AI-Induced Digital Friction: The Next Attention Culprit

Welcome to the age of the three-second attention span. As artificial intelligence becomes more ingrained in our daily professional lives the impact extends far beyond the enterprise tech stack. The eventual proliferation of AI services, particularly specialized chatbots and “GPTs”, will introduce ‘AI-induced digital friction. This phenomenon is not new. It is characterized by the fragmentation of user time and attention via the use of workplace technology. Moreover, digital friction poses significant threats to productivity, wellness, and cognitive efficacy.

The burgeoning issue of AI-induced digital friction lies in the paradox of choice and accessibility that spot AI services bring. Every day we see it on the news. Enterprise software vendors are heavily budgeting their R&D into the use of AI. Small developer houses and armchair enthusiasts are rushing to create ‘baby-GPTs’ which have spot use cases in mind. This movement of AI R&D is foreshadowing the fastest commodification of any utility known to date.

One the plus side, AI will be a boon for human creativity and progress. There are readily available LLMs, tools, dev-kits, even free training. Many services are free for anyone seeking to create novel solutions as a catalyst for advancement.

However, if the past signals the future, we can anticipate the potential proliferation of AI overload given the hype and promise. From 2005 to present, the proliferation of SaaS services led to an increase in application sprawl within the work environment. This led to an explosion of information overload and the decrease of workplace focus over the last twenty years. Similarly, there will be an explosion in specialized AI applications which will become more places to go to hunt for information.

It takes little to imagine how each SaaS vendor will aim for AI efficiency in isolation. After all, application vendors never sought to find common ground over the last 20+ years. A SaaS vendor's value is defended with the user spending as much time in their respective applications as possible to justify spend. This cumulatively contributes to a fragmented digital workplace – and your attention. Think of the staggering number of applications an average employee switches between over 30+ per day, with nearly 1200-3000 context switches within that same 8-hour period. All of this leads to reduced overall productivity and increased cognitive load.

Employees interact with an average of 35 applications in the course of their work day. (Source)

The influx of AI tools in the modern workplace introduces a significant cognitive challenge: the cost of constant context switching. As workers navigate a myriad of AI interactions, the brain will struggle with rapid and frequent digital multitasking that leads to a scattered focus. This constant shifting trap of cognitive resources leaves the user in limbo, undermining efficiency and productivity.

Beyond just inefficiency, this chronic context switching takes a toll on mental and physical health, elevating stress, anxiety, and the risk of burnout. Symptoms like headaches and fatigue are becoming more common. Furthermore, research indicates that such rapid task-switching hampers memory retention, as our brains are less capable of absorbing information from each task. This incessant juggling of micro-tasks creates a hidden productivity sinkhole. It's not just the time lost in the switch itself, but the inability to reach a state of deep, focused flow that truly impacts efficiency. As this pattern repeats across an entire workforce, the cumulative productivity loss becomes a significant, yet often overlooked, concern on the balance sheet.

As AI-induced friction compounds existing digital friction, then the question arises, 'how can CIOs and digital workplaces leaders effectively ensure that AI is utilized correctly - and to its full potential. There are three key strategies to tackle AI-induced challenges in the digital realm: implementing organizational strategies, adopting technological solutions, and modifying personal behaviors.

Let's delve into some simple strategies to get started.

Organizational Strategies:

These strategies involve changes at the policy and management level within an organization that allow proper alignment to business objectives.

• AI/ML Governance Program: Cutting edge organizations are well underway in standing up cross functional teams to manage existing machine learning (ML) and emerging generative AI solutions. This helps to ensure AI is operationalized appropriately to the enterprise and employee personas.

• AI User Training: Change is hard. It’s harder when employees are not included in the efforts. Offering comprehensive training programs to help employees effectively utilize AI tools and manage their cognitive load can aid in acceptance of the new paradigm.

• Mindful Tech Usage Policies and Focus Time: As a rule, establishing workplace policies that encourage mindful technology usage, including setting boundaries for after-hours communication and promoting uninterrupted work periods can aid in diminishing digital friction.

Technological Solutions:

These strategies focus on the development and implementation of technology to mitigate friction.

• Unified AI Build Platforms: Standing up integrated platforms that unify multiple AI tools and or services help by reducing the need for employees to switch between different applications. These platforms are agnostic to AI services but also allow for personalized experiences for employees.

• Universal AI Work Assistants: Implementing an AI Work Assistant (e.g. Workgrid) allows for a universal solution that connects across systems, applications, and services. These types of assistants can be tailored to employee persona and work styles – but also reach across all back-end applications and even multiple AI services. This means less app hopping for the employee and a single platform for developers.

• AI-Driven Workflow Optimization: Utilizing machine learning to analyze and optimize business workflows for greater efficiency and reduced cognitive load can help provide information to the governance team on where efficiencies can be made.

Personal Behavior Changes:

These involve changes at the individual level, focusing on how employees interact with technology.

• Mindfulness in Tech Usage: Encouraging employees to be more mindful of their tech usage, recognizing when it's beneficial to take a break or focus on a single task.

• Personal Digital Detoxes: Promoting regular intervals where employees disconnect from digital devices to reset their cognitive state and reduce burnout risk. Sometimes a gentle reminder is all you need.

• Metacognition (aka, ‘Where is my Mind?): Knowing what is stealing your focus is a difficult task. However, regular practices can help develop stronger skills and executive functions to aid in having greater focal intent. These can include mindfulness, journaling, meditation, and even thinking out loud.

For digital workplace leaders and CIOs, it's crucial to grasp the nuances of this emerging trend. Understanding the implications and implementing well-rounded strategies will be key to leveraging AI's incredible capabilities without detracting from what it means to be human. Navigating a path to a balanced interaction with AI technology is intricate yet attainable with a blend of technology, humility, and strategy.