Imagine a future where artificial intelligence (AI) proves to be entirely positive and helpful, transforming the way we manage our time and attention.
In this future, AI is our friend, helping us enter deep work by focusing on one task at a time. This contrasts with what I observe in most workplaces today, where workers are overloaded and habitually distracted.
In this post, I will explore how AI could transform productivity and time management, if used correctly. I’ll go back to basic time-management principles and discuss how AI could change the way we plan our schedules.
First, let’s understand what time management is all about.
Time management, also known as productivity, is about getting the right things done. This requires a systematic and thoughtful approach to our schedules.
Instead of using random strategies, the most productive people I coach are intentional in how they shape their time. They develop workflows and systems to help them make decisions in line with their values, priorities, context, and energy levels.
One such workflow is David Allen’s “Getting Things Done” methodology, also known as GTD (and the many adaptations that have emerged).
Allen first suggested creating and organising personal workflows to manage digital age complexities. While his ideas have evolved since the 2000s, his core time-management principles remain the same. These principles, which we have simplified and adapted in our List Assassin methodologies, continue to be foundational in how we organise our time and attention.
These habits are:
A strategy for collecting all incoming information – texts, emails, messages, calls, verbal requests, meeting actions, self-generated ideas, and more – into a single, organised stream.
A two-tier list system divided into ‘projects’ and ‘tasks’ ensures that larger, complex activities are broken down and clarified as smaller actions. This system mitigates our tendency to focus on urgent but reactive tasks (think email and urgent requests) instead of truly significant ones.
A clear and simple blueprint of your objectives, spread across multiple levels – annual, weekly, and daily plans. Your plan provides the context to help you decide what to tackle next from your lists. It also involves weekly scheduling, to ensure that your most important activities are represented in your calendar each week.
The stage where you enact your plans, using strategies like disconnecting from technologies to immerse yourself in deep work and advance meaningful projects and goals.
This entire system aims to help us manage the complexity of the modern workspace by defining our work in a way that can guide our day-to-day decisions.
The Transformation of Productivity Systems Using AI
Implementing well-designed time-management strategies is no easy feat. Unlike the prevalent approach among most knowledge workers, who rely on ad-hoc, notification-based, and unplanned workflows, embedding robust time-management systems is more challenging and demands consistent practice.
As you can imagine, the challenge with List Assassin thinking and other GTD-inspired methodologies lies in the need for discipline in how we structure our work. If we plan our time more intentionally we almost always end up with increased capacity, but few leaders or organisations make the transition.
This leads me to wonder if there could be a simpler way to manage our workflows and handle today’s complexity.
The Future of Time-Management Using AI
Let’s visualise how AI tools could facilitate deep work and single-tasking in the future, based on our foundational time-management principles:
AI assistants could help us capture all the inputs in our lives, drawing out actions from the multiple streams of digital communication such as email, Teams, Slack, phone calls, text messages, and more. In meetings, it could record our conversations and capture next actions. It could convert email-generated tasks directly into our lists, obviating manual input. Although we’d still need to capture self-generated ideas (think of the ‘aha’ moments you have in the shower), AI could record and organise our voice activated commands in smarter ways.
In other words, AI could undertake the laborious task of defining and externalising our commitments by monitoring and recording our everyday conversations and digital feeds.
Our AI assistant could then structure our captured tasks into a two-tier list (‘projects’ and ‘tasks’) on an online to-do list platform. It could identify the next logical step for each project on our list, initiate new projects as needed, and even suggest potential next actions.
Your AI assistant would review all tasks on your two-tiered ‘Master List’ and present a selection of potential tasks for the day, aligned with your annual and quarterly goals, and calendar commitments. It would schedule specific actions for the future, in line with due dates and project milestones. You would collaborate with your AI assistant to prioritise your tasks, creating a daily plan out of the options available to you.
Lastly, your AI assistant would present you with one task at a time from your daily plan, promoting single-tasking. To support task execution, your AI would open all necessary programs for a specific task and disconnect you from other applications for a set period. When focusing on deep work, AI would monitor all incoming digital communications and provide basic responses to messages when you are offline.
Of course, you would still need to manage pressing issues that arise unexpectedly. But AI could also manage these.
For instance, for an urgent email of genuine importance, your AI would interrupt your workflow and inform you of the need to switch contexts, minimising interruptions for truly urgent issues.
After completing a focused task from your list, you would receive a summary of the emails and messages that arrived during your “deep-work” time block, providing an efficient way to review and respond to these reactive work tasks. And naturally, your AI assistant would handle the majority of the work needed to draft responses to these emails.
In this way, you could make space to focus your efforts on creative, knowledge-based tasks, while your AI assistant handles the rest.
This is a description of generative AI at its best, where AI tools help us capture, plan, prioritise, and focus, rather than simply increase the volume and speed of information flowing our way.
The culmination of these processes could enhance our ability to get the right things done, allowing AI assistants to handle our working memory and free up time, leaving our creative genius for tasks that only a human can perform.
Will We Get This Right?
This scenario is a hypothetical example of how we might leverage AI to boost our productivity in the future. Whether this becomes reality remains to be seen.
AI might dramatically improve how we organise our time and attention, or we could end up with more of the same – distracted employees constantly responding to an ever-increasing stream of digital communications and extraneous requests… made faster by AI.
As always, the secret to sustained productivity is whether or not we choose to ‘make space’ in our lives. Will we continue seeking quick-fixes for complicated problems? Or will we take time out of our busy lives to think deeply about, applying process thinking in the way we design our workflows, resulting in something fresh and creative?
Meanwhile, why wait for AI to solve our problems – the solution to our lack of attention, focus, and ability to manage complexity is already available. Let’s make space to establish systems and habits to Capture, Organise, Plan, and Do what truly matters, becoming truly productive in what we do.
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