Introduction
Since the first electronic message was dispatched in 1971, email has become the silent backbone of professional communication. It arrived with the promise of speed, clarity, and smoother collaboration, yet many now find it a constant, sometimes overwhelming presence in their workday.
Today, generative AI tools such as ChatGPT and Microsoft Copilot are being touted as the next wave of assistance, capable of drafting, summarising, and replying to messages on our behalf. Recent research from the ARC Centre of Excellence for Automated Decision Making & Society shows that 45.6 % of Australians have tried a generative‑AI application, and 82.6 % of those users employ it for text creation—email being a natural fit.
What will happen when we hand over one of the most routine aspects of office life to machines? Could AI truly cut through the clutter, or might it inadvertently generate even more correspondence?
Why the printer isn’t dead yet
When email first replaced much of the paper‑based memos, analysts predicted office printers would become relics. In reality, most workplaces still keep a printer on hand.
Abigail Sellen and Richard Harper demonstrated in The Myth of the Paperless Office (2001) that digital tools rarely eliminate older work habits; they reshape them. Paper persisted because it offers unique affordances—easy annotation, quick visual scanning, and the ability to spread out documents—features that early digital solutions struggled to replicate.
At the same time, email dramatically lowered the cost of sending messages, encouraging people to write more often and to larger audiences. The net result was a surge, not a decline, in overall communication volume.
Circling back to today
Will AI follow the same pattern? Early indications suggest it will behave similarly. Rather than erasing established email practices, AI tends to amplify them—though it may improve grammar and inject an oddly optimistic tone.
Some emerging AI platforms claim to handle an entire inbox, raising fresh concerns about privacy and data security. In practice, many of these tools act as “polishers,” softening blunt requests, adjusting tone, or fleshing out terse replies, thereby making the everyday performance of email a little smoother.
Instead of eliminating the need to communicate, AI simply offers shortcuts for the more delicate aspects of message crafting.
What email is actually for
Email serves not only to transfer information but also to sustain routine relationships in the workplace. Phrases like “just looping you in” or “circling back” function as a shared dialect that signals competence, responsiveness, and authority while softening demands.
If AI reduces the effort required to generate these social signals, their importance may not fade; instead, the dynamics could shift in unexpected ways. A surge in AI‑generated drafts could turn correspondence into a sort of bureaucratic mime, where everyone outsources sincerity and the true human contribution becomes murky.
The real labor of email has never been limited to wording. It has always involved scanning, sorting, and deciding what demands attention. AI does not erase this workload; it may actually increase it by delivering more polished, seemingly important messages that demand a response.
This raises a fundamental question: if machines can handle the veneer of responsiveness, why do we continue to create situations that require it?
Looking forward
Imagine a workplace where email is not the default solution for every coordination need. Fewer perfunctory check‑ins—such as “just touching base” or “looping you in”—could lead to clearer expectations about which messages truly merit a reply.
Like paper, email will likely endure because of its simplicity, flexibility, and universality. It allows information to be deferred, revisited, forwarded, or even ignored without breaking the workflow.
If AI is to make a meaningful impact, it should expose the ritualistic and habitual aspects of our inbox habits, highlighting what is genuinely essential and what is merely legacy fluff.
And perhaps, if the bots keep signing off with “hope this finds you well,” we’ll finally feel free to retire that line for good.
Key concepts
- Agentic consumer AI
- Generative AI ethics
- Artificial intelligence labor economics
Source credit: TechXplore1
Image credits:
- Image 1 - credit: TechXplore1
- Image 2 - credit: TechXplore1
- Image 3: Credit: Pixabay/CC0 Public Domain - credit: TechXplore1
- Image 4: The Conversation - credit: TechXplore1
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