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Surabhi Rohankar

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✨ Innovation Project

Designing an HR Chatbot for Seamless Employee Support

We designed a conversational AI assistant to centralize HR support enabling employees to quickly find information, resolve queries, and route requests appropriately, while reducing routine workload for HR teams.

Company

Encora

Domain

Conversation Design

Timeline

2022

Role

UX Designer

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Overview

We set out to explore conversation design as a discipline and identify a meaningful use case where it could add real value. Through early research and internal discussions, we arrived at an AI-powered HR chatbot using conversation design principles to shape intent, tone, and dialogue flows that help employees find information, resolve queries, and reach the right support efficiently.

Objectives

Build a foundational understanding of conversation design as an emerging UX discipline, including intents, dialogue structure, tone, and failure handling.

Design an HR chatbot that could answer common employee queries, guide users to relevant resources, and escalate to human support when needed.

Define the bot’s personality, capabilities, limitations, and conversational patterns to ensure clarity, trust, and usability.

Discovery

Desk Research

We began by exploring industry trends and best practices in conversational AI for enterprise HR. Our research focused on understanding what makes chatbots successful in similar contexts.
53%

of companies who identify AI as a tool for 'Customer-first Culture' (CX Network).

86%

of customers believe there should be an escalate to agent option when talking to chatbot (Aspect Customer Index)

90%

of businesses reporting faster complaint resolution with bots (MIT Technology review)

Discovery

User Research Insights

We conducted interviews with both HR team members and employees to understand pain points from both sides.

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HR TEAM

"I spend most of my day answering the same questions."

  • Spending 60%+ of time on repetitive queries

  • Difficulty tracking request status across channels

  • Limited time for strategic HR activities.

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EMPLOYEES

"I never know where to find answers or who to ask"

  • Long wait times for simple questions

  • No visibility into ticket progress.

  • Unclear who to contact for specific issues

Define

Card Sort Activity

We conducted a card sort activity with stakeholders like HRs, employees and Product Manager to identify and prioritize tasks that would benefit most from a chatbot solution.
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Design Approach

A systematic approach to crafting meaningful bot-human interactions, from intent mapping to final interface designs

  • Defined chatbot personality as Friendly, professional and efficient.

  • Mapped user intents to appropriate responses across conversation flows

  • Designed fallback behaviors and escalation triggers

  • Created empathetic language patterns.

View Bot Personality

View Intent Mapping

View Conversation Design

View Flow Diagram

DESIGN PROCESS

Design Approach

A systematic approach to crafting meaningful bot-human interactions

Tone & Voice Definition

We defined the bot’s personality to be:

  • Helpful, neutral, and professional

  • Clear and concise, without sounding robotic

  • Transparent about limitations

Behavior & Boundaries
We documented what the bot could do, how it should respond when uncertain, and what it should explicitly avoid saying to maintain trust and accuracy.

Dialogue Design

We wrote sample conversations to define how the chatbot would behave across scenarios:

  • Introduction and onboarding messages

  • Successful query resolution

  • Error handling and unclear input

  • Escalation to human support

This helped ensure consistency in tone and prevented edge cases from feeling abrupt or confusing.

Flow Design & Interface Exploration

Based on identified intents, we created a high-level conversation flow and explored UI screens.

  • Entry points and guided prompts

  • Clarification questions

  • Guided responses alongside free-text input

  • Clear visual hierarchy within chat messages

  • Smooth transitions between automated responses and human handoff

This flow served as the foundation for both AI logic and UI design.

Bot Task flow

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UI Explorations

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Chatbot in Action

Chatbot Demo Video

Imapact & Outcomes

Where Design Made a Difference

Faster Resolution

Average query resolution time would be reduced from hours to minutes for common requests.

Reduced HR load

There would be significant decrease in repetitive queries reaching the HR team.

Employee satisfaction

24/7 availability and instant responses will improve overall employee experience.

Scalable Framework

The conversational framework allows new features, intents, and workflows to be added over time. As AI capabilities evolve, the system can progressively leverage smarter automation and more advanced interactions.

There’s more behind this work, reach out if you’d like to dive deeper.

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