Distraction theory: how AI can help workers stay focused
How often do you feel distracted or unproductive during the average working day, whether in the office or at home? Whether it’s churning through a bottomless pit of unanswered emails or trying to find the right workspace tool to get the job done, it is easy to lose sight of work that adds value to your business.
During the average day, we become distracted more than 400 times as we are forced to switch context between apps, email and messaging channels. It is staggering to think that our attention is disrupted every 40 seconds.
This constant fragmentation of our time and concentration has become the new normal and, while many workers have adapted willingly to the situation, the bigger picture is that it is eroding our ability to maintain focus on a task and be productive. Some research has gone so far as to suggest it is having a detrimental impact on our IQs and brain cells.
Artificial intelligence (AI) and machine learning (ML) have become popular tools for producing workplace innovation. But how can we best use these technologies to build immersive experiences that boost productivity and engagement?
Using technology intelligently
A McKinsey Global Institute study suggests workers spend nearly 20% of their time looking for information internally or tracking down colleagues. Often this is because various apps and systems don’t talk to each other either — much like team members — creating unnecessary, manual work. This means that workflows are very often driven by the needs of the application, or the constraints of the system, rather than by what works best for the business or the employee.
Today’s IT experience therefore is very application-centric, but technology arguably needs to focus more on the task or outcome that the user is trying to achieve. As AI and ML capabilities mature, micro apps and other intelligent features will become better integrated at a task-based level, enabling the worker to focus on the job in hand. These intelligent systems will be able to organise a vast array of micro-functionality in a way that gives the user exactly what they need, at the time they need it.
Integrating a customer experience for employees
In our personal lives, we are used to recommendation systems being used to great effect in online consumer retail and digital entertainment services. If we could apply those same concepts to our work environment, it could significantly help with focus.
We recently showcased a high-street bank concept to demonstrate how AI-driven task and workload management could help employees in many different types of roles and industries, all of whom have an ever-present set of background activities — but who also have a need to be able to put those activities to one side when clear focus on a foreground task is required.
In the bank scenario, the branch manager was able to introduce an automated workflow, incorporating workspace intelligence and micro apps, so that when a high-value customer entered the bank, that individual could immediately be prioritised with all relevant information, forms, ID checks and financial specialists made immediately available through a single user interface, in just one click.
Greater access makes for greater outcomes
People like to work in different ways, and the rise of intuitive, no-code workflow and automation tools will enable business owners and individual employees to build their own experiences that match the way they want to work. AI technology, or virtual assistants, will learn from what users do manually and recommend (or even automatically create) workflows, thus removing unnecessary distractions from their day.
In the era of context-driven AI, offering a choice of tools and APIs is important. I like to compare this to LEGO, whereby an individual can start with a pre-built model that works in the common case, but add parts, remove parts and change it as much as they like to adapt it to their desired state. The wider the range of building bricks, doors, wheels, axles and propellers, which all fit together in a variety of ways, the more imaginative and bespoke the final creation can be.
Encouraging workspace focus
It is common for workers to confuse importance with urgency, which can lead to overload and a lack of focus. In the bank example, providing a response to a customer request for a sales quote may be important, but if a high-value customer enters the branch, they immediately become the most urgent priority.
Systems of engagement will increasingly need to perform intelligent filtering and prioritisation, showing a user only what they need at the time they need it, deferring other notifications and tasks as necessary. Once we reach the point where systems can intelligently decide what, and what not, to put in front of a user, our likelihood of being distracted during the working day will decline.
By automating the repetitive, mundane tasks that waste employees’ time, knowledge workers can focus their efforts on the creative projects that add the most value to businesses, without distraction. This will not only have an exceptional influence on business productivity in the future, it will also boost the quality of work.
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