Who Should Attend &
Course FAQs

No. No previous agentic AI, AI development, programming, data science, or technical experience is required.

The course establishes a shared foundation by defining AI agents precisely, explaining the core components of agent architecture, introducing autonomy concepts, and providing structured frameworks for discovering and evaluating agent opportunities.

Experienced business, technology, process, and AI professionals also benefit by gaining a disciplined enterprise methodology for moving from possible AI use cases to qualified, prioritized agent opportunities.

An AI agent can perceive information, reason about it, plan actions, take authorized actions, and use memory or context to pursue delegated objectives with an appropriate degree of autonomy.

The course distinguishes AI agents from related technologies and establishes the vocabulary needed to discuss agentic systems accurately, including:

• Traditional workflow automation
• Robotic Process Automation (RPA)
• Conventional AI and machine learning
• AI copilots
• AI agents and agentic workflows
• Autonomy, delegated authority, guardrails, escalation, orchestration, and memory

This shared vocabulary is important because organizations cannot consistently evaluate agent opportunities until business and technology teams are aligned on what an AI agent actually is.

Participants use five analytical discovery lenses to systematically examine business processes for agentic potential.

• Cognitive Task Analysis: Identifies work involving reasoning, judgment, interpretation, and decision-making.
• Decision Authority Mapping: Examines who or what is authorized to make decisions and where authority might appropriately be delegated.
• Information Flow Analysis: Identifies the information required to perform work and make decisions.
• Tool and System Interaction Analysis: Examines the applications, systems, and tools required to complete work.
• Waste and Friction Analysis: Surfaces delays, handoffs, queues, rework, coordination costs, and other sources of process friction.

Together, these lenses reveal opportunities that conventional automation analysis can overlook, particularly work that is judgment-intensive, information-dependent, and potentially delegable.

The course uses a structured opportunity assessment framework rather than relying on enthusiasm for a technology or isolated AI use cases.

Candidate opportunities are evaluated across four weighted dimensions:

• Business Value
• Technical Feasibility
• Risk Tolerance
• Organizational Readiness

Participants learn to translate these assessments into composite scores and value-feasibility portfolio views that make opportunities easier to compare.

The resulting portfolio can then be sequenced into a realistic deployment roadmap based on value, feasibility, dependencies, readiness, and risk.

Participants learn a five-tier taxonomy for classifying how much authority should remain with people and how much can appropriately be delegated to an AI agent.

• Fully Autonomous: The agent performs the task within established authority and guardrails.
• Human-on-the-Loop: The agent acts while people supervise and can intervene when needed.
• Human-in-the-Loop: Human review, approval, or intervention is incorporated into the work.
• Human-Initiated: A person initiates or directs the agent's activity.
• Human-Only: The work remains with people because delegation is inappropriate.

The course also addresses stakeholder validation and phased autonomy evolution so organizations do not assume that every viable agent opportunity should immediately operate at maximum autonomy.

Agent value stream mapping adapts established value stream analysis techniques to visualize how AI agents could change an end-to-end business process.

Participants learn to incorporate:

• Agent opportunity overlays
• Autonomy tier annotations
• Queue elimination modeling
• Bottleneck migration analysis
• Current-state to future-state economic impact analysis

This allows organizations to evaluate potential agent initiatives in the context of the entire process rather than optimizing an isolated task while unintentionally shifting delays or constraints somewhere else.

You will be able to apply a disciplined, repeatable methodology for discovering, assessing, prioritizing, and sequencing potential AI agent opportunities across enterprise business processes.

• Define AI agents and distinguish them from related automation and AI technologies
• Understand the five core components of agent architecture
• Apply the five discovery lenses to business processes
• Identify judgment-intensive and potentially delegable work
• Assess candidate opportunities across value, feasibility, risk, and readiness
• Classify tasks by appropriate levels of autonomy
• Use agent value stream mapping to visualize process and economic impact
• Compare opportunities using structured scoring and portfolio analysis
• Sequence qualified opportunities into deployment roadmaps
• Recognize common discovery anti-patterns before they undermine an AI initiative

Discovering Agentic AI Opportunities focuses on the front end of the agentic AI lifecycle: determining where AI agents should be considered and which opportunities warrant further investment.

It complements Inteq's business analysis, process analysis, process transformation, and data modeling courses by applying those enterprise disciplines to the discovery and evaluation of agentic AI opportunities.

This course is also the prerequisite to Inteq's Analyzing & Specifying AI Agent Business Requirements course, which moves qualified opportunities into the detailed requirements and specification work needed for agent design and implementation.

The course includes professional development credentials, completion recognition, and the frameworks and resources used throughout the program.

• 1.4 CEUs
• 14 IIBA PDUs or CDUs
• Personalized Discovering Agentic AI Opportunities digital badge
• Certificate of completion
• Comprehensive course materials
• Frameworks, assessment techniques, classification methods, and templates used throughout the course

Inteq is an IIBA Endorsed Education Provider.

Live Team Training is available now, and the self-paced Anytime eLearning™ version is coming soon.

Team Training: Live onsite or virtual training for enterprise teams, with delivery aligned to your organization's objectives, participants, and business context. Contact Inteq for Team Training scope and pricing.

Anytime eLearning™: The self-paced version is currently in development. Individuals can request notification when enrollment becomes available.

Government purchasing: Inteq is an approved GSA prime contractor, and Inteq training and consulting are available to U.S. Government organizations through applicable GSA Professional Services Schedule offerings.