Artificial Intelligence (AI) has been making waves across all sectors, including marketing. More importantly, this technology is evolving at breakneck speeds, with each version being more powerful than the previous ones.
The latest AI is called Generative AI (Gen AI) and differs greatly from our current AI technologies.
But what makes Gen AI different from traditional AI? And how does it affect digital marketing strategies?
This article will break down both concepts and their role in marketing.
Traditional AI: The Workhorse of Data and Automation
Traditional AI refers to systems that rely on pre-existing data and algorithms to automate tasks, make predictions, and solve problems. These systems follow patterns, but they don't create anything new. Think of traditional AI as the engine behind automation tools, recommendation algorithms, and customer service chatbots.
Key Uses of Traditional AI in Digital Marketing
Marketers use traditional AI in the following ways.
Predictive Analytics
Traditional AI is effective at predicting customer behavior by analyzing past data. For example, tools like Google Analytics use AI to forecast sales trends based on historical data. Marketing teams use this information to optimize campaigns and target the right audience.
Recommendation Systems
Ever wondered how Netflix knows what you’ll watch next? That’s traditional AI at work. These algorithms analyze user behavior to offer personalized product or content recommendations, improving user engagement and sales.
Chatbots and Virtual Assistants
Many businesses use AI-driven chatbots to offer real-time customer support. These bots follow pre-defined rules to answer common queries. While efficient, their responses are limited to their programming.
Programmatic Advertising
Traditional AI is also behind programmatic ad platforms, which automatically buy and place ads in front of relevant users. This method saves marketers time and increases ad efficiency through targeted ads.
Despite these benefits, traditional AI has many limitations.
Limitations of Traditional AI
While traditional AI is excellent at handling repetitive tasks, it lacks creativity. It relies heavily on human-provided data and predefined rules, which can limit its adaptability in dynamic marketing environments. As a result, traditional AI struggles with tasks like creating unique content or engaging users in meaningful, personalized ways.
Generative AI: The New Frontier
Generative AI represents a big leap forward. Unlike traditional AI, which focuses on analyzing and responding to data, Gen AI creates new content, ideas, and solutions. It doesn’t just follow patterns but can generate text, images, audio, and even video that is unique.
At its core, Gen AI uses deep learning techniques such as large language models (LLMs) like OpenAI’s GPT, which are trained on massive datasets. These systems can understand context, generate creative responses, and even simulate human-like interactions.
How Gen AI is Changing Digital Marketing
Gen AI is impacting digital marketing in the following ways.
Content Creation
Creating relevant content is one of the most prominent applications of Gen AI. Marketers can use Gen AI to generate blogs, social media posts, ad copy, and even email campaigns. Instead of spending hours drafting content, AI tools like Jasper or ChatGPT can produce human-like text in seconds.
Personalization at Scale
Gen AI takes personalization to the next level. With the ability to analyze vast amounts of data, it can create highly personalized marketing messages tailored to individual preferences. For example, it can generate personalized email content based on a user’s previous interactions with a brand.
Dynamic Ad Creation
Another key task is the generation of unique and customized advertisements. These ads can change based on user behavior, location, and even real-time events, allowing for hyper-targeted marketing strategies.
Visual Content Generation
Another exciting development is the use of Gen AI in creating visuals. Tools like DALL·E and MidJourney can generate images based on text descriptions. This allows marketers to create custom graphics, infographics, and other visuals without relying on designers.
Customer Interactions
Gen AI can power more advanced chatbots that not only answer questions but also engage in fluid, human-like conversations. These bots can help marketers provide a more immersive customer experience, enhancing engagement and satisfaction.
Again like traditional AI, Gen AI also has limitations, and it’s important to know them.
The Limitations of Gen AI
Despite its advanced capabilities, Gen AI is not without its challenges. For one, it can sometimes produce inaccurate or misleading information because it doesn’t “know” facts. Rather, it predicts them based on patterns in its training data. Therefore, marketers must review AI-generated content to ensure it aligns with brand voice and accuracy.
There’s also the issue of ethics. As AI-generated content becomes more prevalent, transparency becomes important. Customers need to know when they are interacting with a machine versus a human, to maintain trust and authenticity.
Now that we know what each technology can do, let’s examine their differences in marketing.
Key Differences Between Traditional AI and Gen AI in Marketing
Traditional and Gen AI can co-exist to provide a wide range of benefits. But before you start implementing them, know their key difference in marketing.
Creativity
Traditional AI is good at analyzing data and optimizing processes but lacks the creative abilities that Gen AI offers. Gen AI can create content from scratch, providing a more dynamic and creative approach to marketing. This means you can use traditional AI to gain insights and use Gen AI to create content based on these insights.
Data Dependency
Traditional AI relies on structured data and predefined rules, while Gen AI works with unstructured data and uses deep learning to generate new outputs. This difference makes Gen AI more flexible and adaptable.
Task Automation vs. Task Innovation
Another big difference is in the way each AI approaches tasks. While traditional AI is excellent for automating repetitive tasks, like sorting customer data or running targeted ads, Gen AI innovates by generating new content.
Personalization
While both forms of AI offer personalization, Gen AI can do it at a much more granular level. Traditional AI uses broad data sets to offer suggestions, whereas Gen AI can tailor content down to an individual’s preferences, making it more impactful.
What Does the Future Hold?
As Gen AI continues to evolve, its potential in digital marketing is limitless. However, traditional AI will still play a role in automating tasks, analyzing data, and optimizing campaigns. The combination of both technologies could offer marketers the best of both worlds: efficiency from traditional AI and creativity from Gen AI.
Marketers who harness the power of both AI types can expect to see more engaging campaigns, better customer experiences, and ultimately, higher returns on investment. But the key to success will be knowing when to use each type of AI and how to integrate them into a cohesive marketing strategy.
Bottom Line
The debate between Gen AI and traditional AI in digital marketing is not about which is better but how they complement each other. Traditional AI excels in data-driven tasks, making it invaluable for predictive analytics, automation, and customer service. On the other hand, Gen AI opens new possibilities for content creation, personalization, and dynamic customer engagement. In this sense, Gen AI might be the future, but traditional AI is the foundation that will keep it grounded.