Embracing Generative AI: A Blueprint for Navigating the New Creative Frontier

After months of experimenting with generative AI and its impact on creative work, we thought we’d capture our findings and experiences in hopes they might help other creative leaders navigate this new AI-centric landscape

And Why the Courageous Leaders Who Embrace Change Will Shape the Future

You might have caught wind that there’s a lot of hype—and anxiety—around generative AI lately. No longer is this transformative technology merely threatening the manual labor force; it’s eyeing the corner offices, creative studios, and corporate meeting rooms with increasing interest.

We thought hard about writing on a subject that’s already so widely discussed, but ultimately, felt it unavoidable. Firstly, because generative AI tools are quickly weaving into our processes here at Massive. But also because we’re fielding a lot of questions (and concerns) from clients and partners about how—and if—to incorporate these technologies into their teams and workflows.

So here we go. After months of experimentation, observing their capabilities and impact on creative work in general, we thought we’d capture our findings and experiences in hopes they might help other creative leaders navigate these strange new waters we all find ourselves in. Debunking misconceptions about generative AI is the first step.

An AI-Powered Reality: Four Unavoidable Truths

Whether you’re a CEO, Jr Designer, Marketing Director, or run a creative agency, it’s important to know that;

  • The transformative power of creative AI is not a passing trend. These tools are already drastically changing the way creative teams work, and they’re iteratively improving faster than you can possibly imagine. Below is a Tweet by @juliancole showing the progress Midjourney has made over the course of one year. The majority of quality concerns most people voice will be resolved in a matter of weeks or months, not years.
  • There will be clear winners and losers. As the saying goes, “Pioneers take the arrows, settlers take the land.” Throughout our lives, we’ve seen this pattern unfold more than a few times. Napster paved the way for Limewire, which ultimately led to the rise of Spotify. Microsoft came before Apple, and Ask Jeeves before Google. What’s true is that Innovation is fraught with risks. What’s changed is that today, the dangers of eschewing innovation far outweigh the risks of adoption.
  • Leaders will fall into two categories. When confronted with AI, leadership teams will diverge into those that aim to be best and those that strive to differentiate. And, as has always been the case, those that strive to be best will find themselves at a serious disadvantage in a perpetual race towards commoditization (see Michael Porter’s Five Forces). This is where you’ll see the majority of lay-offs happen.

    The winning strategy; differentiation, while fundamentally more challenging, will be far more advantageous. It requires vision, curiosity, and a desire to focus human equity on areas that can generate more value, separating them from the competition instead of competing within what already exists. I think you already know which kind of leader you want to be.
  • AI is not a passive player. Its impact will be profound and will necessitate a thorough reassessment of your business operations and value proposition. Delay is not an option; adaptation is mandatory.

Getting Your Hands Dirty: Embarking on the AI Journey

We won’t break down detailed steps of using any one specific tool like ChatGPT, Midjourney or DALL·E (though we might in a future post). Instead, we thought we’d discuss what we’ve seen work here at Massive and amongst our clients’ and partners’ teams.

  • Leadership in the AI age cannot be an armchair exercise. The magnitude of this digital revolution requires hands-on learning, a thorough understanding, and an active vision from the top brass, whether you’re a director, a C-suite executive, or a founder.
  • Next, step into the arena of experimentation. Replace AI anxiety with curiosity. This technological behemoth isn’t here to replace human creativity but to amplify it. In a team setting, this means fostering a spirit of exploration, reminding your team that AI is an ally, not an enemy.
  • Sidenote: At Massive, we quickly discovered the team were already experimenting with these tools on their own. I’d imagine this is likely the case for many teams—in which case, a leader’s job is to facilitate and channel that in a way that’s generative for all.
  • A culture of sharing. When integrating AI into an organization, fostering a culture of sharing learnings becomes paramount. Sharing learnings enables teams to overcome challenges more effectively, discover innovative solutions, and avoid redundant efforts. It empowers individuals to learn from each other’s successes and failures, ultimately accelerating the organization’s ability to effectively adopt AI and enhancing the collective team’s expertise. Moreover, a culture of sharing nurtures a collaborative and supportive atmosphere, where individuals feel comfortable seeking assistance and collectively driving the organization towards AI-driven success.

    At Massive, 30 minutes of each discipline’s weekly team meetings is set aside for show-and-tell; where people can share different tools, techniques, and resources they’ve discovered that make their work better. We also have dedicated Slack channels for different tools where our learnings are shared freely and openly.
  • Set some ground rules. Not every question about the ethical use of generative AI will have an immediate answer. But having guiding principles in place will give your team a moral compass to navigate the brave new world of AI, which leads us to our next question of navigating the risks.

Navigating the Risks + Ethical Considerations of Generative AI

We’d be remiss if we didn’t discuss the risks and ethics of AI. As businesses, creative teams, and society embrace this technology, it’s crucial to approach it with a clear understanding of its limitations and the potential challenges it presents.

  • Misinformation, Fake Content, + Authenticity: From faux Drake hits to Pope Frances in Puffer Jackets, it goes without saying that AI is doing a bang-up job of creating highly realistic and convincing content. We’ll spare you the existential commentary on what this means for society or humanity as a whole and focus on the aspects relevant to creative teams in a corporate setting:

    Inevitably, you’ll need to make a decision on what level of AI-generated text, images, or creative you’re comfortable using for public-facing marketing initiatives. Are you comfortable leveraging ChatGPT-generated copy or images for your website? Let’s say you’re a consultant that can’t afford a custom photoshoot. Is it ethical to use MidJourney to generate a photo-realistic image of you and a “client” in a real-world scenario and to use this image for marketing purposes? What about using ChatGPT to write a blog post in the style of a particular well-known author? Ultimately, the answers to these questions depend on a variety of factors, and likely need to be considered on a case-by-case basis. 
  • Job Displacement and Workforce Transformation: Real talk—absolutely, AI will replace a staggering amount of jobs currently held by humans. Them’s the breaks. For creative teams, this likely means ICs (individual contributors) with jobs involving repetitive tasks that follow predefined patterns, such as data entry, copywriting, customer support, etc.

    It’s our belief that this is where the true character and values of the company and its leadership come to light. It’s also where we hope to impart a sense of urgency.

The quicker you can identify the elements of your value chain that are likely to be disrupted, the more time you have to train / upskill team members, or make the bigger strategic shifts needed to remain competitive in a responsible, ethical way. The longer businesses wait to adopt this technology the more drastic the course correction will be when they inevitably make the switch. 

  • Unconscious Bias + Ethical Use: Generative AI models are trained on large datasets, which can inadvertently perpetuate biases present in the data. It’s essential to be mindful of the potential for AI-generated content to amplify existing biases or create new ones. It’s important our creative teams are aware of the ingrained biases within these tools. They will get better, but in the meantime we need to be diligent and ensure we’re not perpetuating harmful cliches or stereotypes. 
  • Regulatory + Legal Considerations: The rapid advancement of generative AI raises questions around intellectual property rights, copyright infringement, and legal responsibility. Organizations must navigate the legal landscape surrounding the use and distribution of AI-generated content. As the technology evolves, policymakers and regulators will need to establish frameworks and guidelines to adequately address these legal considerations.
  • Quality Control + Accuracy: In what’s likely the most predictable story of 2023, Ars Technica recently broke a story about a lawyer that cited six fake cases made up by ChatGPT to help write court filings. You can safely expect your news feed to be filled with thousands of similar stories across hundreds of industries.

    The warning here is to not be a statistic. It’s easy to think of generative AI tools as time-savers—because they so often are. But that doesn’t exclude the need for diligent fact-checking and quality assurance. This is to say, you’ll likely have to adjust your internal review, QA, and approval processes to account for some of the more nuanced aspects of AI-generated creative.

In summary, Generative AI is here to stay, whether we like it or not. And it’s only a matter of time before the downstream effects of its disruption are acutely felt by all. 

This new era’s winners will be the courageous leaders who embrace generative AI, encouraging adoption and experimentation within their creative teams. Conversely, leaders that are slow on the uptake will find themselves having to take drastic measures in attempts to catch up, struggling to make ground against teams that have since adopted AI and adapted their value mix appropriately.

The onus lies with businesses to leverage it responsibly (and effectively from a competitive standpoint), by empowering their creative teams with the knowledge, skills, and nuances required to do so. Because the truth is, AI presents some pretty exciting possibilities for creatives. And, with open minds and a collective willingness to embrace this new frontier, we can make the transition more seamless than it appears.

Looking for a Place to Get Started? Below We’ve Listed Some Great Resources to Get You on Your Way

  • Harvard Business Review: HBR’s podcast “HBR’s IdeaCast” recent published an entire series entitled “How Generative AI Changes Everything”. It’s a must-listen for leaders trying to wrap their minds around the impacts of AI on business strategy and creativity.
  • OpenAI’s Website and Blog: OpenAI, a leading organization in the field of AI, offers valuable resources on generative AI, including research papers, case studies, and blog posts. Their website provides insights into the latest developments and applications of generative AI technologies.
  • MIT Technology Review: MIT Technology Review features in-depth articles and analysis on emerging technologies, including generative AI. Their content offers a balance of technical information and practical insights, making it accessible for business leaders looking to understand the potential of generative AI.
  • PomptHero. The #1 website for prompt engineering. Search millions of AI art images by models like Stabe Diffusion, Midjourney, DALL-E and more. They also have an Academy where they offer paid courses on AI-art generation. 
  • How to Create AI ART – Midjourney EXPLAINED: A Youtube playlist with a breakdown of Midjourney and AI-generated art. See the first video here.
  • Coursera: Coursera hosts a variety of online courses from top universities and institutions, including courses specifically focused on AI and machine learning. These courses cover both theoretical concepts and practical applications, offering business leaders an opportunity to delve deeper into generative AI.