Master’s in Cybersecurity: What Will Your Salary Be?

Mar 18, 2024 • 7 min read

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Cyberthreats keep evolving at an unprecedented rate, affecting critical digital infrastructure across industries. Worst of all? No one’s safe. Not healthcare providers, not financial institutions, and not even government agencies. That’s why it shouldn’t be surprising that the demand for cybersecurity professionals is also unprecedented, with over 347,000 positions waiting to be filled throughout Europe.

Naturally, such high demand comes with competitive salaries for highly trained and educated individuals. So, if you’re pursuing a master’s degree in cyber security, salary expectations are undoubtedly promising, often reaching six figures.

In other words, investing in a master’s degree in cyber security is investing in a financially secure future.

But just how secure will this future be? Keep reading to learn what the master’s in cybersecurity salary expectations are.

How Much Can I Make With a Master’s in Cybersecurity?

Given how desperately companies need qualified cybersecurity professionals, they do their best to make their offers as attractive as possible. That’s why the average salary for a master’s degree in cyber security is roughly €73,000 a year.

In the U.S., the situation is even better, with the average salary as high as $132,962 (around €123,000) a year. This is great news, as virtually all cybersecurity job positions can be done fully remotely.

As for a salary range, top earners make over €100,000 a year in countries like Luxembourg, Belgium, and Switzerland. Entry-level positions typically start at €30,000. This discrepancy clearly shows that years of experience play a significant role in determining the cybersecurity master’s salary. But this factor is far from the only one.

The location of the job, the specific industry (private or public sector), and the level of responsibility also heavily influence compensation in the cybersecurity field.

With these elements, the math is simple. Countries with higher demand for cybersecurity professionals (e.g., Germany) will generally offer higher salaries. The same goes for industries, such as finance and technology, which pay better than government jobs. But what about the level of responsibility? How does your cybersecurity role affect your salary?

The good news is that those who hold a master’s degree can earn a six-figure salary even if they aren’t in a leadership position. Let’s break down the average master’s in cyber security salary expectations for the most common roles in cybersecurity.

Information security analyst: €100,000
Cybersecurity manager: €105,000
Cybersecurity engineer: €125,000
Incident response manager: €125,000
Penetration and vulnerability tester: €125,000
Cybersecurity consultant: €140,000

Can I Make 200k a Year in Cybersecurity?

If you’re looking for a yes or no answer, it’s yes, you can make €200,000 a year in cybersecurity. But since this figure is missing from the median salaries shown in the previous section, you can probably conclude that a €200,000 yearly salary isn’t the norm for every cybersecurity professional.

So, what does it take to earn this impressive figure?

The “easiest” way to such a high cybersecurity master’s degree salary is through a leadership position. For instance, Chief Information Security Officers (CISOs) are all but guaranteed a salary over €200,000, even when working in mid-sized companies. The same goes for the lead software security engineer.

Another factor that can contribute to such a lucrative pay is location. Working for a U.S. company in a high-demand area is more likely to get you your desired salary. For instance, for New York City and Los Angeles master’s in cyber security jobs, salary often reaches €200,000 due to a high demand for skilled cybersecurity professionals.

Finally, specialized roles that call for niche expertise, such as application security engineer, can also command a €200,000 salary.

As you can see, all the highest-paid positions require a Master of Science in cybersecurity. Salary expectations for a Bachelor of Science and other lower-level certifications in cybersecurity usually fail to hit the €200,000 mark.

Can You Make 500k a Year in Cybersecurity?

Again, the short answer is yes, you can make €500,000 a year in cybersecurity. But keep in mind that this salary is reserved only for exceptional scenarios and individuals, such as the following:

Cybersecurity professionals in extremely niche expertise areas (e.g., disaster recovery and application security)
Leadership roles within large multinationals or Fortune 500 corporations
Cybersecurity consultants for high-end clients
Entrepreneurs working on cybersecurity solutions and products

The Investment in Education vs. Return on Salary

There’s no doubt about it – cybersecurity is a highly lucrative field. But to earn the highest possible salary in the field, you’ll need one of the highest degrees of education – a master’s degree. Of course, this degree won’t be affordable if you want it to come from a highly reputable institution. So, is a master’s degree in cybersecurity even worth it?

The answer is a resounding yes!

Let’s do the math.

The simplest 10-year return-on-investment (ROI) calculation looks like this:

(expected annual salary post-master’s x 10) – (annual salary pre-master’s x 10) – (the total tuition for the master’s degree)

Let’s say you’re pre-master’s annual salary is €30,000 and your goal post-degree is a €75,000 salary. For tuition, we’ll use €6,750, which is the cost of the highly coveted Master’s Degree in Enterprise Cybersecurity at the Open Institute of Technology (OPIT.)

After crunching the numbers, you’ll see that the ROI from a cybersecurity master’s from OPIT is over €440,000.

That’s not to mention all the possibilities for advancement within the field and the possibility of working for U.S. companies, which are known to pay significantly more than most European companies.

OPIT’s Master’s Degree (MSc) in Enterprise Cybersecurity: Positioning for High Salaries

The potential ROI from an OPIT master’s degree is a reason enough to pursue a Master’s Degree in Enterprise Cybersecurity. Still, let’s explore how this reputable institution positions its students for such high salaries.

At OPIT, you won’t just work on your technical skills. You’ll also acquire a lot of valuable managerial expertise that allows you to pursue a variety of high-paying roles within the cybersecurity landscape. After all, you can’t get to the CISO position without mastering the intersection of technology and management.

On top of this perfect blend of knowledge, OPIT gives you a chance to gain real-world project experience while studying. This means that you’ll be ready to take on virtually any role in cybersecurity from day one. No extensive training needed!

Here are just some of the roles an OPIT master’s degree can prepare you for:

CISO
Cybersecurity director
Security solutions architect
Cybersecurity risk analyst
Incident response manager
Cybersecurity compliance officer

Aim for Long-Term Success

With a master’s degree in cyber security, salary expectations rise beyond the industry average, which is already more than competitive. Of course, this degree should come from a prestigious institution like OPIT. Why? This is the only way to achieve top-tier salary benchmarks wherever you end up working.

So, if you’re looking for a long-term career that offers financial stability and growth, don’t think twice about applying for OPIT.

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Il Sole 24 Ore: Integrating Artificial Intelligence into the Enterprise – Challenges and Opportunities for CEOs and Management
OPIT - Open Institute of Technology

April 14, 2025
Source:
- Il Sole 24 Ore, published on April 14th, 2025
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.

“CEOs who already work with AI – explains the OPIT expert – see the investment in compliance as necessary, the latter as an opportunity: and the latter, on paper, have the advantage of being able to define a strategy also in terms of ethics and civil responsibility”

SMEs in greater difficulty

There is a further theme that accompanies the diffusion of AI in the European corporate fabric and that is the difference in “approach” between large companies and SMEs. The top executives of enterprise-class organizations, as Casale confirms, have budgets and resources to adequately address and manage the challenge of compliance. Small and medium-sized businesses, on the other hand, are in a waiting position to understand how to carry forward the development process and the risk that many may slow down in the innovation path, and that a conservative attitude towards the use of artificial intelligence prevails, is clear.

Lastly, no less important is the issue of skills, which is very much felt in both the technical and legal fields. “The skills and requirements of AI Engineers and Data Scientists, with all their variations on the theme, are now defined and it is clear – Casale assures – that there is a strong increase in demand. However, I am of the opinion that there cannot be training that is only engineering-based or focused solely on regulatory aspects: instead, we need paths that combine the two dimensions and that lead to preparing the new Chief AI Officers, that is, high-level responsibility figures called to govern all activities related to the use of artificial intelligence”. Nonetheless, according to the expert, we need a layer of specialists who study the impacts and implications of technology on society, anticipating possible risks.

Old universities are not enough

In conclusion, it remains to be asked whether Italy is up to speed in meeting this need, and in this regard Casale’s answer is once again precise and transparent: “Old-style universities can no longer be functional for this purpose, because we need to understand how to teach a new mindset and not a technology as such, given the speed of its evolution. We are in the midst of a phase of great change and evolution towards dynamic study paths, and in other European countries this transformation has already begun”. In the meantime, artificial intelligence continues on its course and suggests that it will not be a passing fad. On the contrary. “AI – concludes the OPIT professor – exists and is here to remain a protagonist: to teach it and bring it to the ground in an adequate way, correct governance of the technology is necessary and the AI Act is an important first step in this direction. But there is still a lot of work to do”.

Read the full article below (in Italian):
- Il Sole 24 Ore
Check out OPIT degrees

BSc in Digital Business MSc in Digital Business and Innovation MSc in Responsible Artificial Intelligence MSc in Applied Data Science and AI MSc in Data Science & AI MSc in Data Science & AI MSc in Data Science & AI MSc in Data Science & AI MSc in Data Science & AI MSc in Data Science & AI
- Career aligned
- Fully Online
- EU-accredited institution
Read the article
The Lucky Future: How AI Aims to Change Everything
OPIT - Open Institute of Technology

April 10, 2025
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.
Check out OPIT degrees

MSc in Digital Business and Innovation MSc in Responsible Artificial Intelligence MSc in Applied Data Science and AI MSc in Data Science & AI MSc in Data Science & AI MSc in Data Science & AI MSc in Data Science & AI MSc in Data Science & AI MSc in Data Science & AI MSc in Data Science & AI
- Career aligned
- Fully Online
- EU-accredited institution
Read the article
Categories
Authors

Francesco Profumo

John Loewen

Professor @OPIT, PhD in Computer Science, Former Professor @Chulalongkorn University and @Vancouver Island University. Location: Italy Teaches Computer Architectures (BSc).

Karim Bouzoubaa

Professor @ OPIT, Professor of Data Science & AI @ Mohammed V University in Rabat, PhD @ Laval University. Location: Canada, Morocco. Teaches Programming courses (BSc).

Khaled Elbehiery

Professor @ OPIT, Senior Director & Network Engineer @ Charter Communications, Professor @ DeVry University and @ Park University. Location: USA. Teaches: Computer Networks (BSc).

Lokesh Vij

Professor @ OPIT, Software Engineer @ Symantec, Faculty @ Seneca College. Location: Canada. Teaches Cloud Computing courses (BSc), Big Data and Cloud Computing Infrastructure (MSc).

Go to all authors

Il Sole 24 Ore: Integrating Artificial Intelligence into the Enterprise – Challenges and Opportunities for CEOs and Management

OPIT - Open Institute of Technology

Apr 14, 2025 • 6 min read

Source:

Il Sole 24 Ore, published on April 14th, 2025

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.

“CEOs who already work with AI – explains the OPIT expert – see the investment in compliance as necessary, the latter as an opportunity: and the latter, on paper, have the advantage of being able to define a strategy also in terms of ethics and civil responsibility”

SMEs in greater difficulty

There is a further theme that accompanies the diffusion of AI in the European corporate fabric and that is the difference in “approach” between large companies and SMEs. The top executives of enterprise-class organizations, as Casale confirms, have budgets and resources to adequately address and manage the challenge of compliance. Small and medium-sized businesses, on the other hand, are in a waiting position to understand how to carry forward the development process and the risk that many may slow down in the innovation path, and that a conservative attitude towards the use of artificial intelligence prevails, is clear.

Lastly, no less important is the issue of skills, which is very much felt in both the technical and legal fields. “The skills and requirements of AI Engineers and Data Scientists, with all their variations on the theme, are now defined and it is clear – Casale assures – that there is a strong increase in demand. However, I am of the opinion that there cannot be training that is only engineering-based or focused solely on regulatory aspects: instead, we need paths that combine the two dimensions and that lead to preparing the new Chief AI Officers, that is, high-level responsibility figures called to govern all activities related to the use of artificial intelligence”. Nonetheless, according to the expert, we need a layer of specialists who study the impacts and implications of technology on society, anticipating possible risks.

Old universities are not enough

In conclusion, it remains to be asked whether Italy is up to speed in meeting this need, and in this regard Casale’s answer is once again precise and transparent: “Old-style universities can no longer be functional for this purpose, because we need to understand how to teach a new mindset and not a technology as such, given the speed of its evolution. We are in the midst of a phase of great change and evolution towards dynamic study paths, and in other European countries this transformation has already begun”. In the meantime, artificial intelligence continues on its course and suggests that it will not be a passing fad. On the contrary. “AI – concludes the OPIT professor – exists and is here to remain a protagonist: to teach it and bring it to the ground in an adequate way, correct governance of the technology is necessary and the AI Act is an important first step in this direction. But there is still a lot of work to do”.

Read the full article below (in Italian):

Il Sole 24 Ore

Read the article

The Lucky Future: How AI Aims to Change Everything

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.