Creative Production

Operational AI: The overlooked key to marketing efficiency

Does an effective marketing organization still work in the same way it did in 2015? Of course not, so much has changed, yet most brands still use the same traditional operating model to manage and produce content.

Efficiency is an urgent need. Marketing budgets are either yo-yoing, with the first part of 2025 seeing a drop and a subsequent recovery in Q2, or flat, according to Gartner. The constant pressure to fight inflation, deal with financial scrutiny and keep up with trends means more than half of the marketers surveyed recently reported feeling overwhelmed and undervalued.

With tight budgets, suboptimal marketer mental health and the consumer landscape more competitive than ever, it’s not enough to simply repeat the ‘do more with less’ mantra and expect stellar results.

“There is a huge opportunity for almost every brand to be more efficient today, without negatively impacting output and actually improving it, simply by working more efficiently,” insists Dan Birks, Chief Growth Officer at Inspired Thinking Group (ITG).

Moreover, the so-called ‘traditional operating model’ isn’t just slowing down progress, in many ways it is actively working against attempts to introduce efficiency. Traditional agency ways of working mean there is still a significant spend on manual work that could be automated. Halo content is one area ripe for automation, with automation and AI potentially freeing up anywhere from between 30% to 70% of costs. This isn’t hyperbole. “There is a huge amount of objective work; versioning, localization, adaptations and production, that is delivered by people that should be delivered by technology,” Birks suggests.

Brands that are spending millions on manually creating adaptations should be spending (much less) on technology and operational AI to automate manual ways of working. Crucially, this isn’t about handing Finance a saving but giving it back to marketing so it can be invested where it’s going to make a real difference.

A retailer’s transformation with Halo content and operational AI

ITG has put this into practice with many of its clients. For example, under the brands old agency model, a leading U.S. retailer used to rely heavily on manually produced weekly ads that were slow and costly to produce. By introducing a streamlined, data-driven promotion engine powered by operational AI, it shifted to a fully digital automated workflow, planning, creating, and distributing offers across multiple channels in a fraction of the time.

What was important was that structured data eliminated manual versioning. Automation and operational AI now keep pace high and errors low, driving a step-change in output, with promotional activity increasing by as much as 80% . Crucially, these gains weren’t just about speed. They meant more engaging messages reaching shoppers, showing that automation isn’t simply about slashing production time but freeing up space to maximize content opportunities. It’s what Birks calls “Halo content in action.”

The gift of time shouldn’t be underestimated. If inefficiencies are found in production, they are also to be found in the sheer weight of admin marketers find themselves floundering under. “Through technology and operational AI, you can take away a lot of admin, a lot of the project management work and help marketers get back to what they want to be doing; what they were employed to do; planning, strategizing, creating and testing,” Birks adds.

There is an understandable fear among marketing departments; the mantra, ‘if you don’t use it, lose it’ rings in many ears. It’s time for a mindset shift. Any efficiency drive must be connected to the business goal and, within that, the marketing strategy. Money saved is money to be invested.

The people problem

The elephant in the room is headcount-shaped. By introducing cost savings, are we automatically removing roles? Birks admits that some brands do take this route, but nothing like the scale suggested by more hysterical headlines.

“It is a difficult conversation,” Birks admits. “A team of 50 may become smaller. But that smaller team are now delivering real value and have a long-term future in that role and in the industry. If brands continue to work in old ways and not take advantage of automation and operational AI, ultimately the whole team is inefficient.”

“The cost saving message isn’t something we should be scared of,” Birks warns. “For the majority, it’s a positive thing. Where it goes wrong is when the message is that cost cutting is there to only save money and not to re-invest in growth.”

What is key is that every potential efficiency drive should be viewed from the perspective of ‘how can this be additive to the business?’. What more can we do with the people who no longer perform these basic tasks? What is the training or expansion opportunity?

Where there is real concern is that automation and operational AI typically take out tasks otherwise allocated to the more junior levels of the organization. While doing the basic versioning or admin, there is critical ‘on the job’ learning going on. How do marketers make sure the new talent pipeline is maintained?

“It’s a real and genuine risk if roles are no longer there because of automation and AI,” Birks claims. “Those doing it well in our industry are the ones who are already managing talent, onboarding, training and development in the light of these changes. Otherwise, we’ll find in five years’ time, there will be a real problem where there’s nobody coming up through the ranks with the necessary skillset.”

Move from savings to substance with operational AI

This is a lesson in unintended consequences and what happens if the efficiency play isn’t fully thought through strategically. Automation may cut immediate costs, but without consideration of how it fits into the mix it has the potential to store up financial and opportunity cost in the future. Birks adds: “This is not black and white. It’s about the right mix, the right blend of models. At times, that’s people, at times, it’s technology, usually both.”

One critical element that has been missing from the whole AI-efficiency conversation has been relevancy. There has been so much focus on what AI can take out of the mix and make faster and/or cheaper, there’s been little consideration for how the organization can adapt to be more efficient as a whole. A big piece of that puzzle is how it stays relevant, and this is where operational AI plays a pivotal role.

“Too many teams will look at an event like Valentine’s Day and produce broadly the same as last year, just with a different creative treatment. It’s the same volume, same channel, same work, same medium. Instead, they need to tackle the question: What should we produce and where should it be deployed?”

Rather than focusing only on how fast content can be produced, the real question is whether it will perform. Operational AI is what gives marketers that clarity, Birks explains.

There are any number of studies in the marketplace that show brands may have 100,000 assets in their DAM yet have never used 70% of them. “There are millions of pounds of marketing budget going into producing assets that are never used because we haven’t thought out what works and what should be produced,” Birks bemoans. “And that’s before getting into the sustainability issue around the environmental cost of creating and storing unused assets.”

There’s been huge focus on generative AI and its creative potential, but the bigger story is how operational AI is transforming the way marketing works. Generative AI is reshaping creation, while operational AI is unlocking efficiency and ROI, turning that potential into real, scalable change.

Operational AI gives marketers the insight to know exactly what to produce, when to deliver it in the customer journey, and how to build efficiency into their operating models.