AI productivity expert with 12 years of experience explores how technology is reshaping time management for students
In an era where artificial intelligence is becoming a part of everyday life, from answering customer service calls to offering health advice, its effect continues to grow. Chatbots draft emails, virtual assistants set reminders, and AI-powered platforms help structure our daily tasks. But can artificial intelligence go beyond assisting with minor tasks and truly revolutionize time management?
The question is more than just theoretical. With work, studies, and personal things, time management has become a critical skill—one that many struggle to master. If AI can help manage our schedules, forecast deadlines, and adopts to shifting priorities, it could give us more time for creativity, relaxation, and personal development.
To gain insights into AI’s impact on productivity, we interviewed Denis Kirichenko, an AI expert with more than 12 years of experience and the founder of voiset.io, and a member of the Association for the Advancement of Artificial Intelligence (AAAI). Kirichenko has dedicated years to developing AI-driven productivity tools, receiving global recognition for his work. In 2025, he will present at LEAP, one of the world’s largest tech conferences held in Saudi Arabia, where AI innovations in time management are drawing immense international interest.
Can AI really help us regain control of our overloaded schedules? Or is the dream of a perfectly optimized day still far from reality? Kirichenko shares his insights on where AI-powered time management stands today—and what the future will be.
How do you see AI changing the way people approach time management and productivity?
Humanity has always wanted to boost productivity, from the discovery of fire to preparing for space exploration. We continuously develop plans to optimize our actions. Planning can be likened to the role of a freight dispatcher who charts the best route considering traffic, addresses, and road conditions. This same concept applies to task management: we identify which tasks are best tackled in the morning, which are suited for the evening, and which should be deferred.
For many years, planning relied on basic mathematical algorithms that identified the optimal timing for tasks based on their nature. Eventually, specialized AI models were developed for route optimization and workload distribution, but their use was confined to specific situations.
With the advent of more advanced AI models, integrating artificial intelligence into various aspects of life has become feasible. Now, AI can function as a personal assistant that adjusts to your work habits. It evaluates your productivity, monitors how frequently you delay tasks, identifies the areas where you generate them, and assesses how many tasks you can realistically accomplish in a day. As a result, when scheduling a new task, AI can recommend the ideal time for it based on your habits and data.
Can AI truly help students and professionals overcome procrastination, or is human discipline still essential?
Great question! To much people struggle with planning and procrastination. We everyday tell ourselves, “I’ll do it tomorrow” or “Maybe later.” Everyone has tasks they try to put off.
Discipline is urgent in everything, and the simple example is going to the gym—if you want results, you must to follow the schedule. When it comes to AI helping with discipline, it’s a tricky subject. Any system can only remind you about tasks or work with already created ones. But the willingness to create tasks and actually work with an AI assistant still has to come from the user.
Once a task is created, AI can suggest the best time to complete it, reschedule if needed, or even break it down into smaller parts. But AI, at least for now, can’t physically make someone complete a task. Maybe in the future, with deeper integration like Elon Musk’s brain-chip technology, we’ll see something more advanced. But for now, AI serves as an advisor or assistant in scheduling, helping to reduce procrastination—but personal motivation is still key.
How does AI determine priorities in scheduling, and can it adapt to the unpredictability of daily life?
AI determines priority based on historical data and previous user behavior. When a person creates a task, the AI first analyzes their intent and then evaluates how critical the task is. Certain words like “urgent,” “important,” or “necessary” can act as indicators, helping AI understand the significance of the event or action.
In most cases, AI assigns priority based on the overall context of a user’s tasks, gradually forming a personalized scheduling algorithm. If a person disagrees with the AI’s priority, they can manually adjust it, which serves as a learning signal for the model.
Right now, AI is highly effective in planning within the framework of weekly schedules, where tasks can be arranged without precise timing. However, AI development is advancing much faster than its integration with external services, such as real-time traffic data or workplace occupancy tracking.
Deeper integrations will come soon, making automatic rescheduling a natural evolution. But, in my vision, AI has yet to solve the unpredictability of human behavior—like when someone unexpectedly extends their lunch break for a spontaneous conversation over coffee, throwing off the entire schedule.
Looking to the future, do you think AI will fully automate productivity, or will there always be a need for human involvement?
Right now, there is a huge focus on using voice to interact with AI agents because it is the easiest way to input information into the system. Many people struggle with turning thoughts into text, and there is also a major challenge with language diversity across the world. At its current level, AI helps solve this by converting speech into text without requiring manual processing.
The result is a just text, which is then translated into specific commands for different platforms. Many people are familiar with Alexa, Siri, and Cortana—these are designed as digital assistants within different devices. However, their primary function is not task management, so their quality in this area is often badly.
Today, some companies focus specifically on Voice-to-Text solutions, as training AI models for this purpose requires a specialized solutions. The best results currently come from combining different AI models—some handling voice input while others focus on scheduling and task planning.
Another important factor is that voice input significantly reduces language barriers. AI can switch between languages in seconds, which is crucial for multilingual teams. While AI is advancing rapidly, full automation of productivity still requires human input—at least for setting priorities and making final decisions.
What ethical problems arise when AI takes over aspects of personal planning and decision-making?
The ethical concerns surrounding AI have been discussed since early its creation, and I think the 2004 movie I, Robot illustrates this issue well. In the film, a robot saves a specific person based purely on an algorithm designed by its creators—without any empathy for the other victim.
Even today, AI agents are being programmed with ethical guidelines that allow them to reason within certain restrictions. For security reasons, we also implement ethical boundaries in AI-driven planning, ensuring that our tools cannot be used for criminal activities. However, I want to emphasize that this is our own initiative rather than a strict government requirement.
If you had to predict the next big step in AI productivity tools, what would it be?
I think the next major step in AI will be using collected data to help correct human behavior—whether for students, employees, or professionals—to improve long-term productivity. We already see clear patterns showing that overloading with tasks can lead to short-term productivity spikes of 120%, but in the long run, it often results in procrastination and burnout.
In the future, I believe AI will integrate with various external services, such as smartwatches, banking systems, or even cars, to build more accurate personal productivity predictions. Based on my experience with AI task management, I’ve noticed that people who aim to maximize productivity often need expert guidance in planning. Our goal is to provide this assistance through AI, helping users maintain a sustainable and efficient work rhythm.