candidates are high. In this chapter, we explore the context of executive search: major trends, the profile of the executive search sector and the types of firms that operate in it. We de-mystify the process: the selection, search, presentation and accompaniment of candidates, looking at the responsibilities of the key players and the accompanying performance pressure and stress. Finally, we propose a vision for the future of executive search and potentially re-think about a professional code of conduct.

An earlier form of this chapter by the author was published in Dutch in “Bestemming Boardroom: over zoeken en gevonden worden” (Boom, Amsterdam, 2018) and in English (online) by the Amrop Partnership (2021) as “Destination Boardroom 1: Three Trends Redefining the Executive Talent Domain.”

Purpose: The COVID-19 pandemic is the most severe threat we have faced since World War II. So far, there have been about 5 million recorded cases, with over 300,000 fatalities globally. The epidemic is also wreaking havoc on the corporate world. People are losing their jobs and money, and no one knows when normalcy will return. So, addressing the VUCA Leadership Strategies Model is important to get more insight into this topic.

Need for the Study: According to the International Labor Organization, the pandemic might cost 195 million jobs. Even when the immediate impacts wear off, the long-term economic impact will reverberate for years. All four volatile, unpredictable, complex, and ambiguous (VUCA) characteristics apply to the issues we confront due to the coronavirus.

Methodology: Changes caused by COVID-19 occur daily, and are unpredictable, dramatic, and quick. No one can predict precisely when the epidemic will end or when a treatment or immunisation will be available. The pandemic impacts many parts of society, including health care, business, the economy, and social life. There is no ‘best practice’ that enterprises may utilise to tackle the pandemic’s issues. The VUCA leadership strategy models will be discussed and compared in this research study.

Findings: In this moment of transition, leaders must adhere to their fundamental values, core purpose, and ambition for big, hairy, and audacious goals.

Practical Implications: In this chapter, VUCA leadership strategy models will be discussed in detail for pre- and post-pandemic scenarios and their impact on different sectors, which will be very important for researchers in the same field.