AI isn't new: Why email marketing may be the best place to understand its evolution
It often surprises me how many people talk about Artificial Intelligence as if it has suddenly appeared overnight and ushered in an entirely new world. From my perspective, working in digital technology for decades, many of the concepts driving today's AI have been with us for a very long time.
The terminology may have changed, and the capabilities have certainly advanced, but the foundations are familiar.
Long before ChatGPT, Gemini, or Claude became household names, we were already using forms of machine learning in digital marketing. Search engines relied on robots and spiders to crawl websites, analyse content, and determine relevance. While primitive compared to today's large language models, these systems were still learning patterns, categorising information, and making decisions based on data.
In many ways, machine learning has been quietly working in the background of our digital lives for years.
From the Commodore era to modern AI
My own introduction to teaching computers began in the 1980s with a Commodore computer. Back then, there was no AI as we know it today. If you wanted a computer to do something, you programmed every instruction yourself.
I remember creating simple games, including a chess game. The machine wasn't thinking independently, but it was operating within the framework I had built. It could respond to my moves and provide an experience that felt intelligent, even though every possibility had been programmed.
Fast forward, and computers can now generate text, create images, analyse data, and hold conversations. The difference is not that computers have suddenly become intelligent. The difference is the scale of data, processing power, and the sophistication of the models we have built.
Have we been using AI all along?
Consider predictive text.
Most of us have been using predictive suggestions on our phones and computers for nearly two decades. Email platforms have suggested subject lines. Search engines have completed our searches before we've finished typing. Smartphones have corrected our spelling, sometimes correctly and sometimes hilariously incorrectly.
Voice assistants such as Siri and Alexa have also been with us for years. They listen, interpret intent, and provide responses.
Were these not early forms of AI?
Perhaps what has changed is not the existence of artificial intelligence, but our expectations of it. The boundary between programmed responses and generated responses has become increasingly blurred.
Is AI just a better chatbot?
Many businesses experimented with chatbots long before generative AI arrived.
Traditional chatbots worked by following predefined decision trees. Developers would create hundreds of possible questions and responses. If a customer asked something outside those programmed paths, the experience quickly became frustrating.
Today's AI-powered assistants are fundamentally different because they generate responses rather than selecting from a list. They can understand context, infer meaning, and create new combinations of language on demand.
Yet the question remains:
Are we witnessing genuine intelligence, or simply increasingly sophisticated prediction?
Large language models do not think in the human sense. They do not possess consciousness, emotions, or personal experiences. Instead, they predict what word is most likely to come next based on patterns learned from enormous amounts of data.
That is incredibly powerful, but it is worth remembering that prediction and intelligence are not necessarily the same thing.
So what is intelligence?
This is where the conversation becomes interesting.
When we talk about intelligence, are we talking about knowledge? Problem-solving? Creativity? Self-awareness? Independent thought?
Computers excel at processing information and recognising patterns. Humans excel at understanding context, emotion, ethics, and nuance.
The more AI advances, the more important it becomes to understand the distinction between automation and true intelligence.
Perhaps the real question is not whether AI is intelligent, but whether it can help humans become more effective.
Bringing the discussion back to email marketing
Email marketing provides one of the clearest examples of how AI has evolved from simple automation into something much more sophisticated.
For years, email platforms such as Mailchimp, Campaign Monitor, HubSpot, and others have offered machine learning features. Marketers have become familiar with:
Subject line suggestions
Send-time optimisation
Audience segmentation
Engagement predictions
Automated workflows
A/B testing recommendations
These features use historical data to improve performance and have delivered measurable value for years.
However, the next generation of AI is moving far beyond these capabilities.
The new era of AI-Powered email
Today's AI systems are beginning to transform every stage of the email marketing process.
Content creation
AI can now generate:
Subject lines
Preview text
Email copy
Calls to action
Personalised recommendations
What once took hours can now be drafted in minutes.
Hyper-Personalisation
Rather than creating a single email for an entire audience, AI can generate variations tailored to individual behaviours, interests, and purchase history.
The future may see every subscriber receiving a uniquely crafted version of the same campaign.
Predictive engagement
Modern AI models can predict:
Who is likely to open an email
Who may unsubscribe
Which customers are ready to buy
Which content themes resonate with specific audiences
This shifts email marketing from reactive communication to proactive engagement.
Intelligent Timing
Timing has always been one of the most important factors in email success.
Historically, marketers relied on broad assumptions:
"Tuesday mornings perform best."
But AI is moving beyond generic rules. It can determine when individual recipients are most likely to engage and deliver messages at precisely the right moment.
The future of email marketing may be less about finding the best time to send and more about finding the best time for each person to receive.
What comes next?
The most exciting development is not that AI can write emails.
The exciting development is that AI can potentially understand intent, behaviour, timing, and context at a scale no human team could manage manually.
Imagine a system that:
Knows when a customer is likely to purchase
Understands their interests
Generates relevant content
Selects the optimal subject line
Sends at the ideal moment
Learns from the outcome
That future is much closer than many people realise.
Final thoughts
AI did not suddenly appear in 2023.
The technologies underpinning today's AI have been developing for decades through machine learning, search engines, predictive text, recommendation systems, voice assistants, and marketing automation platforms.
What has changed is the sophistication of the models and the accessibility of the technology.
Perhaps instead of asking whether AI is new, we should ask a different question:
How do we use these increasingly powerful tools responsibly and effectively?
For email marketers, the answer may be straightforward. AI is unlikely to replace human creativity, strategy, and understanding. But it will increasingly enhance them.
And if history has taught us anything, the organisations that learn to work alongside new technology tend to be the ones that benefit most from it.
This version is structured for SEO and readability, with clear headings, stronger arguments, and a more thought-provoking conclusion that fits a professional digital marketing audience.