According to Data USA, degrees in the business field are among the most popular in the United States, with 840,116 degrees in this field alone being awarded in 2020. You went down the commerce route (meaning you have a grasp of business administration, accounting, and applied economics) and now you’re interested in practical applications of your knowledge.


With your commerce degree firmly under your belt, you may feel like a ship without a rudder – aimless and having no idea what direction to go. Happily, the tech field is ready and waiting for you, as a career in computer sciences may await. Here, we ask, “can a commerce student do BSc Computer Science?” The answer may surprise you, especially if you’re worried that a computer science degree’s eligibility requirements are outside the scope of what you learned in your commerce studies.


Background on Commerce and Computer Science


On the surface, commerce and computer science may seem like they go together as well as peanut butter and granite. But if you dig a little deeper into the scope of each subject, you start to realize that there’s more crossover than there first appears:

  • Commerce – A degree in commerce gives you a firm grasp of the numbers that lie behind the scenes in a business, with banking, economics, and accounting all falling under your developing areas of expertise. Analytics is also a key part of these courses (especially in the research and data analyst fields), which is where we see some crossover with computer science.
  • Computer Science – If commerce is all about the behind-the-scenes numbers in business, computer science handles what goes on under the hood in computing. Software development, data modeling, and analysis all fall under the computer science graduate’s remit, with the ability to pore through data to come to conclusions being essential to this technical subject.

It’s in the analysis that we start to see similarities between commerce and computer science emerge. Yes, commerce focuses more on the numbers behind businesses (and wider economic trends), but the ability to understand the data presented and report on what you see has applications in the computer science field. There’s not a direct crossover, as computer science will require you to learn the “language” in which computers speak, but they are many soft skills you develop in a commerce degree that apply to computer science.


Eligibility for BSc Computer Science


The key questions to ask when considering the issue of whether can commerce student do BSc Computer Science split into two categories:

  • The general eligibility requirements to study a BSc in computer science
  • Specific requirements that apply to commerce students

Eligibility Criteria for BSc Computer Science


BSc Computer Science degrees don’t require a great deal of computer know-how (though it helps), instead focusing on your grasp of mathematics. Requirements include the following:

  • A high school diploma (or your country’s equivalent) that shows solid performance in mathematical subjects.
    • Some degrees require you to achieve a specific Grade Point Average (GPA), though the specific GPA varies depending on where you apply.
  • A high level of English proficiency, which can be measured using one (or both) of the following tests:
    • IELTS – Get a minimum score between 6.0 and 7.0
    • TOEFL – Get a minimum score between 90 and 100

Beyond these educational requirements, international students may need to submit copies of their passport and Visa, alongside certified academic transcripts to show they’ve achieved their country’s equivalents of the above grades. Not all courses require this of international students, with some online universities focusing more on your academic skills and less on your country of origin.


In terms of entrance exams, some colleges enforce computer science-specific exams (such as the CUET or CUCET), while others use NPATS or similar, more general exams, to determine proficiency.


Eligibility Criteria for Commerce Students


You may be standing at the starting line of your educational journey, meaning you’ve not yet applied to start your degree in commerce. First, congratulations on thinking so far ahead that you’re wondering “Can a commerce student do BSc Computer Science?” And second, you need to know what high school subjects help you get onto this degree path.


Commerce is a form of business degree, meaning any high school subjects that apply to the economic world help. Subjects like math, finance, economics, and foreign languages are obvious choices. The likes of marketing and computer applications also help (with the latter also laying some groundwork for your later computer science studies.


Much like computer science, you’ll likely have to take an entrance exam when applying to study commerce at most universities. The CSEET, CUET, and SET are common choices, with the first of these exams focusing specifically on those who study commerce to work as company secretaries.


The Possibility of Flexible Eligibility Criteria


Not all colleges require you to take entrance exams, with some even using broader strokes for their eligibility requirements to the point where they provide flexibility for both commerce and computer science students.


Colleges with open curriculums (such as Brown University and Hamilton College) offer more freedom in terms of what you study, with their entry requirements being more flexible as a result. Online institutions, such as the Open Institute of Technology (OPIT) may also offer more flexible entry criteria, sometimes allowing you to transfer credit from one course to another. That type of credit transfer may be ideal for you if you start a degree in commerce only to later decide to go down the computer science route.



Career Prospects for Commerce Students in Computer Science


When it comes to careers for those who hold computer science degrees, the obvious heavy-hitters are software and web development, IT management, and systems architecture. There are also exciting careers in the emerging AI fields that take full advantage of the technical skills you’ll develop as part of a BSc in computer science.


As for the career crossover between commerce and computer science, the key is to think about the skills that a commerce degree gives you that can apply in the computing field. Such skills include the following:

  • Analytical Skills – Much like computer science, commerce is all about analyzing the data presented so you can report (and leverage) it for other purposes. Your ability to sit down and pore through the numbers will take you a long way in a computer-related role.
  • Problem-Solving Skills – Closely linked to analytical skills, the ability to solve problems requires you to see the data at hand and come up with solutions while accounting for any restrictions presented. In creating commerce models, those restrictions may relate to budget and competencies, while computer science asks you to solve problems while taking system capabilities and limitations into account.
  • Communication and Teamwork – Though often considered soft skills (as opposed to the “hard” technical skills you learn in a commerce degree), communication and teamwork are vital. If you need proof, try to work alone in any technical career and you’ll see why it’s so crucial to have these skills.

Potential Career Paths for Commerce Students with a BSc in Computer Science


With so much crossover potential between commerce and computer science, it’s clear that the answer to the question can a commerce student do BSc Computer Science is a resounding “yes.” And once you’ve completed your studies, several career paths await:

  • Data Analyst – Reviewing data to find insights (be that into businesses or computer systems) are part of the remit for a data analyst. This role is all about problem-solving, which is a skill you’ll develop in abundance as a commerce and computer science student.
  • Business Analyst – Take the ability to gather insights that is required of a data analyst and apply it specifically to areas of improvement in a business to become a business analyst. You’ll combine technical knowledge of a company’s inner workings with complex financial (and computational) models.
  • IT Consultant – More computer science-centric than commerce-focused, IT consultants deal with the hows and whys of the computer networks businesses build. Your commerce skills will still come into play though, particularly when explaining how IT benefits businesses financially.
  • Financial Technology Specialist – Combining the best of both worlds, this role combines the accounting skills you develop studying commerce with the technical ability needed to understand software and its functions.

 

Challenges and Considerations for Commerce Students


Though it’s possible for a commerce student to study (and succeed in) computer science, there are some challenges to consider.


The Technical Nature of Computer Science


As you learn the language of numbers in a commerce degree, so must you learn the language of machines when studying computer science. Getting to grips with the lingo (not to mention coding) can present a challenge to more business-minded students.


Balancing Your Workload


There’s an old saying that goes “Don’t burn the candle at both ends,” which is a warning not to pack too much onto your work plate. If you study commerce and computer science simultaneously, there’s a risk you may push yourself too far. Avoiding burnout requires finding the balance between your studies and personal time.


Networking and Practical Experience


As a commerce student, you understand that the world of business is as much about who you know as what you know. Finding the right people to take a chance on you, thus giving you practical experience, can be tough. But when armed with a pair of degrees in subjects that complement one another, you’re in a better position to build connections with people who can help you go far.



From Commerce to Computing – Is It Right for You?


So, can a commerce student do BSc Computer Science?


The answer isn’t just “yes,” but that it’s actually a great direction to go. Where a commerce degree equips you with a nice mix of technical knowledge and soft skills, a computer science course gives you even more practical knowledge that allows you to enter more specialized fields. However, your interest in each subject plays a role, as your ability (and passion) for studying hinges on your desire to dig into the more technical world of computing.


Assuming you have a genuine interest (and meet the appropriate eligibility criteria), supplementing your commerce studies with computer science can open up many career paths.

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Il Sole 24 Ore: Integrating Artificial Intelligence into the Enterprise – Challenges and Opportunities for CEOs and Management
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Expert Pierluigi Casale analyzes the adoption of AI by companies, the ethical and regulatory challenges and the differentiated approach between large companies and SMEs

By Gianni Rusconi

Easier said than done: to paraphrase the well-known proverb, and to place it in the increasingly large collection of critical issues and opportunities related to artificial intelligence, the task that CEOs and management have to adequately integrate this technology into the company is indeed difficult. Pierluigi Casale, professor at OPIT (Open Institute of Technology, an academic institution founded two years ago and specialized in the field of Computer Science) and technical consultant to the European Parliament for the implementation and regulation of AI, is among those who contributed to the definition of the AI ​​Act, providing advice on aspects of safety and civil liability. His task, in short, is to ensure that the adoption of artificial intelligence (primarily within the parliamentary committees operating in Brussels) is not only efficient, but also ethical and compliant with regulations. And, obviously, his is not an easy task.

The experience gained over the last 15 years in the field of machine learning and the role played in organizations such as Europol and in leading technology companies are the requirements that Casale brings to the table to balance the needs of EU bodies with the pressure exerted by American Big Tech and to preserve an independent approach to the regulation of artificial intelligence. A technology, it is worth remembering, that implies broad and diversified knowledge, ranging from the regulatory/application spectrum to geopolitical issues, from computational limitations (common to European companies and public institutions) to the challenges related to training large-format language models.

CEOs and AI

When we specifically asked how CEOs and C-suites are “digesting” AI in terms of ethics, safety and responsibility, Casale did not shy away, framing the topic based on his own professional career. “I have noticed two trends in particular: the first concerns companies that started using artificial intelligence before the AI ​​Act and that today have the need, as well as the obligation, to adapt to the new ethical framework to be compliant and avoid sanctions; the second concerns companies, like the Italian ones, that are only now approaching this topic, often in terms of experimental and incomplete projects (the expression used literally is “proof of concept”, ed.) and without these having produced value. In this case, the ethical and regulatory component is integrated into the adoption process.”

In general, according to Casale, there is still a lot to do even from a purely regulatory perspective, due to the fact that there is not a total coherence of vision among the different countries and there is not the same speed in implementing the indications. Spain, in this regard, is setting an example, having established (with a royal decree of 8 November 2023) a dedicated “sandbox”, i.e. a regulatory experimentation space for artificial intelligence through the creation of a controlled test environment in the development and pre-marketing phase of some artificial intelligence systems, in order to verify compliance with the requirements and obligations set out in the AI ​​Act and to guide companies towards a path of regulated adoption of the technology.

Read the full article below (in Italian):

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The Lucky Future: How AI Aims to Change Everything
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Apr 10, 2025 7 min read

There is no question that the spread of artificial intelligence (AI) is having a profound impact on nearly every aspect of our lives.

But is an AI-powered future one to be feared, or does AI offer the promise of a “lucky future.”

That “lucky future” prediction comes from Zorina Alliata, principal AI Strategist at Amazon and AI faculty member at Georgetown University and the Open Institute of Technology (OPIT), in her recent webinar “The Lucky Future: How AI Aims to Change Everything” (February 18, 2025).

However, according to Alliata, such a future depends on how the technology develops and whether strategies can be implemented to mitigate the risks.

How AI Aims to Change Everything

For many people, AI is already changing the way they work. However, more broadly, AI has profoundly impacted how we consume information.

From the curation of a social media feed and the summary answer to a search query from Gemini at the top of your Google results page to the AI-powered chatbot that resolves your customer service issues, AI has quickly and quietly infiltrated nearly every aspect of our lives in the past few years.

While there have been significant concerns recently about the possibly negative impact of AI, Alliata’s “lucky future” prediction takes these fears into account. As she detailed in her webinar, a future with AI will have to take into consideration:

  • Where we are currently with AI and future trajectories
  • The impact AI is having on the job landscape
  • Sustainability concerns and ethical dilemmas
  • The fundamental risks associated with current AI technology

According to Alliata, by addressing these risks, we can craft a future in which AI helps individuals better align their needs with potential opportunities and limitations of the new technology.

Industry Applications of AI

While AI has been in development for decades, Alliata describes a period known as the “AI winter” during which educators like herself studied AI technology, but hadn’t arrived at a point of practical applications. Contributing to this period of uncertainty were concerns over how to make AI profitable as well.

That all changed about 10-15 years ago when machine learning (ML) improved significantly. This development led to a surge in the creation of business applications for AI. Beginning with automation and robotics for repetitive tasks, the technology progressed to data analysis – taking a deep dive into data and finding not only new information but new opportunities as well.

This further developed into generative AI capable of completing creative tasks. Generative AI now produces around one billion words per day, compared to the one trillion produced by humans.

We are now at the stage where AI can complete complex tasks involving multiple steps. In her webinar, Alliata gave the example of a team creating storyboards and user pathways for a new app they wanted to develop. Using photos and rough images, they were able to use AI to generate the code for the app, saving hundreds of hours of manpower.

The next step in AI evolution is Artificial General Intelligence (AGI), an extremely autonomous level of AI that can replicate or in some cases exceed human intelligence. While the benefits of such technology may readily be obvious to some, the industry itself is divided as to not only whether this form of AI is close at hand or simply unachievable with current tools and technology, but also whether it should be developed at all.

This unpredictability, according to Alliata, represents both the excitement and the concerns about AI.

The AI Revolution and the Job Market

According to Alliata, the job market is the next area where the AI revolution can profoundly impact our lives.

To date, the AI revolution has not resulted in widespread layoffs as initially feared. Instead of making employees redundant, many jobs have evolved to allow them to work alongside AI. In fact, AI has also created new jobs such as AI prompt writer.

However, the prediction is that as AI becomes more sophisticated, it will need less human support, resulting in a greater job churn. Alliata shared statistics from various studies predicting as many as 27% of all jobs being at high risk of becoming redundant from AI and 40% of working hours being impacted by language learning models (LLMs) like Chat GPT.

Furthermore, AI may impact some roles and industries more than others. For example, one study suggests that in high-income countries, 8.5% of jobs held by women were likely to be impacted by potential automation, compared to just 3.9% of jobs held by men.

Is AI Sustainable?

While Alliata shared the many ways in which AI can potentially save businesses time and money, she also highlighted that it is an expensive technology in terms of sustainability.

Conducting AI training and processing puts a heavy strain on central processing units (CPUs), requiring a great deal of energy. According to estimates, Chat GPT 3 alone uses as much electricity per day as 121 U.S. households in an entire year. Gartner predicts that by 2030, AI could consume 3.5% of the world’s electricity.

To reduce the energy requirements, Alliata highlighted potential paths forward in terms of hardware optimization, such as more energy-efficient chips, greater use of renewable energy sources, and algorithm optimization. For example, models that can be applied to a variety of uses based on prompt engineering and parameter-efficient tuning are more energy-efficient than training models from scratch.

Risks of Using Generative AI

While Alliata is clearly an advocate for the benefits of AI, she also highlighted the risks associated with using generative AI, particularly LLMs.

  • Uncertainty – While we rely on AI for answers, we aren’t always sure that the answers provided are accurate.
  • Hallucinations – Technology designed to answer questions can make up facts when it does not know the answer.
  • Copyright – The training of LLMs often uses copyrighted data for training without permission from the creator.
  • Bias – Biased data often trains LLMs, and that bias becomes part of the LLM’s programming and production.
  • Vulnerability – Users can bypass the original functionality of an LLM and use it for a different purpose.
  • Ethical Risks – AI applications pose significant ethical risks, including the creation of deepfakes, the erosion of human creativity, and the aforementioned risks of unemployment.

Mitigating these risks relies on pillars of responsibility for using AI, including value alignment of the application, accountability, transparency, and explainability.

The last one, according to Alliata, is vital on a human level. Imagine you work for a bank using AI to assess loan applications. If a loan is denied, the explanation you give to the customer can’t simply be “Because the AI said so.” There needs to be firm and explainable data behind the reasoning.

OPIT’s Masters in Responsible Artificial Intelligence explores the risks and responsibilities inherent in AI, as well as others.

A Lucky Future

Despite the potential risks, Alliata concludes that AI presents even more opportunities and solutions in the future.

Information overload and decision fatigue are major challenges today. Imagine you want to buy a new car. You have a dozen features you desire, alongside hundreds of options, as well as thousands of websites containing the relevant information. AI can help you cut through the noise and narrow the information down to what you need based on your specific requirements.

Alliata also shared how AI is changing healthcare, allowing patients to understand their health data, make informed choices, and find healthcare professionals who meet their needs.

It is this functionality that can lead to the “lucky future.” Personalized guidance based on an analysis of vast amounts of data means that each person is more likely to make the right decision with the right information at the right time.

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