Training Course
AI Agents and Enterprise Process Automation
Course Duration: One Week (20 Training Hours)
Introduction
Organizations today are moving beyond using
artificial intelligence as a support tool for answering questions and
generating text, toward AI agents: systems capable of understanding objectives,
planning steps, utilizing enterprise systems and tools, and executing complete
tasks end-to-end under defined human oversight. Gartner predicts that 40% of
enterprise applications will integrate task-specific AI agents by the end of
2026, up from less than 5% in 2025, and that at least 15% of day-to-day work
decisions will be made autonomously through these agents by 2028, up from 0% in
2024.
However, the picture is not entirely
promising. According to Gartner's 2026 CIO and Technology Executive Survey,
only 17% of organizations have actually deployed AI agents, even though more
than 60% expect to deploy them within two years — the widest gap between
ambition and reality Gartner has recorded across all emerging technologies.
More critically, Gartner predicts that over 40% of agentic AI projects will be
canceled by the end of 2027, due to escalating costs, unclear business value,
or inadequate risk controls. Gartner has also estimated that only approximately
130 vendors among the thousands claiming to offer this technology actually
deliver genuine agents, while the rest amount to little more than the
rebranding of chatbots and traditional automation tools under a new label.
These figures are directly relevant to public
and private sector entities operating under ambitious digital transformation
plans with clear performance indicators for service digitization and
stakeholder experience improvement. Such entities handle large volumes of
transactions, correspondence, and recurring requests, operate in both Arabic
and English, and are subject to strict national requirements for personal data
protection, cybersecurity, data classification, and local data hosting. They
therefore stand to benefit most from AI agents, and are equally the most
exposed to their risks if deployed without governance.
The recurring practical problem across many
organizations is that AI projects start from the technology rather than from
the problem: an impressive initial proof of concept is presented to management,
only to stall when it comes to integrating with existing systems, addressing
access permissions and data security, or demonstrating measurable return on
investment. The result is pilot projects that never progress to production,
tools that are purchased but never used, or agents that operate without
sufficient oversight of the actions they take. This course has been designed to
bridge precisely this gap, with practical deliverables that take participants
from fascination with the technology to the ability to select the right
processes, design the agent, govern it, and measure its impact.
Why the
AI Agents and Enterprise Process Automation Course at The Only Solution for
Training and Consulting?
In a field evolving at this pace, it is not
enough for participants to learn about the latest tools. What organizations
truly need is a team that returns from the course able to identify where an AI
agent creates real value, and how to build it, govern it, and measure it. The
course has been designed on this basis:
1.
Participants leave with working documents, not notes
Each day of the course concludes with a
practical deliverable built by the participants themselves: a process map of
their organization classified by automation suitability, a documented business
case for a selected process, a complete AI agent workflow design, a governance
and access-control framework, and a 90-day implementation plan. These are
drafts that can be customized and presented to management immediately upon
return, saving months of preparatory work.
2. Content built on organizational realities,
not generic technology demos
Most available content on AI agents is built
on examples from global technology companies that bear little resemblance to
the operating environment of government entities and large organizations. This
course addresses the situations organizations actually face: administrative
correspondence and transactions, stakeholder requests, procurement and human
resources procedures, and periodic reports, as well as the challenges of
working in Arabic, integrating agents with existing enterprise systems, and
complying with data classification and local hosting requirements.
3. A design focused on moving from pilot to
production
The course is not a showcase of AI
capabilities; it is built around a specific question: How can an organization
avoid having its project become one of those canceled after the initial pilot?
The content therefore focuses on selecting processes based on measurable value,
designing human oversight and access boundaries from the outset, and
distinguishing between genuine agents and solutions marketed under that label
without warranting it.
4. Specialized trainers and up-to-date,
vendor-neutral training material
The course is delivered by trainers
specialized in artificial intelligence, digital transformation, and business
process reengineering, who combine a technical understanding of how agents work
with practical experience in implementing automation within organizations,
enabling them to answer participants' practical questions. The training
material has been prepared in accordance with the latest agent technologies,
development tools, and governance frameworks. It is vendor-neutral, focusing on
the principles and selection criteria that remain valid regardless of which
platform changes, ensuring that what participants learn can be applied to any
technology environment their organization adopts.
Course Objectives
1. Enable participants to distinguish between
traditional automation, AI assistants, and AI agents, and to identify the
enterprise processes most suited to each based on value and risk.
2. Equip participants with the skills to design
an AI agent workflow for a real enterprise process, including the tools, access
permissions, human oversight checkpoints, and performance indicators.
3. Prepare participants to lead an AI agent
project within their organizations from the pilot phase through to production,
within a governance framework that addresses personal data protection and
cybersecurity requirements.
Main Training Modules
1st Day: From Traditional Automation to AI
Agents
•
The difference between Robotic Process Automation (RPA), AI assistants,
and AI agents.
•
Components of an AI agent: the language model, tools, memory, planning,
and multi-agent systems.
•
When is an AI agent not the right solution? And how to identify the misleading
marketing of solutions under the agent label.
•
Practical exercise: Classifying the participant's organization's
processes into: traditional automation, AI assistant, AI agent, or retaining
manual operation.
2nd Day: Process Selection and Building the
Business Case
•
Analyzing and mapping processes to identify points of waste, repetition,
and delay.
•
Criteria for prioritizing processes: transaction volume, value, risk,
and data readiness.
•
Estimating cost and return, and defining measurable performance
indicators before starting.
•
Practical workshop: Preparing a documented business case for a selected
process from the participant's organization.
3rd Day: Designing the AI Agent and Its
Workflow
•
Designing the agent's workflow: inputs, steps, tools, and outputs.
•
Human oversight checkpoints and access boundaries, and when the agent
should stop and refer the decision to a staff member.
•
Integration with existing enterprise systems, and handling Arabic
content and bilingual documents.
•
Practical application: Building a prototype AI agent on a low-code
platform for a real enterprise process, such as classifying and routing
incoming correspondence.
4th Day: Governance, Risks, and Data Security
•
Risks of AI agents: inaccurate outputs, excessive permissions, data
leakage, prompt manipulation, and cost escalation.
•
Data classification and hosting, and compliance with applicable personal
data protection and cybersecurity requirements.
•
Audit trails and traceability, and international AI governance
frameworks such as ISO/IEC 42001.
•
Practical simulation (role-play): Handling an incident where an AI agent
executes an erroneous action, from the moment of discovery through to closure.
5th Day: Operations, Scaling, and Impact
Measurement
•
Transitioning from the pilot to full production, and continuous
monitoring of agent performance.
•
Change management and role redesign, and building an enterprise
operating model for AI.
•
Measuring impact and reporting to senior management in business language,
not technical language.
•
Practical exercise: Preparing an organizational implementation plan.
Course Outcomes
•
A precise, practical understanding of the nature of AI agents and a
clear distinction between them and traditional automation and AI assistants.
•
A process map of the organization classified by automation suitability
and priority.
•
A documented business case for a selected process, with measurable
performance indicators.
•
A complete AI agent workflow design, and a prototype built on a low-code
platform.
•
A governance and access-control framework ready for customization,
addressing personal data protection and cybersecurity requirements.
•
An organizational implementation plan with a clear timeline for moving
from pilot to production.
Certificates
Each
participant who fulfills the attendance and participation requirements of the
course will receive two certificates:
1. A certificate issued by The Only Solution for
Training and Consulting
2. A certificate issued by Cambridge Training
College Britain