Pm ppt

1. Presented by
Ritika Singhal
Ritika Uppal
Ruchita Shulka
Sakshi Prasad
Sanjana Singh
Ananya Dwivedi
Anushree Jaiswal
Role of AI in Performance Management
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3. How AI can make work easier and more effective
for both employees and managers.
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4. Instant Feedback
Performance
Predictions
Goal Setting and
Tracking
360-Degree
Feedback Analysis
Identification of
High Performers
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5. HOWAI CAN PREDICT FUTURE PERFORMANCE TRENDS AND
HELPS IN DECISION MAKING.
• Identifying high-potential employees: AI can analyze historical data on
employee performance, such as past performance reviews, sales figures, and
customer satisfaction scores, to identify employees who are likely to be high
performers in the future.
• Predicting employee turnover: AI can also be used to predict employee
turnover, which can help HR departments to proactively address any potential
problems.
• Forecasting future workforce needs: AI can be used to forecast future
workforce needs, which can help HR departments to plan for hiring, training,
and development.
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6. AI can also help HR departments to make more informed decisions in a
number of other ways. For example,
Analyze employee feedback: AI can analyze employee feedback from
surveys, performance reviews, and other sources to identify trends and
patterns. This information can be used to improve employee engagement,
morale, and productivity.
Identify and address bias: AI can help to identify and address bias in HR
processes, such as hiring, promotion, and compensation. This can help to
create a more fair and equitable workplace.
Automate tasks: AI can be used to automate repetitive tasks, such as
screening resumes, scheduling interviews, and onboarding new employees.
This can free up HR professionals to focus on more strategic tasks.
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7. • HowAI Can Provide Personlized Feedback & Growth opportunities for
employees :-
 Performance Analysis
 Feedback Generation
 Learning Recommendations
 Skill Gap Identification
 Goal Setting
 Mentorship Matching
Its important to use AI in employee feedback and development ethically, ensuring
transparency, privacy, and fairness. Employees should have control over their data and the
ability to provide input into the AI-driven feedback and growth processes to ensure a
balanced approach to personalization.
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10. AI in Performance Management- Key
Applications
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11. AI-Powered Tools and Technologies used in
performance management.
 Performance Analytics Dashboards:
 Tool Examples: Tableau, Power BI, IBM Cognos Analytics
 These tools use AI and machine learning algorithms to analyze performance data, providing
interactive dashboards with real-time insights.
 Dashboards display key performance indicators (KPIs), trends, and predictions, allowing
organizations to make data-driven decisions about employee performance.
 Chatbots for Feedback:
 Tool Examples: TINYpulse, 15Five, Glint
 AI-driven chatbots collect feedback from employees through regular surveys or conversations.
 They use natural language processing (NLP) to understand and categorize feedback, offering
actionable insights to HR and managers
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12. Cont.-
 Machine Learning for Goal Setting:
 Tool Examples: BetterWorks, 7Geese, Workboard
 Machine learning algorithms help organizations set SMART (Specific, Measurable, Achievable,
Relevant, Time-bound) goals for employees.
 These tools also track progress and provide recommendations for adjusting goals based on
performance data.
 Predictive Analytics Tools:
 Tool Examples: Visier, Oracle HCM Cloud, SAP SuccessFactors
 Predictive analytics in HR uses AI to forecast employee performance trends, turnover rates, and
talent gaps.
 By identifying potential issues early, organizations can take proactive measures to optimize
performance and retention.
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13. Challenges in Implementing AI for
Performance Management
Data quality and bias: AI systems are trained on data, so it is essential to have high-quality,
unbiased data to ensure accurate results. However, many organizations struggle to collect and
manage such data.
Explainability and transparency: AI systems can be complex and difficult to understand,
making it challenging to explain how they make decisions. This can lead to a lack of trust and
resistance from employees.
Change management: Implementing AI in performance management requires a significant
culture change. Organizations need to prepare employees for the new system and train them on
how to use it effectively.
Cost and expertise: AI systems can be expensive to develop and deploy. Additionally, they
require expertise in AI and machine learning. This can be a challenge for smaller organizations or
those with limited resources.
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14. Conclusion
In conclusion, the integration of AI into performance management holds great
promise for organizations seeking to optimize their workforce's potential. AI not
only streamlines processes but also empowers employees with personalized
feedback and growth pathways. It's a powerful tool for tracking KPIs and
predicting future performance trends, aiding informed decision-making.
However, as AI takes on a more significant role, addressing ethical concerns such
as data privacy and bias becomes paramount. Striking the right balance between
technological innovation and ethical considerations is key to realizing the full
benefits of AI in performance management.
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