Over the past 150 years, manufacturing has shifted from relying on skilled craftsmen to automated, computer-driven, and flexible manufacturing systems. Marketing will do the same in less than 50 years, as AI radically changes the paradigm of markers. However, if marketers fail to adjust their overall marketing systems, the productivity gains gained from AI can easily be lost.
Let’s explore the legacy of marketing systems, how AI is disrupting those systems, and suggest new ways to approach marketing in the age of AI.
The Legacy of Marketing Systems
Modern marketing often functions as an apprenticeship system, where individuals learn their craft through a combination of on-the-job training and formal education under the tutelage of experienced professionals who provide guidance, supervision, and feedback. Marketing relies on highly skilled individuals in areas such as copywriting, design, and media management to create winning campaigns that drive business results.
As a result, most marketing systems are designed with multiple levels of approval, from mentors to apprentices (think senior copywriter to junior copywriter) to ensure quality and consistency. Workflows are set up to flow from one specialty to another, assuming that each specialty has unique skills that it applies to marketing work. These systems worked quite well in a slower-paced, largely manual world.
The introduction of marketing automation and digital marketing has begun to mechanize the delivery of some marketing assets, but, in general, the creation of marketing assets and systems reflect a traditional approach.
How AI is changing marketing systems
However, as marketing becomes increasingly automated through AI, legacy systems that involve multiple handoffs and manual approvals are holding back productivity gains. What good is it for a graphic designer to create images ten times faster if it still takes a week to go through the approval process? What do we gain if every test and budget adjustment has to go through management for approval?
Just as the introduction of the assembly line radically increased the speed and efficiency of automobile production, AI can potentially increase the speed and efficiency of marketing product production.
Repetitive tasks like content and ad creation will be automated and tested at a scale previously unimaginable. Data will be created, processed, and analyzed in near real-time. Machine learning will continuously optimize campaigns, leveraging ongoing feedback loops.
Instead of debating for hours over button colors and placements, marketers can now run real-time tests with multiple options. The need for multiple levels of approval is greatly reduced as programmatic templates and brand guidelines ensure standardization and quality. Workflows are automated.
Marketers must consider productivity gains and technology as well as the entire marketing system, including the impact on people, processes and roles.
Dig deeper: AI in Marketing: Examples to Help Your Team Today
Impact on the organization of the marketing team
With AI in its infancy in marketing, most marketers are focused on the power of generative AI. However, industry leaders are starting to move beyond generative AI and use AI to drive workflows and feedback loops. Some companies, like Tomorrow.io, have marketers with multiple specialties such as email, events, and social media. As this happens, we are seeing the rise of generative AI. marketing generalista person who has several specialties.
Initially, these marketing AI specialists will be tasked with bringing together individual AI solutions to create a workflow. As the marketing team begins to shrink, the skill set will broaden and marketers will need to improve their data and technology skills.
Marketing teams are now focused on managing automation workflows, streamlining processes, and running tests to achieve faster results and better outcomes. Coordination with data teams, quality teams, and marketing ethics/policy teams has become the norm.
We will start to see the breakdown of strategy and execution when AI notifies the marketing team of a new strategy to try. When marketers approve that strategy, AI will execute it.
For example, MasterCard Digital engine analyzes billions of online conversations to spot new micro-trends. This alerts the marketing team, who then uses existing content to create relevant social media posts and targeted ads.
In a few years, AI could inform the marketing team of the opportunity and, once approved, select which assets to pull from the content library or even develop hyper-personalized content on the fly.
How marketing professions are set to evolve
How does this impact the role of the marketer? Just as automation has changed the number and type of jobs in manufacturing, the number and type of jobs in marketing are set to change. In their book, “Marketing Artificial Intelligence, AI, Marketing and the Future of Business,” Paul Roetzer and Mike Kaput argue that future marketers must be data, technology, and communications savvy.
Future marketers will need technical expertise, problem-solving skills, and a sense of process optimization. Marketers must anticipate these changes and create environments that foster continuous improvement and cross-functional collaboration.
Much has been said about the disappearance of roles. However, AI in marketing is poised to create new opportunities. Automations must be conceptualized, built, managed, and maintained, all within a robust framework of guardrails and guidelines. AI technology in marketing must be chosen, implemented, and maintained.
Dig deeper: AI Transformation: How to Prepare Your Marketing Team
How to react now and in the future
Examples of the response already exist in companies like Netflix, Nike and Amazon. Nike is currently using AI technology to analyze emotional intelligence and traits of specific audience segments to create compelling stories that deliver the best ROI. How do they do it?
Small teams collaborate to achieve specific outcomes with predefined metrics. Teams look for ways to consolidate or automate processes. Leaders look for ways to decentralize decision-making within well-defined policy parameters. Teams are tasked with acting on the insights provided by AI.
If you’re just starting out, look for ways to combine AI tools to automate workflows. Start thinking about how you can automate approval processes. Consider the impact on other processes, including ways to consolidate processes through the power of technology.
If you’re part of an advanced organization, start looking for additional ways to use your data and automations to create feedback loops that continuously optimize predefined outcomes. The goal is to align with other teams on common outcomes and program systems to optimize those outcomes.
As in any fast-moving market, stay flexible, embrace variability and preserve your options.
Dig deeper: How brands like Klarna and Mars are using AI in their marketing operations
AI and the Marketing Ecosystem: Transforming People, Processes and Roles
It’s easy to get distracted by the new way of creating content with AI and forget that marketing works in a system. Current marketing systems rely mostly on manual processes where one person passes the work to another.
In the age of AI marketing, these manual processes have the potential to wipe out the productivity gains achieved through AI. Marketers need to think about how marketing workflows run through the system for automation, similar to how the manufacturing industry is now automating many processes that were once done manually.
Marketers need to think about the fundamental way work gets done—including people, processes, and roles—to take advantage of the real-time decision-making and rapid execution that AI enables.
Dig deeper: How to Implement AI for Your Marketing Team
Contributing authors are invited to create content for MarTech and are chosen for their expertise and contribution to the MarTech community. Our contributors work under the supervision of Writing and contributions are checked for quality and relevance to our readers. Opinions expressed are their own.
