Thanks to generative AI, advertising’s business models will be reinvented

Advertising and disruptive technologies. In many ways, you can’t have one without the other. In past years, disruptive technology meant programmatic media buying, SEO, and mobile. Today, it means artificial intelligence— more specifically, generative AI. Brands and consumers expect the industry to remain two steps ahead of the digital curve and while AI is not new to the industry, generative AI has caused many agencies to shift priorities and the way they operate. In 2024, it will be more about augmentation, not automation.

Agencies are faced with a Catch-22 scenario: They are concerned that AI will significantly change the agency landscape while also investing millions of dollars to stay relevant for clients who are looking for AI-enabled marketing. And this won’t change anytime soon. According to a report from WPP’s GroupM, AI-enabled marketing today accounts for nearly half (45%) of all advertising globally, and by 2032, AI will influence 90% of all ad revenue which is more than $1.3 trillion. As Marla Kaplowitz, president and CEO of the 4As, recently stated, “Gen AI is here to stay, leaving the advertising industry with a stark choice: adapt or become irrelevant.” No one can afford the latter.

Agencies must embrace the opportunity to transform their revenue model. Let’s explore one option: value based pricing.

What is Value-Based Pricing? 
In a nutshell, value-based pricing is when costs are determined by the value of services provided to the advertiser. The need for agencies to change their compensation structures has been bubbling for decades, but generative AI is likely to force this issue over the next few years. This shift will also require professionals to hone their creativity, strategic thinking, emotional intelligence, and cultural understanding—aka skills that machines cannot replicate. Lastly, it will require agencies to offer reskilling and upskilling initiatives while presenting exciting opportunities for professionals to reinvent themselves in a rapidly evolving landscape.

Here is how value-based pricing driven by AI can be advanced further.

Experiment, test, and understand which use cases demonstrate value 
In a soon-to-be-published paper by the 4As and the ANA on agency compensation, agencies and marketers are encouraged to embrace experimentation. Begin with smaller projects or engagements to test and learn from. Be prepared for setbacks, as they often yield valuable insights that can guide the journey toward more effective practices.

Ensure that the agency and advertiser are actively participating in the discovery process and collectively investing time and resources to experiment, test, and learn what use cases are the most relevant for the engagement and drive the most value for the brand. One thing to note: It’s important to experiment and test regularly to ensure that potential use cases aren’t missed. Begin by constructing a proof of concept that strikes the optimal balance between driving efficiencies and maximum impact. Once this is established, the value proposition for advertisers becomes more straightforward.

Once you have experimented, tested, and understand these usage scenarios, you should be able to calibrate the correct level of investment for the wider business and frame implications for pricing and business models. Align products and services to what clients value and need. Keep in mind that your competitors will be doing the same thing, so be sure to factor this in during this phase.

Ensure that value-based pricing is tied to realistic factors, achievements, and goals, not hype 
How are agencies expected to assign value to a technology that is predominately still in its hype phase? This is as much a question for brands as it is for agencies. Generative AI—although still in its infancy—is opening doors for both groups to integrate the technology into existing tools, products, and services. It’s not necessarily about reinventing the wheel but figuring out how to be more efficient and effective with the wheel.

ROI (return on investment) is important for growth but so is ensuring that you and your teams are set up for success in the long run. Generative AI is not going anywhere, and it is more important for leaders to test and experiment with the right pricing models than to introduce a product, service, or pricing model that isn’t viable for clients or your wider business.

While we don’t have a crystal ball, we know that new opportunities will emerge alongside technological advancements, creating jobs, tools, and products that didn’t exist before. A recent Goldman Sachs study suggests that in the next 10 years, most jobs will be complemented by AI, not substituted by it. If we let it, and get it right, we can use generative AI to tell more compelling stories, connect with audiences on a deeper level, and usher in a new era of advertising that is both effective and meaningful.

{Categories} _Category: Applications,_Category: Inspiration,*ALL*{/Categories}
{Author}Jeremy Lockhorn{/Author}

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