AI In Employee Recognition: Can Robots Ever Play A Part In Crafting Genuine, Authentic Feedback?

At the beginning of the movie “Scrooged," TV executive Frank Cross delegates his holiday gift list to his assistant, Grace. He asks her to send hi-tech VCRs to the most influential people on his list and a cheap set of towels to everyone else. Delegating and simplifying his gift-giving removes all sentiment from the act, but Frank has other priorities. In the real-world workplace, this is remarkably similar to what happens when people use an AI tool to generate artificial messages of employee recognition or performance feedback. It's fast and convenient, but the result feels hollow.

There are 33x as many LinkedIn posts dedicated to generative AI and ChatGPT compared to a year ago— the robots are here to stay. But, the difficulty with adopting this sparkling new technology is understanding how to use it responsibly to enhance rather than damage the employee experience. Just because a machine can do something doesn't mean it's the best solution.

Our guide covers why people are attracted to using AI as a workload shortcut, how they might use it to deliver feedback and recognition, and the challenges of keeping employees engaged if they do. With expert commentary and the latest data, let's dive into the debate.

How AI Is Impacting The Workforce

AI has long been on most people’s radars, but the hype peaked in November 2022 when ChatGPT was released for public use, attracting more than a million new users in its first few days. Countless other generative tools and features have since launched, sending ripples of trepidation and anticipation throughout the workforce.

Microsoft's 2023 Work Trend Index report reveals that 49% of people are nervous that AI's speed and efficiency will replace their jobs. However, this anxiety is overshadowed by the 70% of employees excited that AI will reduce the burden of their mounting workloads.

Whichever side of the coin you're on, here's a glimpse at how the working world has embraced AI so far.

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Reclaiming Time And Energy

Employee burnout was classified as an occupational phenomenon by the World Health Organization in 2019. If your employees have feelings of energy depletion or exhaustion, increased mental distance from work, or reduced professional efficacy, the cause might be burnout.

Future Forum Pulse's Winter 2022 snapshot revealed that around 42% of the global workforce is burned out. Microsoft research explains that 64% of employees struggle to find enough time and energy to complete their work, and 68% report a lack of uninterrupted focus time during the workday.

So, how are workers spending their time? In an analysis of Microsoft 365 apps, the average employee spends 57% of their time in meetings, answering emails, or engaged in direct chat. They spend the remaining 43% working on documents, spreadsheets, and presentations.

How AI could help: AI is a whizz at handling tasks like writing meeting agendas, drafting emails, scheduling appointments, and automating routine grunt work to save time and energy.

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Supporting Managers

Individual contributors aren't the only type of employee feeling the pinch. Managers are increasingly expected to become better leaders by regularly connecting with their employees to aid their professional development and ensure inclusion. This could be the reason that 43% of middle managers feel burned out (more than any other worker group), according to Future Forum.

In our own employee recognition survey of 800 US employees, we revealed the importance of employees receiving frequent praise, which undoubtedly puts pressure on managers to communicate this feedback constantly.

• 77.9% of employees would be more productive if they were recognized more frequently 
• 98% of employees who receive daily recognition feel valued by their employer 
• 40% of employees rank managers as the group that has the most impact on them recognition-wise

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How AI could help: Managers may turn to AI tools to speed up the delivery of employee recognition or performance appraisals. In the sales industry, Harvard Business Review reports that managers also use revenue intelligence platforms as an AI coaching tool to analyze customer calls and deliver tips and feedback to sales team members.

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Tackling Poor Leadership

Subpar leadership impacts company culture, resulting in 37% of employees leaving their jobs. A joint US and UK study conducted by Censuswide found that most manager-employee issues were based on interpersonal failures. 14% of employees reported their manager's lack of appreciation as the reason for quitting, while 12.4% mentioned a lack of empathy.

How AI could help: A robot boss may seem a step too far, even for companies that have readily embraced AI. However, a startling 1 in 5 employees believe that AI would perform better than their current manager, according to the Censuswide research. Interestingly, 23% of HR employees would be happy for a bot to replace their human boss, which is food for thought.

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How Are Companies Using AI-Generated Feedback?

Managers and HR pros have been using generative AI in various applications—some are a better fit than others. For example, talent acquisition teams may use ChatGPT or similar to craft a quick job ad to post across multiple recruitment platforms. Similarly, L&D teams might lean on AI to create customized learning recommendations based on an individual's latest performance review. There is no harm with either of these approaches, right?

But people teams have found another use case for generative AI, which could harm the employee experience. They're relying on artificial intelligence to churn out robotic messages of kudos that managers or peers would traditionally have written or typed by hand. Here's how some are already using it:

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Writing Entire Messages

Coming up with entire messages of recognition is challenging, especially given the pressure to deliver them promptly. Some managers and peers defer to artificial intelligence to write entire messages from scratch.

Example prompt: I need to praise Alex for hitting their sales target this week. What can I say?

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Providing Recognition Ideas

For those who prefer to write their own messages but don't know where to start, AI can provide a structure to work from.

Example prompt: I want to praise Marion for her fantastic customer service. What points and examples should I include in my message to ensure it sounds genuine?

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Reviewing Messages Of Praise

If you've already done the legwork and created a heartfelt message, AI can act as a second set of eyes to double-check that your words make sense and are likely to strike the right chord with the recipient.

Example prompt: I want to thank Xavi for his outstanding team presentation today. Can you check that my message is error-free, reads well, and sounds authentic?

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Identifying Employee Accomplishments

Natural language processing (NLP) and sentiment analysis can help teams identify and track employee recognition moments and formulate how to offer praise.

Example prompt: Here's a log of Sarah's recent customer interactions. Can you help me find noteworthy moments where she's gone above and beyond to deliver a great customer experience?

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8 Challenges Of Using AI In Employee Recognition

Generative AI is exciting, shiny, and new. It undoubtedly has many practical applications that are already changing the trajectory of the working world. However, it's easy to overlook the potential pitfalls of using AI for employee recognition, which could damage relationships between colleagues and employers. Here are some points to consider:

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1. AI Recognition Lacks A Human Touch

At the risk of stating the obvious, AI messages are artificial. They're created by technology and lack human input or emotion. We spoke to Human Resources Director Janelle Owens from Guide2Fluency, who shared her concerns that machine-generated messages wouldn't resonate with her employees:

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“I wouldn’t be open to using AI to generate artificial messages of praise and recognition for our employees. Personally, I think the messages would lack creativity and personality, and our employees would see right through it. I don't think it would resonate with our team members. With praise, I think it needs to be clear that it's from an actual human being.”

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Jarir Mallah, Human Resources Manager at Ling App, agreed that humans play an essential role in delivering feedback, and a machine can't replicate this. He told us:

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“Giving praise or feedback must have an identifiable human element; otherwise, the meaning and intent become of little to no value. Who cares what AI thinks? People care and react to what other people think.”

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2. AI Praise Suggests You Can't Make Time For Your Employees

Max Wesman, Chief Operating Officer at GoodHire, explored the idea that it's not so much the content of the message that employees respond to but rather the energy that goes into crafting and delivering it. 

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“AI-generated praise messages feel disingenuous and hollow because there’s no real effort made on the other end of the “thank you.”

Consider a handwritten thank-you note. The words of praise are personalized, and the recipient is as touched by the effort made to buy or make a card and deliver it as they are by the heartfelt message.”

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It’s a similar situation to customer service departments using chatbots to handle incoming queries. Chatbots are efficient, saving a company’s time and money, but 46% of consumers believe that companies deploy AI to keep them away from live agents. Just as they want customer service departments to dedicate time to speaking with them, employees expect managers or peers to take time out of their day to genuinely recognize their achievements.

Denise Hemke, Chief Product Officer at Checkr, offers a workaround for offering genuine human praise on a busy schedule:

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"AI usage for praising employees sends one loud and clear message: you don't have the "time" to thank people personally. The best way to use AI as a part of the recognition process is to set automated reminders to praise your team and pull performance data that can help you see a snapshot of employee progress at any time."

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3. Employees Don't Like Or Trust AI Feedback

Although AI is relatively new to the workplace, some interesting research has already analyzed the impact of artificial feedback on employees. "The Janus Face of Artificial Intelligence Feedback" study followed a large financial services company that used powerful AI analytics to determine its feedback.

The results found the quality of feedback improved to the extent that employees achieved a 13% job performance boost compared to those who received human-generated feedback from their managers. However, this effect was reversed once the employees realized their feedback came from a machine. Workers who were told their feedback was artificial performed 5.4% lower than the human feedback group.

We can put this change down to algorithm aversion. If people have ever experienced an algorithm such as Google Maps making a mistake, they're less likely to trust a machine again, preferring human judgment. This is crucial in understanding how positive reinforcement may work in employee recognition.

Example: Imagine praising Anna for her excellent active listening skills in the latest team meeting. The research suggests she may be more likely to continue this behavior if her manager delivers a human-generated message but less likely to believe the information if she knows it's machine-based.

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4. AI Messages Weaken The Leader-Employee Relationship

The relationship between managers and their employees is critical for employee satisfaction, engagement, and productivity. It relies on trust, understanding, and respect. AI-generated messages of recognition run the risk of shallow relationships where managers don't take the time to get to know their direct reports individually. Denise Hemke explains how this can be damaging:

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“Using AI to generate artificial messages of praise depersonalizes the experience on both ends. Leaders miss out on the opportunity to ponder and consider deeply how their employees' performances are positively impacting them, and employees feel unseen and disconnected from leadership.”

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5. AI Is Addictive

It's reasonable to anticipate that some managers may not initially intend to rely on AI to deliver employee recognition but become more dependent on the technology over time. At first, they need a quick time-saver on a busy day but increasingly depend on these tools over using their own words.

Reliance on machine learning has been a problem in some medical settings, where hospital leaders deny doctors access to AI to ensure it doesn't skew their decision-making. After studying the impact of AI on critical diagnoses, hospitals have taken steps to insist that doctors prioritize their human judgment and training before reviewing machine recommendations.

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6. AI Feedback Isn’t Sufficiently Tailored To The Employee

Individual recognition messages should always be clear, genuine, and tailored to the recipient. This includes carefully choosing:

• The tone of voice or level of formality 
• Range of vocabulary, including technical jargon 
• Level of detail

Managers and peers who work with an employee daily are likely to get the balance right to ensure the message hits home in a way that AI may struggle with. In one study, an AI tool delivered feedback that was too complex for employees with a lower level of skills to understand. At the opposite end of the scale, highly skilled employees found that feedback messages lacked nuance—they wanted more detail.

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7. AI Is Biased

Bias is rife in the workplace, with 188 known cognitive biases impacting hiring and firing decisions, workplace promotions, performance reviews, compensation, interpersonal relationships, and employee feedback. Businesses may turn to AI, believing it's more data-driven and impartial than humans, making it impossible to choose favorites. But by understanding how AI has been trained, it's easy to see that bias has always been a part of machine learning.

AI platforms like ChatGPT are pre-trained using various websites, books, and articles. This helps the platform learn grammar, vocabulary, facts, reasoning abilities, and common sense reasoning. This initial dataset contains natural biases and is then fine-tuned by human reviewers who unwittingly introduce their implicit biases into the mix. Finally, the person prompting the AI tool can use biased language to skew the output.

As an example, Amazon abandoned its AI-backed resume screening model after determining the software was strongly biased towards male candidates. The tool penalized applications from candidates who attended all-female colleges or used the word "women's" in their resume.

Imagine the impact on your employee recognition if your white male employees receive more glowing praise and feedback than your black female employees. How can you measure if your AI tool of choice is truly fair?

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8. Companies Lack A Formal AI Security Policy

As companies rush to adopt AI and keep pace with competitors, many still need to figure out how to design a robust AI policy that protects the business or employees from the implications of using the technology. In a Qualtrics report, 60% of employees say their company doesn't have an AI policy or hasn't shared it yet. Many feel they need help with how to use AI safely and what is or isn't permitted.

Example: It might be tempting to include an employee's personal or sensitive information in an AI prompt to receive a personalized recognition message. However, when we asked ChatGPT itself if this was an acceptable practice, the platform advised against this: 

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“ChatGPT's responses are generated based on the broad patterns it has learned from its training data, which includes a wide range of text from the internet. It doesn't retain memory of past interactions beyond the current session, and it doesn't have direct access to individual users' contributions.

However, it's always important to be cautious about sharing sensitive or proprietary information in any online platform, including interactions with AI models. While OpenAI has safety measures in place to prevent certain types of content from being generated, it's still a good practice to avoid sharing confidential or private information with AI models or any online service.”

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5 Best Practices For Delivering Genuine Employee Recognition

Employee recognition can achieve phenomenal results for your organization when managed correctly. In our Nectar survey, 83.6% of employees stated that recognition for their contributions affects their motivation to succeed at work, and 81.9% of employees agree that it also improves their engagement.

Whether you plan to stick with traditional human-crafted employee recognition, switch to the time-saving benefits of AI, or opt for a hybrid approach, here are five best practices to reap the benefits of praising your employees.

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1. Create A Psychologically Safe Space

Encourage managers to acknowledge employee achievements genuinely and authentically to create a psychologically safe space free from fear or mistrust.

Employees must trust the motivation behind a recognition message for it to truly hit home. They can quickly become suspicious if the words are too generic, aren't aligned with the company's values, or don't sound relevant to their contribution.

Employees should also feel safe to express their appreciation for colleagues and be part of a team that acknowledges each other’s successes. This means establishing camaraderie and a team environment that celebrates progress and rewards effort.

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2. Personalize The Recognition

Meaningful praise goes so much further than a one-liner. Any positive feedback should provide specific examples of the outstanding behavior, which makes it clear you've recognized the depth of their work and motivates them to replicate that same behavior in the future.

Example: Instead of "Great job today, Brian," opt for "Brian, I was really impressed by your level of creativity in our brainstorming session today. You came up with several great ideas that will help us move the project forward. In particular, I was fascinated by your suggestion to tackle our current production bottleneck."

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3. Equip Your Leaders With Human Skills

Leaders must balance out technology by continuously developing soft skills that speak to the humans in their teams. These include:

• Empathy: Leaders who demonstrate vulnerability and empathy can genuinely understand and share the feelings of their team members, making it easier to acknowledge and share wins together.
• Effective communication: Leaders must clearly and effectively convey information, expectations, feedback, and visions to their teams. This involves not only sharing information but also ensuring that it is understood.
• Emotional intelligence: Leaders with high emotional intelligence (EQ) are adept at recognizing and understanding their own emotions and those of their team members. 
• Listening: Active listening is critical to understanding employees' needs and achievements. It enables leaders to offer recognition that is relevant and impactful. 
• Adaptability: Each employee has unique preferences and motivations, so leaders must adapt their recognition style to suit individual team members. This adaptability means acknowledging accomplishments publicly, privately, or through personal handwritten notes or tokens of appreciation.

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4. Communicate Your Feedback And Recognition Policy

An employee recognition program can only be effective if your team members have a shared understanding of the following:

• How to craft messages
• What to include in feedback and recognition 
• How frequently to recognize employee contributions 
• What tools you may use to support employee recognition 
• How to use tools effectively without compromising sensitive data

Clarify all the above via a formal policy, which you can share via email, during onboarding, and as part of your company wiki so everyone can access this vital information.

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5. Involve Your Employees In Technology Decisions

A Microsoft survey of 4,500 company executives revealed that involving employees in decisions about the tools they’re using improves overall engagement and satisfaction.

If you’re unsure about the impact of using AI to craft feedback for your employees, ask them. Use regular pulse surveys, department meetings, and focus groups to understand employee sentiment. Check whether employee recognition messages are landing, how you could improve them, and if your choice of tool is helping or hindering the process.

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Offer Authentic, Meaningful Employee Recognition With Nectar

Handwriting messages of appreciation and delivering them in person to your employees' desks might not be feasible in the fast-paced work environment. But we firmly believe there's still a place for human-crafted praise and recognition to show your employees you notice and value their efforts.

Nectar offers a suite of non-AI tools that allow managers to deliver meaningful messages of appreciation in just a few clicks while still communicating the personal touch your employees crave and deserve.

Here’s how our Recognition tool works:

• Navigate to the Nectar feed, where you'll send meaningful shoutouts to coworkers.
• Tag a recipient and write a personal message of praise to them. 
• Add Nectar points to the message.
• Attach a company core value such as #TeamPlayer or #ExtraMile to the message.
• Hit Give Points.

Once your employees have saved enough points, they can redeem them for a wide selection of Rewards, including Amazon products, gift cards, branded company swag, charity donations, and custom rewards.

Companies using our Recognition tool achieve the following benefits:

• 94% of customers see an increase in employee engagement
• 89% of customers say Nectar helped maintain a healthy remote work culture
• 91% of customers see a boost in employee morale

Want to experience the same results? Book a free Nectar demo today.