You may have heard the catchy phrase “data is the new oil” floating around. The implication is that data in the 21st century is what oil was in the 20th – the biggest industry around. And it’s true, as the sheer amount of data each person generates when they use the web, try out an app, or even buy from a store is digital “oil” for the companies collecting that data.


It’s also the fuel that powers the current (and growing) wave of artificial intelligence (AI) tools emerging in the market. From ChatGPT to the wave of text-to-speech tech flooding the market, everything hinges on information, and people who can harness that data through algorithms and machine learning practices are in high demand.


That’s where you can come in. By taking a Master’s degree in artificial intelligence online, you position yourself as one of the people who can help the new “digital oil” barons capitalize on their finds.


Factors to Consider When Choosing an Online AI Master’s Program


When choosing an artificial intelligence online Master’s, you have to consider more than the simple accessibility the course offers. These factors help you to weed out the also-ran programs from the ones that help you to advance your career:


  • Accreditation – Checks for accreditation come in two flavors. First, you need to check the program provider’s credentials to ensure the degree you get from your studies is worth the paper on which it’s printed. Second, you have to confirm the accreditation you receive is something that employers actually want to see.
  • Curriculum – What does your artificial intelligence online Master degree actually teach you? Answer that question and you can determine if the program serves the career goals you’ve set for yourself.
  • Faculty Expertise – On the ground level, you want tutors with plenty of teaching experience and their own degrees in AI-related subjects. But dig beyond that to also discover if they have direct experience working with AI in industry.
  • Program Format – A self-study artificial intelligence Master’s program’s online nature means they offer some degree of flexibility. But the course format plays a role in your decision, given that some rely solely on self-learning whereas others include examinations and live remote lectures.
  • Tuition and Financial Aid – A Master’s degree costs quite a bit depending on area (prices range from €1,000 to €20,000 per year), so you need to be in the appropriate financial position. Many universities offer financial aid, such as scholarships, grants, and payment programs, that may help here.
  • Career Support – You’re likely not studying for Master of artificial intelligence online for the joy of having a piece of paper on your wall. You want to build a career. Look for institutions that have strong alumni networks, connections within industry, and dedicated careers offices or services.

Top Online AI Master’s Programs Ranked


In choosing the best Master’s in artificial intelligence online programs, we looked at the above factors in addition to the key features of each program. That examination results in three online courses, each offering something a little different, that give you a solid grounding in AI.


Master in Applied Data Science & AI (OPIT)


Flexibility is the name of the game with OPIT’s program, as it’s fully remote and you get a choice between an 18-month course and a fast-tracked 12-month variant. The latter contains the same content as the former, with the student simply dedicating themselves to more intensive course requirements.


The program comes from an online institution that is accredited under both the Malta Qualification Framework and European Qualification Framework. As for the course itself, it’s the focus on real-life challenges in data science and AI that makes it so attractive. You don’t just learn theory. You discover how to apply that theory to the practical problems you’ll face when you enter the workforce.


OPIT has an admissions team who’ll guide you through getting onto the course, though you’ll need a BSc degree (in any field) and the equivalent of B2-level English proficiency to apply. If English isn’t your strong suit, OPIT also offers an in-house certification that you can take to get on the course. Financial aid is available through scholarships and funding, which you may need given that the program can cost up to €6,500, though discounts are available for those who apply early.



Master in Big Data, Artificial Intelligence, and Disruptive Technologies (Digital Age University)


If data is the new oil, Digital Age University’s program teaches you how to harness that oil and pump it in a way that makes you an attractive proposition for any employer. Key areas of study include the concept and utilization of Big Data (data analytics plays a huge role here), as well as the Python programming skills needed to create AI tools. You’ll learn more about machine learning models and get to grips with how AI is the big disruptor in modern business.


Tuition costs are reasonable, too, with this one-year course only costing €2,600. Digital Age University runs a tuition installment plan that lets you spread your costs out without worrying about being charged interest. Plus, your previous credentials may put you in line for a grant or scholarship that covers at least part of the cost. All first-year students are eligible for the 10% merit-based scholarship again, dependent on prior education). There’s also a 20% Global Scholarship available to students from Asia, Africa, the Middle East, and Latin American countries.


Speaking of credentials, you can showcase yours via the online application process or by scheduling a one-on-one call with one of the institution’s professors. The latter option is great if you’re conducting research and want to get a taste of what the faculty has to offer.


Master in Artificial Intelligence (Three Points Digital Business School)


Three Points Digital Business School sets its stall out early by pointing out that 83% of companies say they’ll create new jobs due to AI in the coming years. That’s its way of telling you that its business-focused AI course is the right choice for getting one of those jobs. After teaching the fundamentals of AI, the course moves into showing you how to create AI and machine learning models and, crucially, how to apply those models in practical settings. By the end, you’ll know how to program chatbots, virtual assistants, and similar AI-driven tools.


It’s the most expensive program on this list, clocking in at €7,500 for a one-year course that delivers 60 ECTS credits. However, it’s a course targeted at mature students (half of the current students are 40 years old), and it’s very much career-minded. That’s exemplified by Three Points’ annual ThinkDigital Summit, which puts some of the leading minds in AI and digital innovation in front of students.


Admission is tougher than for many other Master’s in artificial intelligence online programs as you go through an interview process in addition to submitting qualifications. Every candidate is manually assessed via committee, with your experience and business know-how playing as much of a role as any technical qualifications you have.


Tips for Success in an Online AI Master’s Program


Let’s assume you’ve successfully applied to an artificial intelligence online Master’s program. That’s the first step in a long, often complex, journey. Here are some tips to keep in mind and set up for the future:


  • Manage your time properly by scheduling your study, especially given that online courses rely on students having the discipline needed for self-learning.
  • Build relationships with faculty and peers who may be able to connect you to job opportunities or have ideas for starting their own businesses.
  • Stay up-to-date on what’s happening with AI because this high-paced industry can leave people who assume what they know is enough behind.
  • Pursue real-world experience wherever you can, both through the practical assessments a program offers and internship programs that you can add to your CV.

Career Opportunities With a Master’s in Artificial Intelligence


You need to know what sorts of roles are available on the digital “oil rigs” of today and the future. Those who have an artificial intelligence online Master degree take roles as varied as data analyst, software engineer, data scientist, and research scientist.


Better yet, those roles are spread across almost all industries. Grand View Research tells us that we can expect the AI market to enjoy a 37.3% compound annual growth rate between 2023 and 2030, with that growth making AI-based roles available on a near-constant basis. Salary expectations are likely to increase along with that growth, with the current average of around €91,000 for an artificial intelligence engineer (figures based on Germany’s job market) likely to be a baseline for future growth.



Find the Right Artificial Intelligence Master’s Programs Online


We’ve highlighted three online Master’s programs with a focus on AI in this article, each offering something different. OPIT’s course leans heavily into data science, giving you a specialization to go along with the foundational knowledge you’ll gain. Digital Age University’s program places more of a focus on Big Data, with Three Points Digital Business School living up to its name by taking a more business-oriented approach.


Whatever program you choose (and it could be one other than the three listed here), you must research the course based on the factors like credentials, course content, and quality of the faculty. Put plenty of time into this research process and you’re sure to find a program that aligns with your goals.

Related posts

CCN: Australia Tightens Crypto Oversight as Exchanges Expand, Testing Industry’s Appetite for Regulation
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Mar 31, 2025 3 min read

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  • CCN, published on March 29th, 2025

By Kurt Robson

Over the past few months, Australia’s crypto industry has undergone a rapid transformation following the government’s proposal to establish a stricter set of digital asset regulations.

A series of recent enforcement measures and exchange launches highlight the growing maturation of Australia’s crypto landscape.

Experts remain divided on how the new rules will impact the country’s burgeoning digital asset industry.

New Crypto Regulation

On March 21, the Treasury Department said that crypto exchanges and custody services will now be classified under similar rules as other financial services in the country.

“Our legislative reforms will extend existing financial services laws to key digital asset platforms, but not to all of the digital asset ecosystem,” the Treasury said in a statement.

The rules impose similar regulations as other financial services in the country, such as obtaining a financial license, meeting minimum capital requirements, and safeguarding customer assets.

The proposal comes as Australian Prime Minister Anthony Albanese’s center-left Labor government prepares for a federal election on May 17.

Australia’s opposition party, led by Peter Dutton, has also vowed to make crypto regulation a top priority of the government’s agenda if it wins.

Australia’s Crypto Growth

Triple-A data shows that 9.6% of Australians already own digital assets, with some experts believing new rules will push further adoption.

Europe’s largest crypto exchange, WhiteBIT, announced it was entering the Australian market on Wednesday, March 26.

The company said that Australia was “an attractive landscape for crypto businesses” despite its complexity.

In March, Australia’s Swyftx announced it was acquiring New Zealand’s largest cryptocurrency exchange for an undisclosed sum.

According to the parties, the merger will create the second-largest platform in Australia by trading volume.

“Australia’s new regulatory framework is akin to rolling out the welcome mat for cryptocurrency exchanges,” Alexander Jader, professor of Digital Business at the Open Institute of Technology, told CCN.

“The clarity provided by these regulations is set to attract a wave of new entrants,” he added.

Jader said regulatory clarity was “the lifeblood of innovation.” He added that the new laws can expect an uptick “in both local and international exchanges looking to establish a foothold in the market.”

However, Zoe Wyatt, partner and head of Web3 and Disruptive Technology at Andersen LLP, believes that while the new rules will benefit more extensive exchanges looking for more precise guidelines, they will not “suddenly turn Australia into a global crypto hub.”

“The Web3 community is still largely looking to the U.S. in anticipation of a more crypto-friendly stance from the Trump administration,” Wyatt added.

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Agenda Digitale: Generative AI in the Enterprise – A Guide to Conscious and Strategic Use
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Mar 31, 2025 6 min read

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By Zorina Alliata, Professor of Responsible Artificial Intelligence e Digital Business & Innovation at OPIT – Open Institute of Technology

Integrating generative AI into your business means innovating, but also managing risks. Here’s how to choose the right approach to get value

The adoption of generative AI in the enterprise is growing rapidly, bringing innovation to decision-making, creativity and operations. However, to fully exploit its potential, it is essential to define clear objectives and adopt strategies that balance benefits and risks.

Over the course of my career, I have been fortunate to experience firsthand some major technological revolutions – from the internet boom to the “renaissance” of artificial intelligence a decade ago with machine learning.

However, I have never seen such a rapid rate of adoption as the one we are experiencing now, thanks to generative AI. Although this type of AI is not yet perfect and presents significant risks – such as so-called “hallucinations” or the possibility of generating toxic content – ​​it fills a real need, both for people and for companies, generating a concrete impact on communication, creativity and decision-making processes.

Defining the Goals of Generative AI in the Enterprise

When we talk about AI, we must first ask ourselves what problems we really want to solve. As a teacher and consultant, I have always supported the importance of starting from the specific context of a company and its concrete objectives, without inventing solutions that are as “smart” as they are useless.

AI is a formidable tool to support different processes: from decision-making to optimizing operations or developing more accurate predictive analyses. But to have a significant impact on the business, you need to choose carefully which task to entrust it with, making sure that the solution also respects the security and privacy needs of your customers .

Understanding Generative AI to Adopt It Effectively

A widespread risk, in fact, is that of being guided by enthusiasm and deploying sophisticated technology where it is not really needed. For example, designing a system of reviews and recommendations for films requires a certain level of attention and consumer protection, but it is very different from an X-ray reading service to diagnose the presence of a tumor. In the second case, there is a huge ethical and medical risk at stake: it is necessary to adapt the design, control measures and governance of the AI ​​to the sensitivity of the context in which it will be used.

The fact that generative AI is spreading so rapidly is a sign of its potential and, at the same time, a call for caution. This technology manages to amaze anyone who tries it: it drafts documents in a few seconds, summarizes or explains complex concepts, manages the processing of extremely complex data. It turns into a trusted assistant that, on the one hand, saves hours of work and, on the other, fosters creativity with unexpected suggestions or solutions.

Yet, it should not be forgotten that these systems can generate “hallucinated” content (i.e., completely incorrect), or show bias or linguistic toxicity where the starting data is not sufficient or adequately “clean”. Furthermore, working with AI models at scale is not at all trivial: many start-ups and entrepreneurs initially try a successful idea, but struggle to implement it on an infrastructure capable of supporting real workloads, with adequate governance measures and risk management strategies. It is crucial to adopt consolidated best practices, structure competent teams, define a solid operating model and a continuous maintenance plan for the system.

The Role of Generative AI in Supporting Business Decisions

One aspect that I find particularly interesting is the support that AI offers to business decisions. Algorithms can analyze a huge amount of data, simulating multiple scenarios and identifying patterns that are elusive to the human eye. This allows to mitigate biases and distortions – typical of exclusively human decision-making processes – and to predict risks and opportunities with greater objectivity.

At the same time, I believe that human intuition must remain key: data and numerical projections offer a starting point, but context, ethics and sensitivity towards collaborators and society remain elements of human relevance. The right balance between algorithmic analysis and strategic vision is the cornerstone of a responsible adoption of AI.

Industries Where Generative AI Is Transforming Business

As a professor of Responsible Artificial Intelligence and Digital Business & Innovation, I often see how some sectors are adopting AI extremely quickly. Many industries are already transforming rapidly. The financial sector, for example, has always been a pioneer in adopting new technologies: risk analysis, fraud prevention, algorithmic trading, and complex document management are areas where generative AI is proving to be very effective.

Healthcare and life sciences are taking advantage of AI advances in drug discovery, advanced diagnostics, and the analysis of large amounts of clinical data. Sectors such as retail, logistics, and education are also adopting AI to improve their processes and offer more personalized experiences. In light of this, I would say that no industry will be completely excluded from the changes: even “humanistic” professions, such as those related to medical care or psychological counseling, will be able to benefit from it as support, without AI completely replacing the relational and care component.

Integrating Generative AI into the Enterprise: Best Practices and Risk Management

A growing trend is the creation of specialized AI services AI-as-a-Service. These are based on large language models but are tailored to specific functionalities (writing, code checking, multimedia content production, research support, etc.). I personally use various AI-as-a-Service tools every day, deriving benefits from them for both teaching and research. I find this model particularly advantageous for small and medium-sized businesses, which can thus adopt AI solutions without having to invest heavily in infrastructure and specialized talent that are difficult to find.

Of course, adopting AI technologies requires companies to adopt a well-structured risk management strategy, covering key areas such as data protection, fairness and lack of bias in algorithms, transparency towards customers, protection of workers, definition of clear responsibilities regarding automated decisions and, last but not least, attention to environmental impact. Each AI model, especially if trained on huge amounts of data, can require significant energy consumption.

Furthermore, when we talk about generative AI and conversational models , we add concerns about possible inappropriate or harmful responses (so-called “hallucinations”), which must be managed by implementing filters, quality control and continuous monitoring processes. In other words, although AI can have disruptive and positive effects, the ultimate responsibility remains with humans and the companies that use it.

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