What really taught me a digital skills and digital skills certificate

by Lina Droskin

Not only about models and tools. About uncertainty. Professional ethics. Humanity.

Earlier this year, I completed an international certificate on artificial intelligence and digital skills. On paper, it looked like a technical course on algorithms, models and digital maturity. I revealed something deeper.

We often deal with certificates that expect to know new work, or even confidence enhancements. And while I received all of these, this trip gave me more: a mirror of thinking about those who have become professionals and people in an AI.

It is not an artistic abbreviation

The first legend was broken for me was the idea that artificial intelligence is delivery and operation. Media often displays it as magic: enter some data and get great results. But artificial intelligence in the real world is not like this. Models are not the most difficult part: Data preparedness, organizational alignment, and moral clarity We are.

As one of the famous leaders, he said: ” “A” in artificial intelligence does not necessarily mean “artificial.“It can mean” automatically. “This echo that has been deeply echoed. Amnesty International is not some distant properties; it is a group of tools, strong, but uninterrupted, and formed by our intentions, data and morals.

You cannot automate what you do not understand. And it should not be automated unless it is carefully examined.

This also means that the promise of artificial intelligence will always be limited to the quality of our thinking, not only the quality of our models. We still need humans to determine what good Similar.

An invitation to wake up leadership

In our discussions, what was most emerged was not technology, it was the leadership. The most difficult decisions were about models, but for people.

• Who has the results?
• What biases are baked in our systems?
• Who leaves behind when we bear automation?

One group philosophical discussion has turned unexpectedly. We discussed whether it is moral to automate decisions without a human review, especially in sectors such as financing or health care. On that day, I stopped seeing artificial intelligence as a production tool. I started to see it as a Ethical selection.

These talks revealed something uncomfortable: Many organizations are not ready for these questions. Work decisions are taken without the correct sounds on the table. Sometimes the speed is determined on the wisdom.

We are not just coding automation, We cote the values. This means responsibility.

My voice reminder

During the program, I heard visions of people all over the world. I listened to wonderful minds from North America, Asia and Western Europe. But I also started noticing something else: many voices were missing. It was a few participants from Eastern Europe or the smaller countries. Even fewer women in medium -level leadership roles.

It made me think of my voice, and what I can bring to these spaces. I stopped asking, “Do I belong here?” And she started asking, “What can I contribute?”

As a professional from smaller markets or an active actress groups, we often hesitate. But Amnesty International will form the future of everyone, and not only in Silicon Valley. We all deserve a seat on the table where the digital transformation is discussed and decided.

In fact, the diversity of thought is not “good to be” in the design of artificial intelligence. It is a necessity.

Mobility in uncertainty with confidence

If you have to summarize the main fast food, this will be: Artificial intelligence is not just a technical challenge. It is human.

Learn how to deal with artificial intelligence means learning how to move uncertain. Because the data may be incomplete. The algorithms may act in unpredictable ways. The influence may be affected beyond what we can see.

But instead of waiting for everything to be clear, I learned to work with him Intention. To ask better questions. To slow when the answers feel very quickly. To enter others in conversation – not only engineers or analysts, but ethics, designers and front lines workers.

In short: I was not more skilled, but more aware.

What does this mean for business analysts

For those in business analysis, this experience enhances something essential. Our role was never about the requirements and plans. It is related to connecting points through mystery. See the biggest picture. Being the bridge between vision and implementation.

With artificial intelligence, this role becomes more vibrant. Someone needs the question:

• Why do we automate this?
• Who benefits – and who may be harmed?
• Do we trust the data?
• What decisions should we not automate?

Business analysts, strategists and leaders of change are uniquely placed to direct organizations – not only in digital transformation, but to Responsible,.

This is the place where our analytical thinking meets A moral reflection.

The hidden curriculum

The official curriculum covered automated learning, digital literacy, and decisions that depend on data. But the hidden approach was more powerful: learning how to drive in the face of complexity.

This means interrogation not only tools, but A culture about those tools. This means realizing when the speed was used to avoid uncomfortable conversations. This means noting when priority was given to “efficiency” at the expense of sympathy.

This also means having my own development, paying through the antichrist syndrome, and speaking even when I was not sure that I got the ideal answer, and communicate with others who move in the same doubts.

This was a mental transformation that I did not expect. But this is what I appreciate most.

The preparation gap that we are not talking about

One of the less bright, but most important lessons is: many organizations Not ready for AI, not technically, not culturally.

We assume that the tools will create value. But the tools do not work in isolation. They depend on alignment teams, clear operations, clean data, and common goals. In many cases in the real world, commercial operations are not documented or varying widely between departments. The data is chaotic, incomplete, or horrific. The difference lacks a common understanding of what is artificial intelligence, and what is not for it.

This is where business analysts can shine. Not only as the requirements of the requirements, but like the sensor, the facilitators, and the navigators of the complexity. We can reveal what is missing for a long time before building the solution. We can ask uncomfortable questions before making irreversible options. We can create a common understanding Bridges and delivery strategy.

Empowering new voices

Finally, I would like to share a single personality vision that continues to grow in meaning: we need more voices from regions, roles and perspectives active in an artificial intelligence.

As a person from BalTics, I know how easy I am invisible in international digital conversations. But knowledge is not created only in large cities or headquarters. The shift is not limited to large companies.

For this reason, I began to integrate artificial intelligence ethics and digital thinking in training courses, to ensure that students and Future analysts can participate in confidence, critical and morally.

because The future of work does not only need programmers. It needs conscious decision makers.

What comes after that

This certificate was not the end. It was the beginning. I now find myself attracted to deeper talks on technology, confidence, systems, values, speed and sustainability.

I have begun to bring this mentality to every training that I lead and every decision that affects him. Because I now see that the way we implement artificial intelligence is not just a matter of “how”, but “from”, “why”, and “what”.

I share these ideas not because I have all the answers, but because I know that I am not alone in asking these questions.

Anyone who thinks about AI or Digital Skills Program: bypassing the curriculum. Ask how to change learning for you, not just what you can do, however How to choose to do that.

Because this is really important.

Reference

1. Sol Rashidi, (2024). 6 lessons on artificial intelligence and data from Sol Rashidi. Wall Street Journal, Deloitte.

https://deloitte.wsj.com/sustain-busining/6-lesons-on-II-and-data-from-sol-rashidi-a6364E4

1. Harvard Business Review (2024). Focus on people, not only technology in artificial intelligence.

https://hbr.org/

1. Christina Wallace (2022). Human Venn Plan: A logical functional path. TEDX conversations.

https://www.tud.com/Speakers/christina_wallace

1. BCS, Carted Institute of Information Technology (2020). Business Analysis, Fourth Edition.
2. World Economic Forum (2023). Tomorrow functions: mapping chances in the new economy.

https://www.weforum.org/

About the author
Lina DroskinMBCS, is a teacher of sound analysis and commercial analysis of a passionate thinking of data, clarity and responsible transformation. It helps organizations and individuals to make more wise decisions-by thinking about the systems, the leadership that suffers from human, and digital awareness.

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