Artificial intelligence is no longer a distant concept in the workplace.

Professionals are experimenting with different AI tools.

Writing content.

Conducting research.

Summarizing meetings.

Preparing reports.

Generating ideas.

But an important question remains:

Does using AI tools necessarily mean we are working more efficiently?

Giving a task to an AI system is not the same as integrating that system into a meaningful workflow.

An AI tool might summarize meeting notes in minutes.

But if the summary does not clearly identify actions, responsibilities, and decisions requiring human review, the process may deliver limited practical value.

Deniz Tekbaş, Founder of TruOpt.ai and an AI, growth, and digital transformation consultant, highlights an important principle:

“The most effective way to work with AI is actually to work together. We should use AI as a tool.”

This perspective places collaboration, rather than replacement, at the center of AI adoption.

AI can accelerate the production of an output.

However, evaluating whether that output meets the objective, correcting inaccuracies, and turning it into a business decision remain essential responsibilities.

The real question is not whether we use AI, but how and why we use it.

What Does It Mean to Use AI Effectively at Work?

Effective AI adoption does not mean trying to automate every task.

It begins with identifying which activities can become clearer, more manageable, or more efficient with AI support.

Consider a professional who regularly turns meeting notes into action lists.

AI may help:

• Structure the notes.
• Separate decisions from tasks.
• Draft responsibility assignments.
• Identify follow-up items.
• Highlight information that requires clarification.

However, human review remains important.

Are responsibilities assigned correctly?

Are deadlines accurate?

Do the listed decisions reflect what participants actually agreed upon?

Which details require verification?

When these questions are addressed, AI becomes more than a content-generation tool.

It becomes a practical assistant within the workflow.

Why Does It Matter?

Turning Technology Into Practical Business Value

Using a new technology does not automatically improve business processes.

The important question is which problem the technology solves and which outcome it improves.

Clearly defined tasks can transform occasional experimentation into a more systematic approach.

Making Repetitive Tasks More Manageable

Meeting notes, research, reporting drafts, and content preparation often involve recurring activities.

AI can help structure these tasks, allowing professionals to dedicate more attention to evaluating and improving the results.

Maintaining Human Oversight

AI-generated outputs are not always ready for immediate use.

Misinterpreted information, missing context, and unclear instructions can affect output quality.

Human oversight should therefore be considered from the beginning of the workflow rather than added only at the final stage.

Turning Learning Into Everyday Practice

Experimenting with an AI tool once is different from using it consistently within a professional workflow.

Long-term value becomes more achievable when the process is repeatable, measurable, and open to improvement.

How Can You Integrate AI Into Your Workflow?

1. Identify the Business Need

Start with a specific task you want to improve.

Instead of saying:

“I want to use AI more often.”

define a practical objective:

“I want to turn weekly meeting notes into a structured action list.”

2. Define the Task Boundaries

Explain which sources AI should use, what format the output should follow, and which information must remain unchanged.

Clear boundaries make results easier to review.

3. Specify the Expected Output

Do you need a summary?

An action list?

A comparison table?

A research draft?

Defining the desired output makes the task more focused.

4. Establish Human Review Points

Determine which information must be verified and which decisions require human approval.

Consider privacy, security, and confidentiality requirements, especially when working with customer information, financial data, or commercially sensitive content.

5. Evaluate and Improve

Rather than accepting the first result as final, assess how well it meets the original objective.

Make adjustments and improve the instructions for future use.

Each iteration can contribute to a more effective workflow.

A Quick Test

Think about your typical working week.

Choose one task you performed repeatedly.

Then ask:

Which part of this task could AI support?

What exactly should the output look like?

Where is my own review or approval necessary?

If you can answer these three questions clearly, you may already have a useful starting point for integrating AI into your work.

From Knowledge to Practice: ThumbsAd's First Free AI Webinar

At ThumbsAd, we believe AI should be more than a technology people discuss.

It should be something professionals can learn, evaluate, and apply to real business needs.

With this approach, we have introduced a new Educations section on our website.

Our first event is a free live webinar:

What Can You Simplify at Work With AI?

Date: Saturday, October 24, 2026
Time: 12:00–13:00 (Turkey time, UTC+3)
Format: Online, delivered in Turkish
Participation: Free
Speaker: Deniz Tekbaş — AI, Growth & Digital Transformation Consultant

During the webinar, participants will work through a practical business example and complete a short exercise related to their own tasks.

The program includes:

1. Identifying business needs and boundaries
2. Fundamentals of task design
3. Turning meeting notes into an action list
4. A short practical exercise
5. Workshop information and Q&A

The objective is not simply to introduce AI concepts, but to help participants identify a practical starting point for their own work.

Free registration: ThumbsAd Educations

Conclusion: Learning to Work With AI

The development of artificial intelligence does not mean every task should be handed over to technology.

Real value comes from selecting appropriate tasks, setting clear expectations, evaluating outputs, and improving workflows while maintaining human oversight.

This is the principle behind Deniz Tekbaş's perspective:

AI does not have to replace human expertise. It can become part of a more effective way of working together.

Learning AI should therefore go beyond becoming familiar with tools.

It should involve understanding how those tools can be applied to real business problems.

Knowing the technology is a starting point. Learning how to use it effectively is what helps turn that knowledge into practical value.

Our free webinar on October 24 is an opportunity to begin putting this approach into practice.