AIDigital Agency

Why we (Us) needed to redefine our agency model… And why I advice every agency to do the same…

The Impact Of AI Within The Agency

The traditional agency model faces significant challenges in the wake of AI democratization, forcing us to embark on another journey of reinvention. We are facing the same tumultuous period retailers experienced during the COVID-19 pandemic, where adaptation was key.

Just as retailers transformed obstacles into opportunities, embracing innovative strategies for resurgence, we too must explore and adapt. Inspired by these examples, we also need to be creative and resilient, finding new ways to move forward as AI changes our industry.

The Process of Content Creation Has Shifted

AI has forced us to re-evaluate the process of creating content. Theoretically, if content creation would take one hour of work (without insulting any content creator).

HERE’S WHAT THE OLD PROCESS WOULD LOOK LIKE:

IF WE WOULD LOOK INTO THE NEW AI PROCESS, IT WOULD LOOK MORE LIKE THIS:

Using a very simplified example like this, it doesn’t take a genius to see the true issue here. As an agency we are forced to find double the amount of projects to pay the same amount of salaries and make our agency profitable. So, can we consider our agency to be growing if, despite not hiring any new personnel, we’re managing to work on twice as many projects?

Or maybe a “time and material” pricing model is a thing of the past? After all, if you only charge for the hours spent on a project, where does the expertise in AI come into play? What I didn’t mention before in my example is the significant amount of research, knowledge, and training that is required to effectively use AI for the benefit of the company. Another option could be to purchase licenses for a new AI marketing technology tool. Yet…

We Are Over-Licensing AI Resulting In a License Hangover

One of the biggest threats appearing at the moment is the over-licensing of emerging new AI MarTech tools, solving small parts of the puzzle without getting a clear overview on the full size of the puzzle. If brands, agencies, … continue to purchase licenses like they are doing now, they’ll end up with a huge financial license hangover.

We’ve identified that 50% of current MarTech AI licenses could be solved with a simple API call. The only thing you need is a developer, time and the correct mindset. In my experience, only those last two pose a challenge.

AI Engineering For Marketing Is Overrated

You don’t need an AI engineer if you want to grow your agency. It’s like hiring a pilot to drive a taxi. I’m sure a pilot can drive a taxi, yet your customers will be paying for an overpriced taxi ride.

Like stated above, it requires a good developer with the right skills, a solid mindset and AI as a sidekick. Why AI? Because AI plays a crucial role in assisting with the coding needed for integrations. Isn’t that the beauty of it all?

This perfect combination of a talented developer and AI has enabled us to develop our own internal software solutions, free from licensing constraints. Here are a few examples of what we’ve independently created:

An internal linkbuilding AI tool
An AI image alt tag generator with visual AI integration
An automated multilingual SEO product description generator with keyword enrichment, google search
volumes and product feed importer
Extended menu items with fixed prompt buttons within Google Docs, Google Sheets and Google Slides
And many more…

Shift Now From A Time-Based Model To An Expertise-Based Model

Shifting to an expertise-based model marks a transformative approach for agencies, focusing on leveraging specialized knowledge and skills to offer exceptional value to clients. This model positions the agency as a trusted expert in specific areas, moving beyond generic service offerings to deliver deep, strategic insights and solutions, tailored to each client’s unique challenges.

Adopting an expertise-based model can significantly enhance an agency’s value proposition, enabling it to build stronger client relationships, differentiate itself in a competitive market, and achieve focused growth.
By committing to excellence in specific areas of expertise, agencies can elevate their status from service providers to indispensable strategic partners.

That is why one of our first core pieces of advice to all our clients is the importance of recognizing that OpenAI is open-source. This means that all your brand intelligence could potentially be accessed by your competitors. Without a structured marketing process implemented within your marketing team, you may inadvertently be enhancing your competitors’ strategies.

Hold on… why am I assisting my competitors who could also possibly read this? First and foremost, if anyone disagrees with my advice, they are under no obligation to follow it. I’m merely sharing my perspective on this matter. Perhaps I’m just an idealist who believes in collaborative intelligence with only one purpose; boosting AI adoption that will result in a smarter Belgian ecosystem of top notch agencies. It’s time to stop running behind the Netherlands, before they really start to believe that this is the case.

Agencies Should Offer More Expertise As A Service and Less Team As A Service

An “Expertise as a Service” (EaaS) model revolves around providing specialized knowledge and skills to clients on demand. Unlike traditional service models that might offer a broad range of services or products, EaaS focuses on delivering highly specialized expertise. This model is particularly beneficial in fields where specialized knowledge is critical but not constantly needed, allowing businesses to access expert insights and solutions without the overhead of full-time specialists.

The Expertise as a Service model offers businesses a flexible, cost-effective way to access specialized knowledge and skills. It supports innovation, enhances the quality of results, and allows companies to stay focused on their core operations, while leveraging expert insights for specific challenges and projects.