[Student IDEAS] by Nelberto Nicholas Quinto - PhD student in the Management department at ESSEC Business School


This article offers a long-term overview of the transformative role of AI in shaping the future of creativity. Aside from democratizing creative production, it illustrates how AI enhances creativity by reducing the cognitive barriers to ideation and information recombination that is at the heart of innovation. However, issues related to rising quality benchmarks, acceptance, trust, and over-dependence may stifle these benefits. The article ends by offering a simple solution to these quandaries while highlighting other more pressing concerns related to AI’s march into the creative sphere.


AI's march into the realm of creativity has been teeming with trepidation, stemming from fears that increasingly sophisticated machines might eclipse our ingenuity and devalue the human experience. Dissecting the intricacies of co-creating works that are deemed creative– i.e. deemed both novel and useful – with generative AI in the first installment of this two-piece article series however reveals an inherently human process. A dance that involves iterative bouts of innovative experimentation, unique amalgamations of tools and ideas, and a critically overlooked component – emotion. The realization of these intensely human aspects offer a distinctly more hopeful perspective, contingent upon us remaining actively involved in the process. 

Transitioning from the debate concerning the retention of humanistic elements in AI co-creation – elements that imbue depth, meaning, and value to the creative process, as discussed in this article’s predecessor, this installment aims to elaborate more on the benefits, limitations, and long-term challenges to creativity that arise from this generative process. The question of whether AI could potentially spell the demise of creativity in the long-term is ultimately addressed, followed by a conclusion that steers the discourse towards identifying more pressing concerns about AI that will require much of our ability to provide novel and useful solutions.

Recapping the Creative Benefits to Leveraging AI

Creativity is understood as the generation of ideas, processes, or products that are both novel and useful1,2. When understood as an ability to produce works that meet this two-fold criteria of novelty (uniqueness, originality) and usefulness (value, quality), both the outcomes and processes inherent in generating them become relevant. One of the most widely observed benefits of co-creating with generative AI is that it streamlines and democratizes the process of creative production. By curtailing the costs related to skill, talent, and equipment (or software), AI facilitates the genesis of valuable, new creations –- be they illustrations, poems, marketing slogans, or strategic proposals. This empowerment invites a wider demographic to unlock their inherent creative potential and engage in the human-AI symphony of creation. Take, for instance, the case of Aamar Reshi discussed in detail in the first part of this article series. His imaginative journey to crafting a children's storybook in 3 days without any prior experience in illustration or creative writing was made possible by AI's ability to translate his motivation into captivating illustrations and engaging storylines.

AI also significantly lightens the cognitive load associated with conceiving original solutions to intricate, pressing problems. For instance, imagine a marketing team trying to brainstorm a new advertising campaign. Instead of spending hours coming up with basic ideas, a large language model (LLM) such as Chat GPT could generate a list of them within minutes. The team could then immediately start discussing which of these listed ideas are worth developing further. They could also combine different AI-suggested concepts to create something unique and impactful. In this way, AI allows for more effective use of the team's expertise and creative thinking. And while much of the content produced by LLMs tends towards the mundane and predictable, this in fact offers a crucial advantage. The immediate availability of a broad spectrum of highly conventional ideas allows individuals and teams to swiftly dispatch with the obvious, learn from these iterations, and refocus their cognitive prowess. In the context of prototyping, generative AI tools have emerged as a catalyst for quickly transforming abstract concepts in our heads into tangible, useful drafts. They shoulder the cognitive and labor-intensive burden of the initial groundwork, generating the first iterations swiftly. As a result, just as in brainstorming, teams can re-allocate their mental energy and time towards more creative tasks, including those where human expertise still surpasses AI.

AI’s Impact on Quality Standards Perpetuates Creativity

As we hurtle into a future fraught with increasingly complex challenges requiring novel solutions, it's clear that both creativity and generative AI’s role in the creative process is here to stay. While individuals will continue to extract value from AI, the benchmark for what constitutes quality and usefulness will concurrently increase. When productive expectations rise, fostering creativity and innovation to meet these heightened standards will always be a need, and often, a priority. While the influx of novel combinations of information and ideas might make the task of generating something truly different and unique with AI progressively challenging as well, it will undeniably necessitate increasingly creative methods to continuously derive value from current tools and systems. Thus, regardless of how sophisticated AI systems become, creativity will always have a place within organizations and society. 

For instance, in producing digital art, some graphic designers are already leveraging AI image generators such as Midjourney and Stable Diffusion to simulate prototypes of their ideas, draw inspiration from different styles, or ultimately create distinct artworks that require minimal post-processing. At first, such use of AI was deemed innovative, and there have been many cases where fresh and valuable works have been produced through such a process. But as leveraging AI capabilities have become more widespread, the novelty of such techniques have declined, and the average uniqueness of generated works have suffered as well. Consequently, the standards for what is considered useful have risen as more people have realized the value of current AI tools. Artists must then deepen their creative explorations, finding fresh ways to collaborate with AI to generate art that remains innovative and valuable amidst the evolving landscape. This may involve countless experimentations with prompt patterns or combining different tools, systems, or methods to process works generated by AI.

Meanwhile, in organizational settings, particularly when teams make use of Large Language Models (LLM), such as OpenAI’s ChatGPT or Google’s Bard, to streamline brainstorming sessions, catalyze idea generation, and decode complex problems– the interplay between creativity and AI unfolds in the same manner as in the arts. Consider a tech start-up using GPT technology to augment their product design brainstorming. The AI solutions might generate new perspectives on user interface design, providing inspirations that the team hadn't previously considered. Companies that successfully integrate such technologies into their workflow stand to gain a competitive edge, as they can alleviate the cognitive burden inherent in creative tasks and propel their innovation teams into uncharted territories. However, as AI-assisted approaches become commonplace, the novelty of these processes diminishes. As more and more employees, teams, and organizations become accustomed to harvesting the creative benefits of AI across a spectrum of tasks, the standard for what can be achieved within a certain timeframe and resource set escalates exponentially.

In response, organizations would need to persistently cultivate creativity to extract further value from AI. They might deploy additional algorithmic tools to discern patterns from past AI-laden brainstorming sessions and predict potential hurdles. For example, a company could use AI to analyze both previous meeting notes and past AI suggestions given various employee-generated GPT prompt patterns. This would allow individuals and teams to leverage insights derived from such data analyses to consequently modify their use of generative technologies for idea development and prototype-building. Such a solution could also lead to routinized processes and systems that facilitate extracting more value from novel AI suggestions in order to suit their unique problem contexts. For example, a marketing team could develop protocols for how to synthesize campaign ideas developed through multiple rounds of brainstorming with generative AI, across several meeting groups. They could also devise a structured process that involves integrating these insights with those uncovered by social media trends, competitor campaigns, and customer behavior data that predictive AI models concurrently deliver. 

In such instances, creative production necessitates innovation in processes where different individuals and AI systems come together to meet the new, heightened standards for novelty and value that innovation and competition propel. However, when novel processes or new best practices are found to be creative at a given point in time, more and more companies are likely to find value in them. This implies that standards will rise again and organizations would need to search for more ingenious processes that leverage existing human and technological capital, fostering creativity and perpetuating its need.

Threats to Creativity: Under-Appreciation and Over-Reliance on AI

Instead of pondering the supposed demise of creativity, perhaps the real issue at hand is the skepticism and under-appreciation of the immense value generative AI brings to the table. It is unsettling to see how quickly some individuals abandon the use of these technologies, swayed by a few erroneous outputs, unsuccessful prompts, or the cynicism of others. On the flip side, there exists an equally troubling group – those over-reliant on AI to the extent that they forsake nurturing their own critical thinking, domain expertise, and breadth of knowledge. This excessive dependency threatens to hollow out human innovation and intuition, reducing our contributions to mere button-pressing reactions to whimsical needs. The remedy to both of these conundrums lies in fostering a comprehensive understanding of AI's capabilities and limitations among the broader population, as discussed in more detail in the first piece of this two-part series.

There is simply so much value-creation lost when people do not simply understand the usefulness of generative tools that can rapidly produce creative drafts and prototypes ; all while harnessing centuries of accumulated human knowledge to yield accurate, factual results in at least 9 out of 10 instances. As such, there is a pressing need to educate individuals about applying even basic generative AI capabilities to the multitude of use cases in their personal and professional lives. This requires promoting practices that encourage persistent experimentation with AI, while fully acknowledging its current bounds and how it can complement our unique strengths. 

The Solution: Continuous Exploration of AI-Human Boundary Capabilities

AI will continue to improve, and so too will our abilities, skills, and talents. In this constant cycle of progression, the necessity of understanding the evolving capacities of AI and human creativity cannot be overstated. Identifying the complementary intersections between AI and our innovative capacity enables us to effectively harness their combined potential. And this begins by ensuring that we remain determined to cultivate the requisite knowledge, expertise, and capabilities to credibly evaluate the usefulness, appropriateness, and credibility of AI generated outputs.

In this dynamic panorama of evolving AI systems and expanding human capabilities, the value of experimentation in demarcating the ever-changing boundaries of both AI and our personal abilities becomes paramount. In particular, this knowledge helps illuminate our understanding of what AI can and cannot do for us, and what we can achieve more efficiently with or without these technologies, for any given moment in time. It also enables us to identify which domain-specific skills and new capabilities we should invest our time in developing and refining. And as we navigate this blurred frontier, the role of continuous learning, engagement, and development of our unique creative abilities vis-a-vis AI becomes ever more critical.

While the “death of creativity” is far from imminent, the reshaping business and societal terrain calls for both prudence and immediate action. As AI emboldens individuals and organizations to leverage technology to augment their unique capabilities and cumulative expertise, navigating this evolving landscape thus calls us to reconsider our part in the redefined creative epoch. Are we disrupting, merely keeping up, or falling behind? Survival in competitive environments, after all, necessitates exploiting the opportunities emerging technologies offer, and we should therefore set aside time in our schedules to explore ways we can achieve this at a personal level. Again, this begins by carefully discerning what both we and AI uniquely excel in, and identifying potent synergies that allow us to balance each other's strengths and weaknesses for our specific trade and tasks. Whether you are a marketer,  musician, illustrator, business owner, or a corporate planner, understanding how emerging technologies affect the value and novelty you produce at any given point in time is paramount to continued success.  Stop. Think. Reflect. What critical inputs, processes, and skills does AI need from you to deliver in order for you to generate ideas, products, and systems that are new and valuable? What are you doing to know or develop this? Your answers to these questions may well define your survival amidst AI’s creative renaissance.

Beyond the Issue of Creativity: Where More Pressing Challenges Lie

While this thought exploration attempts to address whether AI would extinguish the flame of human creativity, it inevitably leaves a myriad of related issues unexplored. Indeed, while AI, with its prodigious generative capacities, promises to herald a creative renaissance—exploring uncharted territories of ideas and unveiling transformative solutions to pressing issues—we must also recognize the potential detrimental impact it could have on our artistic workforce. As discussed, the process of co-creating with generative AI still necessitates an intricate, often emotionally charged, and iterative human endeavor. It involves the careful orchestration of past human experiences to weave into the fabric of our creations. 

Yet a recurrent threat that we are treading is the dangerous line of devaluing the authentic human touch; that is– the artisanal signature underlying much of the creative work we know. Companies may start to undervalue the finesse of artistic capability, leading to reduced remuneration for graphic designers, composers, and other artists. This, even before a novice utilizing generative AI can genuinely outperform seasoned creators. Such devaluation can cause both current and aspiring artists to neglect nurturing their unique aesthetic skills and specialized capabilities, which could be detrimental to the future of creativity. After all, truly harnessing the power of AI for creative endeavors requires not just knowing its technological boundaries, but also having a robust foundation of one’s specialized domain and the aesthetic sensibility needed to both recognize and conjure quality art.

Furthermore, we need to tread carefully on the path of intellectual property (IP) rights. Artists may feel aggrieved as their creative genius– their unique output– is utilized to train AI systems without due recompense or consent. This could make it facile for others to mimic their distinctive style, enabling these individuals to build on years of the artists’ painstaking dedication without due permission or acknowledgement. If we fail to establish robust mechanisms for suitable compensation, recognition, and consent for creative IP, we risk discouraging artists from trusting and reaping the benefits of AI. Worse, we risk a decline in traditional artistic pursuits, which form the bedrock of cultural heritage and individual expression. On a less immediate yet significant impact, we risk losing valuable creative contributions that future generations could build upon. If we deter a whole generation from pursuing arts due to lack of passion or adequate incentive, we lose more than just individual livelihoods. The vibrancy of our cultural tapestry and our collective ability to innovate are at stake. It is therefore vital that we safeguard the livelihoods and IP of artists to prevent cultural impoverishment.

Moreover, while AI undoubtedly creates new job opportunities and uncovers novel synergies between human and machine to drive value and discover novel solutions to critical problems, the rapid pace at which AI is reshaping the job market is cause for concern. The velocity of job displacement could potentially outpace that of job creation and skill development across a wide-array of fields. Its reach already extends to every facet of work, life, and the economy, sometimes unpredictably. Such an imbalance could endanger a substantial segment of the workforce, along with their dependents.

While AI is not poised to extinguish the flame of creativity, it could expedite the ebb of certain industries and livelihoods faster than it rebuilds or expands them. This necessitates an inventive approach to temper potential fallout. Hence, the real merit of AI lies not only in catalyzing and amplifying human creativity to forge new solutions to high-value issues, but also in innovating answers to the challenges it itself surfaces– from that of artistic preservation, intellectual property rights, overly rapid job displacement, and beyond.


[1] Teresa M. Amabile et al., Affect and Creativity at Work, Administrative Science Quarterly 50, no. 3 (September 1, 2005): 367–403,

[2] Teresa M. Amabile, The Social Psychology of Creativity: A Componential Conceptualization., Journal of Personality and Social Psychology 45, no. 2 (August 1983): 357–76, 

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