How to use AI-enabled nudging to mutually benefit managers and employees

The way we design an environment affects how we make decisions. A “nudge” is a cue strategically embedded in our environments that alters people’s behavior in a predictable way. 

Even the smallest modifications can motivate us to make different choices - without us noticing! Google employees reduced their food waste by 30%-70% simply because they replaced the bowls in their cafe with shallower ones.¹ 

Nudges are effective because our decisions are strongly influenced by mental shortcuts called “heuristics“ - cognitive biases we fall back on to reduce cognitive effort. At the drug store, we’re likely to buy lipstick or painkillers from a brand name that we recognize, rather than the most cost-effective option (thanks to a phenomenon known as the “mere exposure effect”). When choice architecture is designed effectively and ethically, nudges can help us make better decisions without exhaustive deliberation. 

Government agencies in the UK, US, and Australia have used strategic nudges to promote desired behaviors for decades. It’s no wonder that corporations are catching on to this trend in their management strategies. Nudges actually have a bigger impact on people’s behavior (per dollars spent) than traditional policy tools such as tax incentives, subsidies, and educational programs.²  

UX designers and human-computer interaction specialists can employ digital nudges to gently steer users to desired outcomes - by making use of our tendency to rely on heuristics by default. Similar to environmental nudges, digital nudges adopt a “one-size fits all,” since they target assumptions that a community collectively shares.

For example, many organizations schedule meetings using software that defaults meeting durations  to 60-minutes. So we start to assume that meetings ought to be 60-minutes—whether or not that’s necessary.

Changing the default meeting duration to 30-minutes adjusts our assumption. It might even nudge us to move through the weekly agenda a bit more quickly.³

In business management, the “one-size-fits-all” approach can only take us so far - as it fails to consider an individual's distinct short-comings, learning styles, and base knowledge. High performing companies prioritize on-the-job training and tailoring instructions to the strengths and aptitudes of the individual. 

On top of neurotypical, day-to-day learning preferences, there are currently 65.6 million Americans with learning and attention-related disabilities.⁴ These individuals thrive when information is presented according to their specific needs. For example, an employee with ADHD may perform best when presented with less information at once.⁵  

Adapting to diverse learning styles is crucial- as poor coaching harms employee experience, morale, and engagement, subsequently driving up attrition.⁶  Hence, the application of “one-size-fits-all” nudges in the workplace are significantly limited.

AI-enabled nudges can be advantageous since they allow managers to personalize feedback based on sophisticated data analytics and machine learning. 

Imagine you’re working remotely at a major corporation, and you just completed on-boarding. You are working on a task due at the end of the day, but you haven’t exactly formatted your work according to your organization’s guidelines. Unfortunately, your manager is busy, so they are unable to give frequent feedback. If your organization implemented an AI-enabled nudging system, you may be prompted to:

• Watch a relevant training video.
• Complete certain steps or actions.
• Review summaries of best practices for that task.

Thanks to advancements in AI technology, your behavior can be analyzed with pin-point accuracy, such that personalized nudges can be delivered in real-time. This means that if you respond effectively to a certain nudge (e.g. a training video), that data will be stored, so you will be prompted with the same type of cue again. Also, if you’re prone to making the same type of mistakes, you’re likely to receive a nudge again at that stage again in the process. 

Workers can even provide information about their learning styles through preliminary surveys to shorten the process of fine-tuning the AI-enabled nudges specifically to their needs.⁶

For managers, the data gathered from machine learning algorithms can help them isolate the factors that matter most. In principle, this data can be drawn from a myriad of sources like Google Workspace (or other platforms where organizations store their information) to quantify their team’s productivity levels, and prioritization of tasks. To implement this effectively, managers need to clearly define key performance indicators (KPIs) so they can be automatically tracked.⁷ This helpful information will remind managers to: 

• Check in on certain projects
• Overlook an employee’s potential short-comings
• Celebrate a worker’s performance

Managers are vulnerable to making impulse decisions - insofar as they are human. On the other hand, data-driven algorithms don’t let any relevant information fall through the cracks. While managers focus on overall strategy and promoting the morale of their team members, AI-enabled nudges can keep track of the minutiae details. 

When implemented ethically, digital nudging is the corporate equivalent to encouraging kids to look both ways before crossing the street. Quite obviously, encouraging kids to act safely around cars benefits everyone involved in the situation. In the same respect, workers must be “nudged” to do a behavior that genuinely benefits them as well - not just the powers that be. 

In the past, digital nudging has received a bad reputation for its capacity to favor organizations over the worker’s best interest. The term “sludge'' refers to design features that weaken the individual’s autonomy and capitalize profit at the expense of their well-being—like design elements that push employees to work longer hours without compensation and limit human interaction at all costs. 

However, AI-enabled nudges can be advantageous for organizations and employees, depending on how they’re used. Digital nudges can remind employees to sign up for retirement savings programs, follow safety measures, and recognize their progress.

Digital nudges run the risk of positive or negative impact, so it’s important to consider all potential consequences of AI-enabled nudging. People work better when nudges serve their best interest, which will benefit the organization in turn. 

The Decision Lab is a behavioral consultancy that uses science to advance social good. If you are interested in learning about how to effectively integrate AI-enabled nudges at your organization, please contact us to hear more about our services.