Gains:
- Ability to explain the roles of robotic process automation (RPA) and artificial intelligence and the smart automation (hyperautomation) approach.
- Ability to design a manual process by dividing it into steps and distinguishing between steps that are suitable for automation and those that require human approval
- Ability to evaluate AI-supported automation designs in terms of exception management, audit trail and error cost
In every organization, there are tedious and error-prone tasks that people repeat every day: copying data from one system and entering it into another, manually processing billing information, sorting incoming emails. Robotic process automation (RPA) automates these regular and repetitive tasks with software robots that imitate the steps taken by a human on the screen. "Robot" here is not a physical machine, but software that clicks, writes and copies on the screen. The power of RPA is that it works on top of existing systems without changing them; Therefore, it provides fast results even in old systems that are difficult to integrate.
RPA alone cannot understand “no rules” situations. If an invoice arrives in standard format, the robot reads the fields; But if each supplier sends it in a different format, the robot will be confused. This is where artificial intelligence comes into play: AI performs the steps that require “judgment” such as understanding the document, classifying the text, extracting information from free text, and RPA carries out the canonical steps. This combination is called intelligent automation or hyperautomation (end-to-end, artificial intelligence-supported process automation). The role of the MIS specialist is to break a process into parts and design which part belongs to RPA, which part belongs to AI, and which part belongs to human.
Automating a Process
The heart of automation design is breaking the process into steps and classifying each step. There are three categories. Ruled and structured steps (RPA-friendly): "Enter each row in Excel into the ERP screen." Steps requiring comment (AI-powered): “To which category does this complaint text belong?” High risk or uncertain steps (left to the person): "Refund approval over 5,000 TL."
Good automation saves people from the repetitive burden, not from the entire job; leaves the critical decision to people. This is called human-in-the-loop design: the robot prepares the work, the human approves it. For example, the robot reads the invoice and enters the draft into the ERP, and the accountant gives the final approval. Thus, speed and security are ensured together.
Tip: Before automating a process, always simplify it first. Automating a bad process will only produce bad results faster. Eliminate unnecessary steps first, then automate the rest.
Exception Management and Audit Trail
Every automation eventually encounters a situation that breaks the rules: missing data, unexpected format, system crash. Exception handling allows the robot to safely stop and notify a human in such situations, instead of silently doing the wrong thing. If no exceptions are designed, the robot will silently proliferate errors and no one will notice.
Another necessity is the audit trail: a record of each step of the robot, when it was done, with what data and with what result. Without an audit trail, an error cannot be investigated later; This traceability is a legal requirement, especially in financial processes. AI can produce an outline of this process design, exception scenarios, and documentation; But which step is critical and what the cost of error is is determined by business knowledge.
Three Mini Cases: By the Numbers
Case 1 — Correct split process. In one accounting center, 4,000 monthly supplier invoices were being processed manually; The procedure took 6 minutes per person. AI read the document and extracted the fields, RPA entered the draft into ERP, the accountant just approved it. Processing time decreased from 6 minutes to 1.5 minutes, but the confirmation step remained with the human; thus the erroneous invoice continued to be caught.
Case 2 — When no exception is designed. At one insurer, a policy renewal robot silently mishandled 340 records with unexpected date formats; no one noticed and the renewals were entered with the wrong date. If the exception rule ("stop and report if format not recognized") were designed from scratch, the robot would direct these records to the human. The fix took weeks.
Case 3 — Automation of the wrong process. At one retailer, the order confirmation process had 11 steps; It would be automated with a robot. When the MIS expert examined the process, he saw that the 4 steps were unnecessary double checks. First the process was reduced to 7 steps, then it was automated. If it were automated without simplification, 4 unnecessary steps would be permanent.
Weak Prompt / Strong Prompt
Weak prompt:
Automate invoice processing.
Powerful prompt:
Your role: You are a process automation designer. Break the following manual process into steps and classify each step:- [RPA] canonical, structured, repetitive- [AI] requiring interpretation/categorization/text understanding- [HUMAN] high risk or ambiguous decision For each step, write down possible exceptions and what to do in case of error. List the information that needs to be recorded for the audit trail. Process: [step-by-step manual process description]
Powerful prompt breaks down the process, assigns each step to the correct role, and raises exceptions and audit trail from the beginning.
Four Copiable Templates
1) Process decomposition:
Break the manual process below into numbered steps. For each step: input, process, output, and automation availability ([RPA]/[AI]/[HUMAN]).Process: [text]
2) Generating an exception scenario:
For the following automated process, “what could go wrong?” List scenarios: missing data, incorrect format, system error, double record. Suggest what the robot should do for each. Process: [text]
3) Simplification review:
Mark the steps in the process below that are unnecessary, repetitive, or do not produce value, and write why they can be removed. Suggest simplification BEFORE automation. Process: [text]
4) Audit trail design:
Design an audit trail for the following automated process: which fields (time, user/robot, input, result, decision) should be recorded at each step?Indicate any gaps in terms of financial traceability. Process: [text]
Comparison Chart: RPA / AI / Human
criterion
RPA
Artificial Intelligence
human
What he's best at
Regular, repetitive
Comment, classification
judgment, responsibility
Input type
structured
Semi/free text
all types
Error behavior
Follows the rule to the letter
As sure as can be wrong
Can detect and stop
Audit
Easy to log
Output must be logged
Signature/approval
final decision
no
no
Yes
Common mistakes
- Automating the bad process. Automating without simplifying first perpetuates waste.
- Not designing exceptions. The robot, built on the assumption that "all goes well", silently produces errors at the first surprise.
- Leaving the critical decision to AI. Delegating high-risk approval to the model; Even if the model seems confident, it is wrong and bears no responsibility.
- Bypassing the audit trail. Without a trace, the error cannot be investigated; This is a legal violation in the financial process.
- Not watching the robot at all. Systems change (screen, space); One day, the unmonitored robot silently starts clicking in the wrong place.
Caution: The speed of automation also speeds up error. If a human makes a mistake while processing 60 records per hour, they are limited to 60 errors; An incorrectly installed robot can corrupt thousands of records in minutes. So pilot it in a small volume at first, under supervision.
In summary
RPA automates regular and repetitive tasks by mimicking screen steps; Artificial intelligence takes over the steps that require interpretation and classification. The combination of the two is intelligent automation. The heart of design is breaking the process into steps and assigning each step to RPA, AI, or human; High-risk decisions keep people in the loop. Exception handling and audit trail are a must. AI accelerates process decomposition, exception scenario and documentation drafting; But which is the critical step and the cost of error is determined by business knowledge. Before automating, simplify and validate with small pilot first.
Application task
Choose a “leave request approval process” (employee requests, manager approves, HR processes). (1) Divide the process into steps with the powerful prompt and classify each step as [RPA]/[AI]/[HUMAN]. (2) Describe at least 3 exception scenarios and what the robot will do in each. (3) Find at least 1 unnecessary step that can be removed before automation. (4) List the areas to be recorded for the audit trail. (5) Mark the single high-risk step and write why it should remain in the human.
checklist
- [ ] I divided the process into steps and assigned each step to the correct role.
- [ ] I simplified the process before automation.
- [ ] I defined exception behavior for each step.
- [ ] I have determined the areas to be recorded for the audit trail.
- [ ] I left high-risk decisions in the human loop.
- [ ] I first planned a small volume, supervised pilot.