Synergy or Conflict? Lessons for managers on how to successfully adopt AI to augment employee creativity

synergy or conflict

By Jakob Stollberger and David De Cremer

Artificial intelligence undeniably offers the potential to improve decision-making, at least in certain contexts. In this article, AI experts Jakob Stollberger and David De Cremer offer guidance for managers on how best to integrate the technology into work processes, even those associated with creativity, while continuing to meet the needs of the “human components” in the system.

 

The digital transformation offers near-boundless opportunities to improve work processes, including those on which organisations depend for their survival, such as creativity and innovation. A key challenge in this respect is how to successfully integrate AI in work processes that have previously been exclusively reserved for human team members, such as creative problem-solving. In this article, we make several recommendations on what managers can do to enable AI-augmented creativity in their organisations.

The positive side of AI for organisations, and the negative, too

The on-going digital transformation of workplaces and the increased integration of machine learning and artificial intelligence (AI) into work processes hold the potential to substantially augment work carried out by human employees and take it to the next level (Reeves, 2015). The last decade saw AI taking another developmental leap in that its capabilities are now not limited to relatively routine clerical or administrative tasks but extend to those that are more knowledge-intensive and necessitate considerable thinking capability (Huang, Rust, & Maksimovic, 2019), such as tasks requiring creativity.

However, despite the potential economic benefits, the automation of work processes by means of AI has sparked fear over a possible devaluation of human labour, rising unemployment due to the computerisation of jobs, and suggestions that AI represents a threat to democracy itself (Helbing et al., 2017). Looking into the future, although some are optimistic about the various ways in which AI might enhance human creativity and help ensure continued societal progress (Amabile, 2020), others (Barrat, 2013; Lindebaum, Vesa, & den Hond, 2020) are more sceptical, arguing that the fruit of human creativity may undermine our own ability to be creative in the future. Because AI is not human-like, the initial perceptions of AI are characterised by a lack of trust in its capabilities (Glikson & Woolley, 2020), as well as lack of authenticity (Jago, 2019) compared to humans, leading to a preference for human collaborators over AI (Dietvorst, Simmons, & Massey, 2015). Moving forward, managers face the challenge of successfully integrating AI in work processes (De Cremer, 2019), such as those requiring creativity. In the following, we will therefore outline some ideas of how AI can be integrated alongside humans in the creative process and formulate three takeaways for managers on how to facilitate effective AI integration in organisations.

Human-AI collaboration for improved creative problem-solving

Creativity can be described as the generation of ideas that are both novel and useful (Amabile, 1996), implying that ideas are considered creative if they (a) differ from the existing body of knowledge on a chosen topic and (b) add value in a human work environment, for example, in the context of improved products or services. The process underlying creative idea generation, however, is not uniform and varies depending on what kinds of activities one engages in (Nijstad, de Dreu, Rietzschel, & Baas, 2010). Specifically, creative ideas can be the result of either engaging in activities that require persistence, for example those involving methodical information search and the exploration of a limited number of prescribed categories, or activities that necessitate flexibility, such as those that involve breaking habitual thinking and meaningfully connecting knowledge across a variety of broad, previously unrelated categories. In a way, the persistence–flexibility duality can be likened to the relationship between exploration and exploitation that has previously been linked to enhanced innovative potential in organisations (Bledow, Frese, Anderson, Erez, & Farr, 2009). We take the two different pathways to creativity, that is, persistence and flexibility, as a starting point to outline a division of labour for humans and AI as part of the creative process, which will also guide our recommendations on how to effectively integrate AI in creative processes in organisations.

Despite the potential economic benefits, the automation of work processes by means of AI has sparked fear over a possible devaluation of human labour, rising unemployment due to the computerisation of jobs, and suggestions that AI represents a threat to democracy itself.

Specifically, the typical capabilities of AI appear to be better suited to contributing to the creative process when it comes to activities that require persistence. For example, if programmed appropriately, AI is able to search vast databases for relevant predefined categories and keywords, as well as formulate suggestions on how the information gathered can translate into novel additions to existing products and services. Thus, AI is a prime candidate to augment the creative process via the persistence pathway to creativity because, compared to humans, it excels at storing and processing information, as well as at engaging in systematic and incremental search processes within large data sets (Logg et al., 2019; Metcalf, Askay, & Rosenberg, 2019; Raisch & Krakowski, in press). Conversely, the typical capabilities of humans should enable them to contribute to the creative process on activities that require flexibility. This is in part because flexible out-of-the-box thinking is, to a large extent, driven by quintessentially human experiences, such as emotions (Nijstad et al., 2010), which AI cannot yet emulate (Huang et al., 2019), underlining the significance of human contributions to the creative process and offering a glimpse of how human-AI collaboration for creativity could play out in practice.

Managing the integration of AI in creative work processes

Having identified the unique contributions that AI and humans can make to augment the creative idea-generation process in future workplaces, the question becomes what managers can do to manage human-AI collaboration and effectively integrate AI into creative work processes in their organisations.

1. Spell out an overarching vision that is inclusive of both humans and AI

In many ways, the advent of AI in organisations presents a challenge for diversity and inclusion at work. Whereas previous organisational efforts in this respect may have focused on managing a diversity of individuals with different demographic (e.g., gender, age, ethnicity) or functional backgrounds (e.g., diversity of knowledge, skills and expertise; Guillaume et al., 2014), diversity management will likely be both more complex and more important for organisational effectiveness in the future. This is because the introduction of AI adds another layer of diversity, that of humans versus AI. Fortunately, the wealth of research on diversity and inclusion is not merely applicable to purely human diversity in organisations, but can also be used to manage the new human-AI diversity moving forward. One particularly promising way to manage such human-AI collaboration is to spell out an overarching vision to employees (Stam, Lord, van Knippenberg, & Wisse, 2014), specifically on how AI will contribute to work processes, such as those involving creativity, reassure humans that their role in this context is still essential and will not fall prey to AI-related automation, and that the input from both AI and human employees is necessary to achieve collective goals.

2. Allow for a degree of human control regarding idea selection in the creative process

Research has shown that many of the negative perceptions and biases humans have towards AI can be resolved by allowing humans to retain an element of control over the collaborative work process in question (Dietvorst, Simmons, & Massey, 2018). In the case of humans and AI contributing to creative processes, this element of control could reside in bestowing upon human employees an idea-selection capacity. Specifically, although AI may come up with ideas as a result of engaging in persistence-related activities, this does not guarantee that AI-generated ideas are automatically useful for organisations and markets comprised of humans; in fact, they may even prove harmful (Amabile, 2020). Here, human ombudsmen may be tasked with making sense of AI-generated ideas and selecting those that hold the greatest potential to add value to products and services in a human environment.

3. Focus leadership for creativity on exploitation and implementation of new ideas

The effectiveness of teams comprised of both AI and humans will, in large part, depend on managers finding a way to successfully integrate AI into relevant work processes, such as those requiring creativity.

Effective leadership for creativity ought to be ambidextrous, that is, involve behaviours that promote exploration and exploitation activities of their employees (Bledow et al., 2009). The integration of AI into creative work processes, however, is likely to change how leading for creativity will be performed in the future. First, AI does not have to be led in the same way as human employees, because, once AI is programmed, it delivers on those task instructions. In contrast, effective leadership of human employees involves influencing them to contribute to the attainment of organisational goals, motivating continued goal pursuit, and providing resources to enable eventual goal attainment. In the context of leading for creativity, because AI – due to its unique capabilities to generate ideas by analysing large databases – covers substantial ground regarding the exploration of potential creative ideas, human involvement will to a large extent be focused on efforts associated with the exploitation of ideas. As previously mentioned, these efforts may include sense-making and idea-validation activities with the aim of implementing the most promising ideas to develop new products and services. As a result, leadership for creativity will have to follow suit and predominantly shift to those creative activities that retain mostly human involvement, specifically focusing on behaviours geared towards exploitation, such as idea validation and implementation (Stollberger, West, & Sacramento, 2019; Zhou, Wang, Bavato, Tasselli, & Wu, 2019). This may, for example, involve an increased focus on setting meaningful deadlines for brainstorming and creative problem-solving activities to ensure greater efficiency of human-AI collaboration. Furthermore, even if ideas arising from collaborative efforts are novel and potentially useful, they may not be easily implemented in practice and thus prove unfeasible.

Conclusion

The digital transformation holds the promise to augment human capabilities at work and add value to the development of products and services in the future. However, the introduction of “digital co-workers” comes with challenges, as well, that include but are not limited to the restructuring of work processes and related transition to human-AI collaboration, as well as manoeuvring the potential pitfalls of effective AI integration. The effectiveness of teams comprised of both AI and humans will, in large part, depend on managers finding a way to successfully integrate AI into relevant work processes, such as those requiring creativity, and thereby unlocking the value proposition of AI for organisations. 

About the Authors

Dr. Jacob StollbergerJakob Stollberger is an assistant professor at Aston Business School, UK, as well as an international research affiliate of the Centre on AI Technology for Humankind at NUS Business School, Singapore. Jakob’s research examines topics such as leadership and innovation, the intersection between work and family, as well as how artificial intelligence plays a role in the future of work. He also works as a practitioner advising businesses in these areas. Prior to joining Aston Business School, Jakob held research positions at Judge Business School, University of Cambridge and the University of Birmingham.

David De CremerDavid De Cremer is Provost Chair and Professor in Management and Organisations at NUS Business School, National University of Singapore, a former KPMG endowed Professor in Management Studies and current honorary fellow at Cambridge Judge Business School, and a fellow at St Edmunds College, University of Cambridge. He is also the founder and Director of the Centre On AI Technology for Humankind. He has been called one of the world’s top 30 management gurus and speakers in 2020 and is a best-selling author, his latest book being on “Leadership by algorithm: Who leads and who follows in the AI era?” His personal website: www.daviddecremer.com

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