WHY MACORVA
This indicates a huge gap between what HR leaders hope to achieve with performance evaluations and the results in terms of employee engagement. AI performance reviews are not a flawless solution to gaps in the performance review process. However, like other uses for this revolutionary technology, AI performance management has distinct advantages over older methods.
Consider these pros and cons of integrating AI performance reviews into your employee engagement strategy and HR process. As with any new workflow, you need to know the benefits of using AI for performance as well as the potential setbacks.
Pro #1: Higher-quality assessments
As managers conduct assessments using conventional methods, they rely on their subjective decision-making. However, human errors are all too common. Recency bias is one way that employee performance can be misjudged. It happens when a manager weighs an employee’s recent actions more heavily than their overall performance.
AI performance management is not subject to human errors. Generative AI can supply objective data that creates the full picture of an employee’s performance, including not only their recent actions but also their broader career progression.
Using AI tools, managers can expedite the evaluations by efficiently identifying data patterns from numerous inputs, including peer feedback, historical performance data, self-evaluations, and L&D outcomes. This leads to more actionable and evidence-based decisions than any manager, no matter how devoted, could generate.
In addition, higher-quality assessments can lead to more personalized career plans for individual employees. With only 32% of employees reporting that they feel engaged at work, the ability to customize each employee’s development based on their performance and career progression gives HR leaders many more ways to put the human element back into their performance feedback.
Pro #2: Real-time insights
Annual performance reviews used to be broad snapshots of employee performance feedback over long periods. Creating actionable strategies from these reviews was taxing. Timely guidance that not only assesses employees but also engages them relies on real-time feedback.
When utilizing AI to write performance reviews, business owners can request feedback anytime. Employees can request it too, expanding the feedback loop and lowering the pressure of the “yearly review time”.
An effective performance review is not a judgment but an open dialogue between an employee and their HR managers. When conducted this way, businesses can assess and improve their employees’ engagement in real time.
Consider that in 2022, the engagement factors that declined the most from the previous polling period were:
- Whether employees understood the expectations placed on them
- Whether they connected to their companies
- Whether they felt they had opportunities to learn and improve
By using AI technology to turn performance reviews into ongoing conversations, businesses can clarify these responsibilities and expectations for each employee. Rather than rely on company-wide initiatives for engagement, businesses can personalize them, which is a key engagement factor in the post-pandemic workforce.
Pro #3: More efficient (and frequent) performance reviews
In addition to collecting and analyzing employee data, generative AI can also consolidate it. One of the benefits of using AI for performance reviews is that it can summarize feedback from multiple sources, including internal platforms like emails, peer reviews, other performance reports, and more.
Generative AI can also write performance reviews based on key insights, saving administrative time. If you’ve ever been stuck for the right word or phrasing when writing a feedback survey, generative AI can do that thinking for you.
AI performance reviews respond to custom criteria, so you can define your employee goals in the surveys, prompt them for your KPIs, and easily edit them until you get a draft that looks perfect. The entire process of putting the review together is easier, which saves your managers time that they can now devote to using the assessments, rather than just making them.
Additionally, employees no longer have to wait for the “review period” to receive feedback reports on their performance. Since they’re easier to make, they can be administered more frequently, allowing managers to use feedback as an opportunity to create an environment of continuous learning.
Pro #4: Fewer inaccuracies
Many employees leave their performance reviews unsure of how to apply them to their jobs. Most think the review was inaccurate or subject to performance bias, which is when moderators pay more or less attention to participants depending on their expectations.
AI performance management irons out these errors and assures employees that the assessment is fair. The AI can pull from more data sources than human moderators, objectively identifying the patterns that form the assessment. It can even offer suggestions for actionable strategies to improve engagement.
Ultimately, your business’s course of action is up to your HR manager. By using AI, they simply have a bigger picture to work with, which improves their ability to tailor the strategy to the engagement you hope to achieve.
Pro #5: Customizable input
AI performance reviews can respond to custom inputs to generate better strategies than automated systems of the past. Consider a scenario where a specific employee could improve on their collaboration skills. This could be posed to generative AI as a custom query, such as:
How can [X employee] improve their collaboration skills? Consider that they were given [this feedback] last year to address this issue.
Your managers will no longer have to implement generalized feedback to all employees as the data concerning each one can be easily itemized with AI. Customized inputs lead to customized outputs with AI performance management. Your employees won’t feel like a passive observer of their own career when you open the performance feedback dialogue with them. They will feel like an active participant.
Uses for AI performance reviews
Performance evaluations generated or aided by AI tools do more than just free up managers’ time. They offer tangible uses that help businesses achieve the intended goal of any performance review: increasing employee engagement. They do this through a combination of custom inputs, multiple feedback sources, and objective insights.
Consider these example uses of AI performance management:
Helping an employee develop a personalized career plan
Employee engagement is on the decline because many employees don’t feel they have opportunities to advance their career path. AI performance reviews customized for each employee based on numerous data sets – including their past reports, their colleagues’ feedback, and even their skill maps – engage employees in their own assessment.
The question could be posed like this:
Analyze [this employee’s] major career achievements from [this list]. Extract the major themes from this list, including hard and soft skills. What skills are most important for the employee to improve to continue developing their career?
Using AI, managers can show workers how they can advance their careers. AI can give them a career projection, help them upskill, and engage them in their learning, a proven way to increase employee retention and satisfaction.
Analyzing data in real time
We’ve established that AI-powered performance reviews can analyze numerous sources and generate insights free from human biases. Its ability to do this in real time with continuous insights is how it helps managers create environments of continuous learning.
Only 21% of employees strongly trust their business leaders, according to Gallup. Yet, this number skyrockets to 95% when managers support three policies: lead changes, clear communication, and inspiration for future prospects.
Real-time data analysis keeps your managers’ finger on the pulse of your workplace community. This is even more significant in a post-pandemic economy, when so many employees are switching to a remote or hybrid work model. With so many employees physically distant from the workplace, managers need ways of fostering continuous learning environments. Continuous real-time data generated by AI performance reviews is one way.
Writing the performance reviews
HR managers can write performance reviews using generative AI. But they don’t have to feel like a “template.” This technology has the capability to produce evaluations that are authentic and original. One of the upsides is that managers no longer have to waste time on specific wording. They can generate the performance review using only the broad insights. For example, you could type,
Focusing on [these traits/skills], write a performance review using a positive tone. Offer alternate vocabulary where applicable to create a personalized review for [this employee].
With the time that managers save on writing the reviews, they can devote more effort to turning the review insights into actionable engagement.
Drawbacks of AI in performance reviews
Like any emerging technology, AI is not without its flaws. Recognizing the limitations of AI technology is crucial for its successful incorporation into your workflow. Reflect on these potential challenges and strategies for mitigating them:
Con #1: Potential for misleading results
Sometimes, AI can generate misleading results, a phenomenon known as “hallucination”. This can happen to AI on a case-by-case basis, often as a result of conflicting inputs. Additionally, AI has the potential to make incorrect inferences from otherwise accurate data, posing a concern for businesses.
This is why Macorva has custom settings that don’t exist on AI programs like ChatGPT. With Macorva, users are able to generate summaries only, receive data citations, and get less “creative” answers. Additionally, we perform a final AI legal risk analysis on your finished insights to minimize the possibility of errors.
No matter the AI your business adopts, your managers need to know that generated responses are not infallible. Treat the AI’s results as a first draft, and remember to always review and approve documents before finalizing them.
Con #2: Learning curve
There’s also a potential learning curve with AI. For example, your manager may not review the first draft created by the AI before submitting it. Additionally, the AI may respond with an error or require differently worded inputs to produce a useful result. In many cases, business teams struggle with adopting AI due to this learning curve.
Macorva streamlines AI adoption for business teams by embedding intuitive and straightforward features directly into our platform. We’ve equipped our built-in performance review workflow with detailed instructions, making critical information readily accessible to all team members. A crucial component of our approach is the mandatory step-by-step approval process for managers, ensuring every personal review is completed. This not only facilitates a smoother transition but also emphasizes our commitment to maintaining the accuracy and integrity of the reviews through required managerial oversight and approval.
But remember that AI can never completely eliminate human error from your performance review process. It can improve the efficiency and effectiveness of human insights, but your managers still need to know that these programs have limitations.
While your business must commit to adopting AI systems, it must also commit to additional technical training and education to ensure that your teams use them effectively. Macorva facilitates this shift through its AI performance management tools, which are designed to be both user-friendly and adaptable, aligning with your organization's quality assurance requirements.
Con #3: Security concerns
Many business executives fear the possibility that AI systems are insecure. On their own, they can be. Everything you input into an AI is saved by default and used as training data to improve the system. This means that potentially vital company and personal employee data is stored by these systems, posing a potential security risk.
Depending on the industry, AI tools also have legal, ethical, and practical restrictions that will prevent some businesses from using them. For example, the images generated by AI can have a complex legal status that changes depending on the AI you use.
This is why Macorva uses enterprise-grade APIs with built-in security features that don’t exist on the AI by default. Additionally, using Macorva’s tools, your inputs will be deleted after submission instead of being submitted as training data. This helps protect your managers and employees from having their data saved and exploited by a system out of your control.
The takeaway for businesses
AI performance reviews undoubtedly have the potential to fill major gaps in traditional review methods. When used correctly, they can personalize data outputs and engage employees in their career progression through a performance review process that more resembles a dialogue than a critique. They can make the entire review process more efficient while enhancing your managers’ ability to turn feedback into an opportunity for continuous learning.
However, despite the benefits of using AI for performance, a human element is still vital to the success of your performance feedback process. Macorva enhances AI productivity with added safeguards, custom priorities, and security features to ensure that you get the most out of your reformed performance reviews. But more than that, our performance management tools ensure that your automated responses will enhance your employees’ engagement with their company’s brand, their managers, and their own careers. The AI’s responses may be automated, but its applications must always remain human.
To see Macorva’s AI performance management solution in action, watch this demo.
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