It is strange how in a time when AI can write reports, summarize meetings, and predict trends, simple human coordination still slips. Tonight at 11 pm, while reviewing the week’s tasks, I realized the TDS filing had not been done. It was not a complex calculation or a matter of missing data. The responsibility was assigned, the process was known, and the deadline was fixed. Yet it sat untouched. In the back of my mind, I had assumed it was taken care of, partly because I have trained myself to believe that reminders, alerts, and automated systems would catch such things before I needed to. But the reminder never came, and the task stayed dormant until I happened to notice it by chance.
I reached out to my CA’s team immediately, knowing it was late but hoping someone would be available. To their credit, they responded quickly, acknowledged the oversight, and acted promptly to complete the filing. There was relief in knowing the penalty could be avoided, but it left me unsettled. This was not a case of ignorance or incompetence. It was the same problem I have seen across teams and industries: when people are on leave or focused on other work, deadlines can vanish from collective attention, even when technology exists to track them. AI tools do not replace the need for someone to actively own a task, and if that ownership is diffused, the system becomes fragile.
The irony is that AI excels at the kind of pattern recognition that could prevent this. A well-integrated workflow could flag the absence of activity before a deadline, send escalating alerts, and even prompt alternative assignees if the primary person is unavailable. But such systems require setup, maintenance, and a culture that treats them as more than optional tools. In reality, many professional relationships still depend on a chain of human follow-ups, verbal nudges, and unspoken assumptions. When a link breaks, the whole chain fails. And no AI, however advanced, can automatically rebuild the chain unless it has been given that authority in advance.
The other challenge is timing. People still think in terms of work hours, even in roles that could, in theory, operate asynchronously. At 11 pm, I did not know if anyone from the CA’s office would be reachable. In the past, missing the window would simply mean waiting until morning. Now, the expectation is that someone should be reachable because digital tools make it possible. This expectation works both ways. I could reach them, but it also meant they had to react immediately, regardless of their own time zones or personal schedules. This is where technology can create subtle tension—it removes technical barriers but increases social and psychological pressure to always be on call.
As the filing was completed and I closed my laptop, I found myself thinking less about the task itself and more about the process. The tools are available. The capability exists. The problem is alignment—getting people, processes, and technology to work in sync, without depending on chance observations or last-minute interventions. It is easy to talk about automation, AI integration, and predictive systems, but unless they are embedded deeply into the daily operational culture, the reality is that we will keep catching these things at 11 pm, hoping there is still someone awake on the other end.