Why can digital tools create more work? A tool can make a task seem finished long before the person responsible is able to let it go. The presentation is drafted, the email is ready, the website change is documented, and the social post sits on a calendar. Yet someone still has to check the facts, save the right version, confirm the live result, and decide what happens next.
This is one of the less visible pressures of technology-assisted work, and it sits alongside the technostress many employees already report. Faster preparation does not always mean less work; it can simply produce more partly finished tasks competing for attention. I noticed it while organising the digital side of my own consulting practice, and the challenge will be familiar to small organisations everywhere: more platforms, more outputs, and more status indicators, but not always more certainty. It also builds on an idea I explored in why AI at work goes better when people feel safe to learn.
Why digital tools can create more work for people
Consider a communications task. A well-written, correctly addressed draft is one achievement. A message sitting in the Sent folder is another, and a reply showing genuine interest is another still. A meeting, an agreed scope, and an actual payment are different outcomes again, each needing its own evidence.
When all these states collapse into the single word done, reporting becomes misleading. A team may count a draft as outreach, an enquiry as a qualified lead, or an automatically tracked conversion as a new customer. The same confusion affects well-being. Someone may be quietly monitoring dozens of nearly finished pieces of work while the dashboard suggests everything is running smoothly, and it is hard to switch off when you don’t know what will fail if you stop checking. No wonder rest can feel like doing something wrong.
In a recent review of my own systems, a platform’s conversion count had to be reconciled with real contact, booking, and payment records. The figure was not false; it simply answered a narrower question than the commercial one I cared about, and treating the two as the same would have led to a poor decision.
Make the hand-off part of the design
An AI-assisted workflow should spell out what happens after the content is generated. Who checks the evidence behind a claim? Who can access the final publishing system? Who confirms that a scheduling or payment setting actually works? And when does responsibility pass from the person preparing the work to the approver, the publisher, or the recipient?
- Intended outcome: What the task is ultimately meant to achieve.
- Current state: Where the work stands right now, in plain words.
- Responsible person: The one name who owns the next step.
- Evidence of completion: What would prove the task is genuinely finished.
- Next action if blocked: What happens, and who decides, if the task stalls.
A hand-off record this short is not paperwork for its own sake. It stops the same uncertainty returning to everyone who touches the work. The principle applies to education and mentoring too, where I have worked for many years: giving instructions is not the same as knowing someone can do the task alone. For technology, the matching question is whether people can confidently use, evaluate, and correct a system without depending forever on whoever introduced it.
When more automation is not the answer
Organisations often meet complexity by adding another subscription, another automation, or another reporting layer. Each may be useful on its own, but together they multiply the places someone has to look for the truth. A better step may be to simplify the workflow before automating it: remove duplicated approvals, choose one reliable source of current information, decide which tasks genuinely need human judgement, and agree where the process should stop rather than spawn another activity.
The aim is to cut avoidable checking, not accountability. For consequential decisions about clients, money, health, privacy, or reputation, human review remains essential, and automation can support it by making the underlying information easier to find and compare. I have also learnt to tell apart a system that cannot act from one that has not been authorised to act. Both leave a task unfinished, but one needs a technical fix and the other needs a decision from whoever owns the responsibility.
A more human measure of productivity
We tend to describe digital transformation in terms of speed, volume, or the number of tasks automated. Those measures are useful but incomplete. A person interrupted all day to check whether other systems did what they promised may generate more digital activity while feeling less in control, and a team that sends more messages without knowing who replied may be creating noise rather than better relationships.
So I would add three questions to any evaluation of an AI workflow. Did it reduce total effort, including checking and correction? Did it leave the next person with clearer responsibility rather than more ambiguity? And did it produce an outcome that matters beyond the software itself? They are less glamorous than a demonstration in which a tool finishes a task in seconds, but they are closer to the work people actually have to live with.
My own path has run from customer-facing operations through education, executive roles, and independent advisory work, and one lesson has held throughout: a process is useful when it helps people act with understanding, not merely when it leaves an impressive record of activity. AI can contribute a great deal to that, but the unfinished loop still belongs to someone, and designing an honest finish may be one of the most practical ways to make technology serve the people expected to use it.
FAQs
- Why do digital tools create more work? They speed up preparation but leave checking, confirming, and following up to people, so partly finished tasks pile up.
- What is an unfinished loop? A task that looks done in a system but still needs a human to verify the result or decide the next step.
- How can teams reduce digital busywork? Simplify workflows before automating, keep one source of truth, and record clear hand-offs with an owner and evidence of completion.
