You’re Ready for Agentic AI. So Where Do You Start?
Not an Agent for Every Process, but the Right Agent for the Right Process
Three to five workflows with clear decision criteria, reliable data, measurable outcomes, and manageable risk can provide a strong starting point for your organisation’s Agentic AI journey.
One of the most fundamental questions facing organisations exploring artificial intelligence is the same:
Where should we start?
The range of possibilities is broad.
Customer service, procurement, operations, human resources, finance, information technology… There are opportunities across virtually every function. Prioritising these opportunities requires organisations to assess both their level of readiness and the business value that can be created.
Gartner’s reports on AI readiness and competing in an Agentic AI environment provide complementary perspectives on this challenge. Although these studies focus primarily on financial institutions, they also offer an important takeaway for other industries: a successful starting point depends on understanding the organisation’s existing capabilities and defining the boundaries of the work that will be delegated to AI.
Starting Point: What Is Your Organisation Ready For?
Gartner’s report on AI readiness indicates that a large proportion of the organisations surveyed are still at relatively early stages of maturity.
While progress has been made in areas such as strategy and governance, data readiness, technical capabilities, organisational structures, and employee preparedness for new roles continue to stand out as areas for further development.
This raises several fundamental questions that can guide technology and implementation decisions:
- Is the data to be used reliable, current, and accessible?
- Is the process owner clearly identified, and are success criteria defined?
- Are the AI system’s authorities and the steps requiring human approval clearly established?
- Are employees prepared for the new operating model and their responsibilities within it?
- Can the value created be measured in terms of cost, time, and quality?
The answers to these questions help determine the scope of the first implementation.
Preparing the data, authority structures, and control mechanisms required by the selected workflow creates a concrete foundation for moving forward.
Select 3–5 Workflows for the First Step
Gartner’s Agentic AI reports recommend identifying three to five high-value workflows that are suitable for greater levels of delegated authority.
Priority is given to processes where decision criteria are clear, data is reliable, outcomes can be measured, and risks can be managed.
When this approach is applied across industries, potential starting points become quite tangible.
Examples include matching purchase orders, deliveries, and invoices in procurement; classifying customer requests and preparing responses in customer operations; checking onboarding documentation in human resources; and evaluating support tickets and recommending resolution steps in IT operations.
For each candidate process, the expected value should be defined from the outset.
How much will processing time decrease? How will error and rework rates change? Will the amount of manual checking required from employees decline? Will customer requests be resolved faster?
When current performance is measured before the pilot begins, the contribution of the implementation becomes visible.
This allows subsequent investment decisions to be based on results observed in real operations.
Transforming the Way We Work with Agentic AI
We see Agentic AI as a transformation in the way organisations work.
Within the authority assigned to them, AI agents can evaluate information, coordinate actions across different systems, and move workflows forward.
When these capabilities work alongside existing automations, business rules, and enterprise systems, they can create a broader field of value.
In a procurement process, for example, reading a document is only the first step.
Comparing the document with the relevant purchase order, identifying discrepancies, requesting missing information, and routing the case for the necessary approval all contribute directly to completing the process.
This is also how we define an AI-native way of working: designing workflows so that human judgement and AI capabilities create value together.
Determining who makes which decisions, what data is used, and how outcomes are monitored are all part of that design.
As Delegated Authority Increases, Human Responsibility Becomes More Explicit
One of the fundamental shifts highlighted in Gartner’s report is that while agents take on a greater role in decision-making and execution, humans continue to manage objectives, risk, and accountability.
For this reason, we see the human-in-the-loop approach as critical for organisations.
The points at which human approval is required, the conditions that trigger intervention, and the individuals responsible should be defined from the beginning of the process.
An agent may, for example, identify missing documentation and request that it be completed.
Actions such as releasing a payment or making a binding commitment on behalf of the organisation, however, may require human approval depending on the risk and authority thresholds defined for the process.
The ability to trace decisions, escalate exceptions to the appropriate person, and stop an action when necessary are also part of the same governance structure.
The appropriate level of authority may differ from one workflow to another.
In some processes, AI may provide the greatest value through decision support. In others, allowing it to execute actions within clearly defined boundaries may create greater value.
Initial Agent Implementations Reveal the Next Opportunities
Well-selected initial workflows provide organisations with both measurable business value and practical implementation experience.
Data gaps, approval bottlenecks, and dependencies between processes become more visible.
These learnings make it easier to identify and evaluate new areas where agents may create greater value.
We work with partners that help organisations shape their vision and governance models, while adapting our existing capabilities to individual business processes to support a fast and controlled start.
The initial objective is to establish an operating model whose value can be demonstrated and which can be scaled with confidence.
Let’s identify your organisation’s first three to five workflows together and begin the transformation with Agentic AI through value that can be measured.