A big agency CEO recently tweeted that her solution to integrating generative AI into her organization was to require that everyone in the agency be required to use AI tools in their work. It made for a good press release. But…..
Good luck with that!
Artificial Intelligence (#AI)#ChatGPT and #GenerativeAI have become raging buzzwords in the advertising and marketing industry, promising instant enhanced creativity and efficiency or depending on your perspective doom and end times for human creatives. An unending firehose of generative AI news, must -read newsletters and breathless noise greets us every morning -- causing one to easily believe one is far behind. However, the contention that every employee in an ad agency should immediately start using generative AI tools such as ChatGPT is a proposition that sounds great but warrants more than careful consideration.
While generative AI holds immense potential, its current limitations in terms of accuracy, applicability and creativity call for a thoughtful and strategic approach to integration rather than splattering the wall with whatever every individual, informed or uninformed believes in. Blindly embracing generative AI without direction and support could ultimately lead to generic creative execution, confused clients, and costly setbacks for an ad agency. THe worst outcome for introducing AI into the blood veins would be advertising that seems all the same.
Limitations of Generative AI:
Generative AI, although wildly impressive on a one-off basis, is very much an evolving technology still in its infancy. It has many limitations, not all of which are receiving the same attention as the hype machine flooding your email box and Twitter account. For example, one of its primary limitations lies in accuracy. Generative AI models often produce outputs that are close to but not entirely accurate or in other instances completely detached from proof and reality. As a consequence, the need for human intervention, oversight, and fact-checking will not go away. In fact, with accelerated times to creation, this issue could become much more burdensome on an agency or marketing organization than the current state of affairs. In the creative industries, where accuracy and originality are paramount, reliance solely on generative AI may lead to compromised results, dilution of a brand's unique voice, and, worst case, PR nightmares.
Furthermore, applicability is another area where generative AI still falls short and will for some time. While Generative AI excels at generating content based on existing data, it will likely struggle with understanding complex nuances and context. Creative projects often require a deep understanding of human emotions, cultural references, jokes, memes, and irony; critical constructs which current generative AI models as currently offered struggle to grasp fully. Relying solely on generative AI for creative purposes risks producing content that feels bland, disconnected, generic, and sometimes even insensitive to the target audience.
And which of the burgeoning list of AI-related applications should an agency enroll into its processes and product output? Dozens of new tools and plug-ins are announced every single day. Hundreds of “prompt guides” offering to solve every problem you could imagine and then some are populating my stream almost hourly. Is anyone thinking about tool curation, standards for use, and quality control? Not so much in our discussions with creative agency executives.
AI Integration for Creative Companies:
Like any young child, generative AI is going to need a great deal of adult (human) supervision.
To harness the true potential of generative AI and avoid the many potential pitfalls, ad agencies should adopt a thoughtful and measured approach to its integration into the organization. This involves acknowledging the current limitations of the technology; among them the flood of uncurated options, and the risks of both bland creative output or outright inaccuracy. Here are a few key considerations for introducing generative AI tools to a creative company:
Define Objectives and Use Cases: Clearly identify the specific areas where generative AI can add value within the agency's workflow. Whether it's automating repetitive tasks, generating preliminary ideas, or enhancing data analysis, a well-defined integration plan ensures targeted utilization of generative AI.
Training and Education: Invest in training programs to ensure employees understand the capabilities and limitations of generative AI. Equip them with the necessary skills to leverage the technology effectively. By fostering a learning environment, employees can develop a discerning eye for when to rely on generative AI and when human intervention is required.
Human-Machine Collaboration: Promote a collaborative work culture that encourages synergy between generative AI tools and human creativity. Instead of replacing human talent, generative AI should be viewed as a valuable assistant that can augment and amplify creative ideas. By combining the strengths of both humans and AI, agencies can achieve better results.
Quality Assurance and Review: Establish robust quality assurance protocols to ensure that generative AI outputs meet the agency's standards. Encourage a review process that involves human experts who can fine-tune and refine the generative AI-generated content, ensuring accuracy, relevance, and alignment with the agency's creative vision.
Evaluate and Analyze Post-performance: Under any circumstances, systems must be established to evaluate performance (by platform if multiple tools are used) and internal costs per creative unit. Measures and standards will need to be developed at both the account, organizational and industry wide levels to inform future effort and provide codified learning.
Conclusion:
While #generativeAI holds great promise for ad agencies and marketing organizations, its current limitations must not be overlooked. The contention that immediate adoption by every employee is the best path to “AI-literacy” is simplistic and overlooks the need for a thoughtful and strategic integration plan. Agencies must recognize the accuracy and applicability limitations of generative AI and instead aim for a collaborative approach that combines the power of AI with human creativity and expertise. This, by the way, creates tremendous opportunities for new kinds of work and jobs.
By defining clear objectives, setting a flexible strategy, investing in training and education, fostering effective and efficient human-machine/bot/robot collaboration, and implementing robust quality assurance measures (both objective and subjective), ad agencies can leverage generative AI effectively. With careful direction and support, generative AI tools can become valuable assets that enhance creativity, increase output, improve efficiency and profit margins, and ultimately drive successful campaigns.
But, the Agency CEO who thinks a shotgun, one-size-fits-all approach is to merely punt the ball down the road. And we repeat:
Good luck with that! #AIinAdvertising
Article by Bruce Carlisle Contributors: Kevin Sullivan , George Chalekian , #chatgpt
NB: Proving our point. ChatGPT was deployed in the development of this piece. Without our (human) direction, the original bot draft wouldn’t exist (and even i it did exist, it would have no discernible point of view) and without our (human) post-draft intercession, this post would have been much more generic, far less interesting and plagued by more than a few inaccuracies. Don’t Panic. Your job is safe. For now. (First published by Bruce Carlisle on LinkedIn May 24,2023)