You can not just set up an AI agent then sit and wait for magic to happen. In this post we’ll explore how to decide which AI agents you need for your workflow.
Let me tell you a memory of my own. Several years ago, in my home town, I was chatting with a senior officer of a tea company. The topic was soil management, soil analysis etc. In his own words ‘’ there was one farmer. When we first visited him, he saw us in his garden, he stood up and came toward us happily. We took samples, sent them to the laboratory for analysis, then sent him the report along with advice to improve his soil and of course green tea quality as a product. The next year we visited him, he sat in his chair, not even looking at us and said ‘’what you did last year didn’t change anything.’’ That’s what we experience all the time.
If your plan is to do nothing and expect the best, like in the story above, you will fail with AI agents. Deploying them is a process, you should see them as colleagues. For reference take a look at my previous post, AI Agents: A Beginner’s Guide to Understanding the Basics
The framework below tells you how to decide which AI agents you need. Let’s start.
Step 1 – Task inventory
bring your team together for a 2-hour session
We’ve seen that asking a few specific questions yields better results than brainstorming; ask your team the following questions
1- What tasks do you find yourself repeating during the week?
2- What activities/tasks prevent you from focusing on more strategic work?
3- What are the processes/situations in our operations that constantly create bottlenecks/impediments?
4- Which routine tasks require the most oversight to prevent errors?
💡 The key point is to capture not only the tasks, but also their frequency and the approximate time spent on each.
- Write down the tasks/jobs you found
Example;
1- ………..
2- ………..
3- ………..
4- ………..
5- ………..
Step 2 – Impact Assessment
4.
Assess the potential impact of automating each task/job. For each task, give a score between 1 and 5 based on the criteria below; refer to the table below
A. Time Saved: How much time does the task/job currently take that could actually be saved?
B. Strategic Value of Freed-Up Time (What is the opportunity cost?)
C. Error Reduction Potential (How frequently do errors occur?)
D. Scalability Impact (Can this be applied across the entire organization?)
- Enter the score you assigned for each of A, B, C, and D into the corresponding section of the table below.
Calculate the total score for each task/job. The total scores will range between 4 and 20. The higher the total score, the more suitable the task/job is for automation.
Example;
1- A + B + C + D + ………..
2- A + B + C + D + ………..
3- A + B + C + D + ………..
4- A + B + C + D + ………..
5- A + B + C + D + ………..
Step 3 – Feasibility Assessment
💡We divide feasibility into 2 main components, and we score both (from 1 to 5). Check the table below
E- Process Standardization: Ask this question:
“Can a new person fully follow this process using only our documentation?
F- Data and System Access:
Score whether the data is structured, easily retrievable, and accessible through modern systems — or if it requires manual preparation.
7.
Write the scores for E and F in their places in the table below, and calculate the total score.
Example;
1- A + B + C + D + E + F ………..
2- A + B + C + D + E + F ………..
3- A + B + C + D + E + F ………..
4- A + B + C + D + E + F ………..
5- A + B + C + D + E + F ………..
💡 After the scoring, you have identified which tasks/jobs are ready for automation and which ones need improvement beforehand.
Step 4: Implementation effort
How to Score Technical Complexity (1–5, Reverse Scoring)
This is a reverse-scored metric, meaning lower scores indicate higher complexity and greater difficulty in implementation.
G – Score each task/job based on one of the situations below.
Score 5 (Easiest to Implement) — The task can be automated using standard tools that require little to no customization.
Score 4 — Some customization is needed, but it relies on widely used technologies.
Score 3 — The solution requires significant custom development, such as scripting.
Score 2 — Requires complex integrations or adoption of new technologies.
Score 1 (Most Difficult) — The task requires cutting-edge technology solutions or extensive research and development (R&D).
Add the G score to the table below, and calculate the total score.
Example;
1- A + B + C + D + E + F + G = 30
2- A + B + C + D + E + F + G = 25
3- A + B + C + D + E + F + G = 31
4- A + B + C + D + E + F + G = 27
5- A + B + C + D + E + F + G = 34
After the scoring, you have determined which tasks/jobs are ready for automation and which ones need to be improved beforehand.
Step 5 Conclusion: Final Analysis – Select the highest-scoring task/job for intelligent automation.
You have identified No.5, which scored 34 out of 35 points, as the most suitable task/job for intelligent automation.
💡💡💡Our recommendation is to always start with proven, mainstream tools and platforms before pushing technological boundaries.
Automating simple, high-impact tasks first builds momentum, reduces risk, and achieves early wins before tackling more complex solutions.
You just decided which AI agent you require most. To implement with no code platform you may take a look at my previous post; How to Build Your First No-Code AI Agent in Minutes: Step-by-Step Guide
Hakan Kose
hakankose.com