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Quest Training

Conversational AI & Enterprise Chatbots Training Course

Covers designing and managing enterprise chatbots, from dialogue design and knowledge integration to rule-based, intent-based and generative AI assistants.

AIEA · Artificial Intelligence & Enterprise ApplicationsAll Levels#2740ClassroomEnglish , Arabic
Duration
5 Days
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Free substitution at any time · 30+ days' notice: full refund minus 10%. Cancellation policy

Sectors:Data, Analytics & Digital TransformationCategories:Artificial Intelligence & Enterprise Applications

Course Overview

This course equips participants with the practical skills to design, develop, and manage conversational AI solutions and enterprise chatbots that improve customer service, employee support, and business process efficiency. It explores natural language processing, large language models, dialogue design, knowledge integration, and intelligent automation to help organizations deliver responsive, consistent, and context-aware digital interactions. Participants learn how to define chatbot use cases, design conversational workflows, connect AI assistants to enterprise systems, and evaluate performance against business objectives. The programme also covers data security, governance, responsible AI, integration strategies, and continuous improvement, enabling organizations to deploy scalable conversational solutions aligned with operational requirements.

Learning Objectives

  • By the end of the course, participants will be able to:
  • Explain the principles and business applications of conversational AI and enterprise chatbots.
  • Differentiate between rule-based chatbots, intent-based virtual assistants, and generative AI assistants.
  • Identify suitable chatbot use cases across customer service, human resources, IT support, and business operations.
  • Design conversational flows, dialogue structures, intents, entities, and fallback mechanisms.
  • Apply natural language processing and large language model concepts to conversational solutions.
  • Integrate enterprise knowledge sources and business systems into chatbot workflows.
  • Design chatbot architectures that support scalability, availability, security, and maintainability.
  • Establish controls for data privacy, access management, responsible AI, and information protection.
  • Define performance indicators to measure chatbot accuracy, user satisfaction, adoption, and business impact.
  • Develop an implementation and optimization plan for enterprise conversational AI solutions.

Who Should Attend

This course is designed for AI specialists, software developers, chatbot designers, data professionals, business analysts, solution architects, and IT managers involved in developing, integrating, or managing conversational AI solutions. It is particularly relevant to professionals seeking to automate routine interactions, improve digital service delivery, streamline internal support, and enhance access to organizational information. The programme is also suitable for customer experience managers, digital transformation leaders, human resources professionals, service desk managers, innovation teams, and business process owners in government entities, ministries, banks, financial institutions, oil and gas companies, industrial organizations, and large corporations. Basic familiarity with business processes, digital platforms, or information systems is beneficial, although advanced programming experience is not required for all course activities.

Learning Outcomes

  • Evaluate conversational AI technologies and select suitable approaches for different business requirements.
  • Define chatbot objectives, target users, functional scope, and measurable success criteria.
  • Map user journeys and design effective dialogue flows for common and complex interactions.
  • Configure intents, entities, response patterns, fallback handling, and escalation to human agents.
  • Apply natural language processing and large language model concepts when designing conversational experiences.
  • Connect chatbots to enterprise knowledge bases, databases, APIs, and business applications.
  • Apply retrieval-augmented generation (RAG) concepts to improve responses using approved organizational information.
  • Identify security, privacy, reliability, and responsible AI requirements for enterprise deployments.
  • Evaluate chatbot performance using analytical measures, user feedback, and operational indicators.
  • Prepare a deployment roadmap covering testing, integration, user adoption, monitoring, and continuous improvement.

Course Outline

Day 1

Conversational AI Fundamentals and Enterprise Use Cases

  • Understanding conversational AI, virtual assistants, and enterprise chatbot architectures.
  • Exploring natural language processing, intent recognition, entity extraction, and dialogue management.
  • Comparing rule-based, intent-driven, retrieval-based, and generative AI chatbot approaches.
  • Understanding the capabilities and limitations of large language models in conversational applications.
  • Identifying enterprise use cases in customer service, HR support, IT service desks, procurement, and internal knowledge access.
  • Mapping business requirements to chatbot capabilities and expected operational benefits.
  • Assessing user needs, conversation complexity, data availability, and integration dependencies.
  • Establishing objectives, scope, user groups, and success criteria for chatbot initiatives.
  • Practical Exercise: Develop a chatbot use case proposal for a selected business function, defining its users, objectives, expected benefits, and functional requirements.
Day 2

Conversation Design, Natural Language Understanding, and User Experience

  • Designing user journeys and conversational experiences around business tasks.
  • Developing dialogue flows, conversation states, prompts, and response structures.
  • Defining intents, entities, sample utterances, and confidence thresholds.
  • Handling ambiguous requests, incomplete information, misunderstandings, and unexpected inputs.
  • Designing clarification questions, fallback responses, and escalation to human agents.
  • Applying tone, language, accessibility, and usability principles to chatbot interactions.
  • Developing conversational scenarios for frequently asked questions and multi-step processes.
  • Testing conversation paths for consistency, clarity, accuracy, and user satisfaction.
  • Practical Exercise: Design a complete conversational flow for an enterprise chatbot, including common requests, clarification paths, error handling, and human escalation.
Day 3

Generative AI, Enterprise Knowledge Integration, and System Connectivity

  • Understanding how large language models support conversational applications.
  • Designing prompts, instructions, context management, and response constraints.
  • Exploring retrieval-augmented generation (RAG) for accessing approved enterprise knowledge.
  • Preparing knowledge sources, documents, metadata, and retrieval strategies for chatbot use.
  • Connecting conversational interfaces to databases, APIs, enterprise applications, and workflow systems.
  • Understanding authentication, authorization, and secure access to enterprise information.
  • Managing conversation context, session state, and multi-turn interactions.
  • Reducing unsupported responses through grounding, source retrieval, validation, and controlled response generation.
  • Practical Exercise: Design a knowledge-enabled enterprise chatbot that retrieves approved information and connects to a selected business system or service workflow.
Day 4

Enterprise Architecture, Security, Governance, and Quality Assurance

  • Designing chatbot architecture components, including interfaces, orchestration, models, knowledge sources, and integrations.
  • Evaluating deployment options, scalability, availability, monitoring, and maintainability.
  • Applying data protection, access control, encryption, and secure integration principles.
  • Addressing confidential information, sensitive data, retention, and privacy requirements.
  • Establishing governance policies for content, model usage, approved knowledge, and operational accountability.
  • Evaluating hallucinations, bias, prompt injection, unauthorized disclosure, and other conversational AI risks.
  • Developing testing strategies for functional accuracy, retrieval quality, security, robustness, and performance.
  • Establishing human oversight, incident handling, audit trails, and escalation procedures.
  • Practical Exercise: Conduct a risk and quality review of a proposed enterprise chatbot architecture and develop controls for security, accuracy, privacy, and operational reliability.
Day 5

Deployment, Performance Measurement, and Continuous Improvement

  • Planning chatbot development, pilot implementation, production deployment, and organizational rollout.
  • Defining responsibilities across business owners, IT teams, data teams, security specialists, and service managers.
  • Establishing performance indicators for response accuracy, resolution rate, containment rate, response time, user satisfaction, and cost efficiency.
  • Analyzing conversation logs, user feedback, unsuccessful interactions, and escalation patterns.
  • Improving knowledge coverage, dialogue design, retrieval quality, and response consistency.
  • Managing model updates, knowledge refreshes, regression testing, and ongoing quality monitoring.
  • Evaluating business value through productivity gains, service improvements, reduced handling time, and better information accessibility.
  • Developing adoption plans, user guidance, operational procedures, and continuous improvement cycles.
  • Final Workshop: Develop and present an enterprise conversational AI implementation plan covering use cases, conversation design, architecture, knowledge integration, security controls, testing, deployment, performance indicators, and expected business value.

Upcoming Dates

Selected date

Abuja · 15 – 19 Feb 2027 · Classroom

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Kuala LumpurScheduled
2 – 6 Nov 2026€4,400—
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LisbonScheduled
9 – 13 Nov 2026€5,400—
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LondonScheduled
16 – 20 Nov 2026€5,600—
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MadinahScheduled
23 – 27 Nov 2026€4,200€3,780until 2 Nov
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MadridScheduled
30 Nov – 4 Dec 2026€5,400€4,860until 9 Nov
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ManamaScheduled
7 – 11 Dec 2026€4,700€4,230until 16 Nov
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MarbellaScheduled
14 – 18 Dec 2026€5,400€4,860until 23 Nov
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MarrakeshScheduled
14 – 18 Dec 2026€4,300€3,870until 23 Nov
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MilanScheduled
21 – 25 Dec 2026€6,000€5,400until 30 Nov
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MuscatScheduled
28 Dec 2026 – 1 Jan 2027€5,300€4,770until 7 Dec
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OnlineScheduled
3 – 7 Jan 2027€1,700€1,530until 14 Dec
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ParisScheduled
11 – 15 Jan 2027€5,700€5,130until 21 Dec
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RiyadhScheduled
18 – 22 Jan 2027€4,200€3,780until 28 Dec
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RomeScheduled
25 – 29 Jan 2027€5,800€5,220until 4 Jan
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SalalahScheduled
25 – 29 Jan 2027€5,300€4,770until 4 Jan
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Sharm El-SheikhScheduled
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ViennaScheduled
8 – 12 Feb 2027€5,700€5,130until 18 Jan
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AbujaScheduled
15 – 19 Feb 2027€5,100€4,590until 25 Jan
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AccraScheduled
22 – 26 Feb 2027€5,100€4,590until 1 Feb
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AmsterdamScheduled
1 – 5 Mar 2027€5,400€4,860until 8 Feb
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BarcelonaScheduled
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CairoScheduled
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CasablancaScheduled
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DohaScheduled
22 – 26 Mar 2027€4,400€3,960until 1 Mar
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DubaiScheduled
28 Mar – 1 Apr 2027€4,400€3,960until 8 Mar
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GenevaScheduled
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12 – 16 Apr 2027€5,800€5,220until 22 Mar
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