Workforce Engagement Management

Hi everyone,

I wanted to share two related ideas I submitted around making Quality Evaluations and AI Scoring more actionable, transparent, and useful for agent development.

The first idea is about adding an AI-generated feedback summary field to Quality Evaluation Forms.

After an evaluation is completed, Genesys Cloud could use AI to generate a clear and structured feedback summary based on the answers, scores, comments, and failed criteria in the form. The evaluator would still remain in control, reviewing, editing, and approving the AI-generated feedback before submitting or sharing it with the agent.

This could help reduce manual effort, improve consistency in coaching comments, and make evaluations easier for agents to understand.

Idea link:
https://genesyscloud.ideas.aha.io/ideas/WEQUAL-I-515

The second idea is about allowing agents to view and dispute fully automated evaluations.

Today, when assignment, response, and finalization happen automatically, agents do not have the same visibility into the completed evaluation form, and there is no dispute or contestation workflow available.

In my opinion, this creates an important gap. Fully automated evaluations are extremely valuable for scale, but agents still need transparency into what was scored, what improvement opportunities were identified, and a way to challenge the result when there may be a misunderstanding or interpretation difference.

Idea link:
https://genesyscloud.ideas.aha.io/ideas/WEVS-I-6

Together, I believe these two improvements would help connect AI Scoring, Quality Management, Coaching, and Agent Development in a stronger way.

AI can help scale evaluations, but the process also needs to remain transparent, actionable, and trusted by agents and supervisors.

If these topics are relevant to your operation too, I'd really appreciate your votes and comments on the ideas.

Curious to hear how other teams are currently handling automated evaluations, agent visibility, disputes, and coaching feedback.

Hi everyone,

I wanted to share two related ideas I submitted around making Quality Evaluations and AI Scoring more actionable, transparent, and useful for agent development.

The first idea is about adding an AI-generated feedback summary field to Quality Evaluation Forms.

After an evaluation is completed, Genesys Cloud could use AI to generate a clear and structured feedback summary based on the answers, scores, comments, and failed criteria in the form. The evaluator would still remain in control, reviewing, editing, and approving the AI-generated feedback before submitting or sharing it with the agent.

This could help reduce manual effort, improve consistency in coaching comments, and make evaluations easier for agents to understand.

Idea link:
https://genesyscloud.ideas.aha.io/ideas/WEQUAL-I-515

The second idea is about allowing agents to view and dispute fully automated evaluations.

Today, when assignment, response, and finalization happen automatically, agents do not have the same visibility into the completed evaluation form, and there is no dispute or contestation workflow available.

In my opinion, this creates an important gap. Fully automated evaluations are extremely valuable for scale, but agents still need transparency into what was scored, what improvement opportunities were identified, and a way to challenge the result when there may be a misunderstanding or interpretation difference.

Idea link:
https://genesyscloud.ideas.aha.io/ideas/WEVS-I-6

Together, I believe these two improvements would help connect AI Scoring, Quality Management, Coaching, and Agent Development in a stronger way.

AI can help scale evaluations, but the process also needs to remain transparent, actionable, and trusted by agents and supervisors.

If these topics are relevant to your operation too, I'd really appreciate your votes and comments on the ideas.

Curious to hear how other teams are currently handling automated evaluations, agent visibility, disputes, and coaching feedback.

Hi everyone,

I wanted to share two related ideas I submitted around making Quality Evaluations and AI Scoring more actionable, transparent, and useful for agent development.

The first idea is about adding an AI-generated feedback summary field to Quality Evaluation Forms.

After an evaluation is completed, Genesys Cloud could use AI to generate a clear and structured feedback summary based on the answers, scores, comments, and failed criteria in the form. The evaluator would still remain in control, reviewing, editing, and approving the AI-generated feedback before submitting or sharing it with the agent.

This could help reduce manual effort, improve consistency in coaching comments, and make evaluations easier for agents to understand.

Idea link:
https://genesyscloud.ideas.aha.io/ideas/WEQUAL-I-515

The second idea is about allowing agents to view and dispute fully automated evaluations.

Today, when assignment, response, and finalization happen automatically, agents do not have the same visibility into the completed evaluation form, and there is no dispute or contestation workflow available.

In my opinion, this creates an important gap. Fully automated evaluations are extremely valuable for scale, but agents still need transparency into what was scored, what improvement opportunities were identified, and a way to challenge the result when there may be a misunderstanding or interpretation difference.

Idea link:
https://genesyscloud.ideas.aha.io/ideas/WEVS-I-6

Together, I believe these two improvements would help connect AI Scoring, Quality Management, Coaching, and Agent Development in a stronger way.

AI can help scale evaluations, but the process also needs to remain transparent, actionable, and trusted by agents and supervisors.

If these topics are relevant to your operation too, I'd really appreciate your votes and comments on the ideas.

Curious to hear how other teams are currently handling automated evaluations, agent visibility, disputes, and coaching feedback.

Hi everyone,

I wanted to share two related ideas I submitted around making Quality Evaluations and AI Scoring more actionable, transparent, and useful for agent development.

The first idea is about adding an AI-generated feedback summary field to Quality Evaluation Forms.

After an evaluation is completed, Genesys Cloud could use AI to generate a clear and structured feedback summary based on the answers, scores, comments, and failed criteria in the form. The evaluator would still remain in control, reviewing, editing, and approving the AI-generated feedback before submitting or sharing it with the agent.

This could help reduce manual effort, improve consistency in coaching comments, and make evaluations easier for agents to understand.

Idea link:
https://genesyscloud.ideas.aha.io/ideas/WEQUAL-I-515

The second idea is about allowing agents to view and dispute fully automated evaluations.

Today, when assignment, response, and finalization happen automatically, agents do not have the same visibility into the completed evaluation form, and there is no dispute or contestation workflow available.

In my opinion, this creates an important gap. Fully automated evaluations are extremely valuable for scale, but agents still need transparency into what was scored, what improvement opportunities were identified, and a way to challenge the result when there may be a misunderstanding or interpretation difference.

Idea link:
https://genesyscloud.ideas.aha.io/ideas/WEVS-I-6

Together, I believe these two improvements would help connect AI Scoring, Quality Management, Coaching, and Agent Development in a stronger way.

AI can help scale evaluations, but the process also needs to remain transparent, actionable, and trusted by agents and supervisors.

If these topics are relevant to your operation too, I'd really appreciate your votes and comments on the ideas.

Curious to hear how other teams are currently handling automated evaluations, agent visibility, disputes, and coaching feedback.

Hi everyone,

I wanted to share two related ideas I submitted around making Quality Evaluations and AI Scoring more actionable, transparent, and useful for agent development.

The first idea is about adding an AI-generated feedback summary field to Quality Evaluation Forms.

After an evaluation is completed, Genesys Cloud could use AI to generate a clear and structured feedback summary based on the answers, scores, comments, and failed criteria in the form. The evaluator would still remain in control, reviewing, editing, and approving the AI-generated feedback before submitting or sharing it with the agent.

This could help reduce manual effort, improve consistency in coaching comments, and make evaluations easier for agents to understand.

Idea link:
https://genesyscloud.ideas.aha.io/ideas/WEQUAL-I-515

The second idea is about allowing agents to view and dispute fully automated evaluations.

Today, when assignment, response, and finalization happen automatically, agents do not have the same visibility into the completed evaluation form, and there is no dispute or contestation workflow available.

In my opinion, this creates an important gap. Fully automated evaluations are extremely valuable for scale, but agents still need transparency into what was scored, what improvement opportunities were identified, and a way to challenge the result when there may be a misunderstanding or interpretation difference.

Idea link:
https://genesyscloud.ideas.aha.io/ideas/WEVS-I-6

Together, I believe these two improvements would help connect AI Scoring, Quality Management, Coaching, and Agent Development in a stronger way.

AI can help scale evaluations, but the process also needs to remain transparent, actionable, and trusted by agents and supervisors.

If these topics are relevant to your operation too, I'd really appreciate your votes and comments on the ideas.

Curious to hear how other teams are currently handling automated evaluations, agent visibility, disputes, and coaching feedback.

Hi everyone,

I wanted to share two related ideas I submitted around making Quality Evaluations and AI Scoring more actionable, transparent, and useful for agent development.

The first idea is about adding an AI-generated feedback summary field to Quality Evaluation Forms.

After an evaluation is completed, Genesys Cloud could use AI to generate a clear and structured feedback summary based on the answers, scores, comments, and failed criteria in the form. The evaluator would still remain in control, reviewing, editing, and approving the AI-generated feedback before submitting or sharing it with the agent.

This could help reduce manual effort, improve consistency in coaching comments, and make evaluations easier for agents to understand.

Idea link:
https://genesyscloud.ideas.aha.io/ideas/WEQUAL-I-515

The second idea is about allowing agents to view and dispute fully automated evaluations.

Today, when assignment, response, and finalization happen automatically, agents do not have the same visibility into the completed evaluation form, and there is no dispute or contestation workflow available.

In my opinion, this creates an important gap. Fully automated evaluations are extremely valuable for scale, but agents still need transparency into what was scored, what improvement opportunities were identified, and a way to challenge the result when there may be a misunderstanding or interpretation difference.

Idea link:
https://genesyscloud.ideas.aha.io/ideas/WEVS-I-6

Together, I believe these two improvements would help connect AI Scoring, Quality Management, Coaching, and Agent Development in a stronger way.

AI can help scale evaluations, but the process also needs to remain transparent, actionable, and trusted by agents and supervisors.

If these topics are relevant to your operation too, I'd really appreciate your votes and comments on the ideas.

Curious to hear how other teams are currently handling automated evaluations, agent visibility, disputes, and coaching feedback.