Cybersecurity and AI: A Changing Landscape
Written by:
University of Tulsa
• Dec 13, 2023
The threat cyber attacks pose to companies’ systems and services continues to grow, along with the costs associated with these attacks. In 2025, an IBM survey found that the average cost of a global data breach was $4.4 million, with 97% reporting security incidents related to artificial intelligence (AI) and a lack of proper AI access controls.
Part of the reason these attacks pose such a grave threat is the increasing sophistication of hackers’ tactics, which includes the use of artificial intelligence in cybersecurity. However, while innovations in AI are providing cybercriminals with new ways to commit malicious acts, they are also creating opportunities for companies to protect themselves.
The benefits of AI in cybersecurity have been enticing enough for a number of companies to invest, with a report from Fortune Business Insights finding that global spending on artificial intelligence in cybersecurity reached $34.09 billion in 2025.
The increasing role of cybersecurity and AI means that professionals who know how to get the most out of these technologies are leading the efforts to keep companies’ networks safe. Pursuing a graduate degree in cybersecurity can help individuals stay on top of industry trends, such as the interplay between cybersecurity and AI, and develop the skills and expertise they need to advance their careers.
What Is Artificial Intelligence?
Artificial intelligence is a simulation of human intelligence by machines, which use various methods but often make algorithm-based decisions based on a large set of data. In the cybersecurity landscape, interest in AI has surged recently, becoming a central topic of discussion across industries.
Among the many different types of cybersecurity challenges facing organizations, AI’s rapid development and adoption have made it a key concern for many businesses and cybersecurity professionals. AI’s growing prominence can be partially attributed to the emergence of generative AI, which has garnered significant attention from the public and businesses.
What Is Generative AI?
Generative AI refers to AI models that can create seemingly novel content, including text, images, and music, based on patterns and examples provided during the model’s training. Platforms such as ChatGPT represent one of the fastest-growing areas at the intersection of cybersecurity and AI, and have gained recognition for their ability to generate humanlike responses. These systems employ deep learning algorithms that analyze vast amounts of data to find patterns and then generate seemingly coherent and contextually relevant responses to a user’s inputs.
Generative AI Challenges and Misconceptions
While generative provides the most acceptable outputs for particular prompts based on its training, it is incapable of checking those for accuracy. It does not pull information from a memory bank or directly from the internet. Instead, it chooses the most likely series of responses based on the input context in relation to patterns it learned during its training.
As a result, generated responses may not reflect up-to-date data or may give incorrect or uncanny responses to user inputs, regardless of the AI model’s certainty in its accuracy. Because of this, using generative AI to create code requires a professional to oversee and potentially fix outputs to ensure that they don’t contain errors.
Scraping data and collecting material can also raise concerns around cybersecurity ethics. Many artists, creatives, and businesses cite copyright infringement as a significant AI challenge and are looking to block AI platforms from training using their material without permission.
AI in Cybersecurity Today
Understanding AI technology is paramount for cybersecurity professionals. As AI advances, cybercriminals can use its capabilities to develop increasingly sophisticated attack techniques, posing new challenges in the cybersecurity landscape.
AI-driven cyber attacks represent a growing concern. Cybercriminals are using AI algorithms and machine learning techniques to automate their attack processes, enabling them to launch large-scale and highly targeted attacks with minimal human effort. These AI-driven attacks exhibit adaptive and evasive behaviors, making them difficult to detect and mitigate using traditional security measures.
The emergence of AI-driven cyber attacks has significantly increased the demand for skilled professionals in the cybersecurity landscape, particularly those with AI expertise. Organizations need professionals who possess a deep understanding of AI technology and its potential applications in cybersecurity to meet modern AI challenges. Armed with this expertise, these professionals can analyze AI-driven attack patterns, develop advanced defenses, and implement strategies to counter evolving cybersecurity and AI threats.
AI Risk Framework Development
Cybersecurity professionals are constantly training and developing their skills to keep up with the latest challenges and risks. One way many professionals tackle breaches within cybersecurity and AI is by implementing AI risk frameworks.
Risk frameworks are structured sets of guidelines, processes, and tools that cybersecurity professionals use to identify and manage AI risks within security systems. Associations like the National Institute of Standards and Technology (NIST) have developed AI risk management frameworks that both public and private companies can use. For organizations that prefer to implement their own frameworks, skilled cybersecurity professionals can develop customized programs and systems to mitigate risk.
AI-Driven Threats in the Cybersecurity Landscape
As AI becomes more accessible, cybercriminals are finding innovative ways to exploit its capabilities, leveraging it to launch sophisticated attacks.
Despite the need for human oversight to ensure malicious code functions properly and obscures hackers’ identities from authorities, the level of automation that AI allows can enable cybercriminals to launch large-scale, coordinated attacks that they otherwise may not have had the skill or capacity to pull off. These attacks can compromise networks, steal sensitive information, or damage critical infrastructure, significantly disrupting the cybersecurity landscape.
AI-Assisted Cyber Attacks
AI-powered “botnets” are falsified or compromised network-connected accounts and devices that all act on the orders of the infecting malware. These bots can coordinate distributed denial-of-service (DDoS) attacks that overwhelm their targets through repeated attempts to access their systems. Coordinated DDoS attacks can trigger an entire system to shut down, causing service disruptions and incurring high financial costs until cybersecurity professionals can return the system to normal.
As artificial intelligence in cybersecurity evolves, hackers have been able to use AI to bypass traditional cybersecurity defenses. Adversarial machine learning techniques allow attackers to manipulate AI models and exploit vulnerabilities in their decision-making processes. By feeding malicious inputs into AI systems, attackers can deceive them into making incorrect decisions.
Phishing
Another emerging concern regarding cybersecurity and AI is the use of generative AI models to create realistic fake content, such as deepfakes or phishing emails that appear authentic and can be used to deceive individuals or organizations. As it becomes increasingly challenging to distinguish between genuine and malicious communications, the number of hackers attempting to trick individuals into revealing sensitive information or compromising their security is likely to rise.
Phishing attacks are already one of the most common methods of cyber attack, with the Cybersecurity and Infrastructure Security Agency reporting that more than 90% of cyber attacks begin with a successful phishing scheme. Generative AI can make phishing emails seem even more legitimate, making it one of the top areas of concern in the realm of cybersecurity and AI.
Concerns over phishing are particularly noteworthy as more employees move to remote work, which often means the devices they use to interface with a company’s secure network may not be as heavily secured, creating unintended backdoors for hackers.
AI Challenges for Cybersecurity Professionals
Other areas of concern for cybersecurity professionals stem from the potential challenges companies face due to their increasing reliance on AI for decision-making in critical systems. If attackers gain unauthorized access to an AI-driven system or manipulate the system’s training data, they can introduce biases or cause it to make incorrect decisions.
For example, a cyber attack that manipulates AI algorithms in autonomous vehicles or critical infrastructure could have devastating consequences, leading to accidents or infrastructure failures. Examples like these showcase how the unquestioning adoption of AI systems into more aspects of everyday life can create vulnerabilities and AI challenges, highlighting the increasing importance of cybersecurity professionals in a range of industries.
AI Benefits to the Cybersecurity Landscape
While AI introduces new challenges across the cybersecurity landscape, it also offers valuable tools and solutions that cybersecurity professionals can use to mitigate attacks.
Improved Threat Detection
AI in cybersecurity can bolster threat and anomaly detection. AI models can analyze vast amounts of data from various sources, including network logs, user behavior, and system events, to identify patterns indicative of potential attacks.
AI can also automate routine and time-consuming tasks, enabling cybersecurity teams to focus on more complex and critical activities. For instance, AI can automate the analysis of security alerts, reducing the burden on analysts and allowing them to allocate their time and expertise to investigating and responding to high-priority incidents.
By monitoring various sources, including social media sites and dark web forums populated by hackers, AI-powered systems can identify emerging threats, trends, and indicators of malicious activity without human intervention.
Improved Defenses and Response Time
AI tools can analyze and correlate data in real time, providing security teams with actionable insights and context during an ongoing security incident. By quickly identifying the scope and severity of an attack, cybersecurity professionals can respond promptly, implement the necessary containment measures, and minimize the impact of a breach.
AI-powered systems can also identify potential vulnerabilities and prioritize them based on their severity and potential impact by analyzing various aspects of a system, the code that makes it function, and historical data. This prioritization enables organizations to focus on promptly addressing the most critical vulnerabilities, reducing the window of opportunity for attackers.
Cybersecurity experts can also employ AI in user behavior analytics (UBA) to check unusual or unexplained user activities to determine if they’re cyber threats.
The Importance of Continuous Cybersecurity Education
As more opportunities arise to combine cybersecurity and AI tools, cybersecurity professionals with artificial intelligence expertise will be increasingly important across industries. In such a rapidly evolving field, staying up to date with the latest AI-driven threats, vulnerabilities, and defense mechanisms is essential. Ongoing learning allows cybersecurity professionals to adapt their strategies and stay ahead of cybercriminals who use AI for malicious purposes.
Professionals can expand their expertise and career opportunities through further education that builds upon their specialized knowledge and skills. Additionally, ongoing education helps professionals understand the ethical implications of AI in cybersecurity, enabling them to navigate complex issues as they use and implement AI technologies.
Advance Your Career in Cybersecurity
As AI becomes increasingly sophisticated, cybercriminals can use its capabilities to launch more sophisticated attacks, presenting a formidable threat to individuals and companies alike. However, AI also offers valuable solutions for cybersecurity professionals, enabling them to detect and respond to threats more effectively, automate routine tasks, and stay ahead of evolving attack methods.
Career success in cybersecurity and AI will increasingly require the ability to navigate the complexities of attacks and defenses. Pursuing an advanced education like the online Master of Science (M.S.) in Cyber Security program at The University of Tulsa (TU) can help you develop crucial and advanced expertise.
TU’s program prepares cybersecurity professionals to shape their companies’ defense strategies, including how they approach AI-driven threats and how they use AI in their defenses. With courses covering cybersecurity policy, defensive technologies, and secure system administration, the program teaches the foundations of cybersecurity.
Find out how The University of Tulsa can help you lead cyber defense in the age of AI.
Recommended Readings
AI and Access Security: How It’s Changing the Industry
Cybersecurity Law: What Professionals Should Know
How to Choose Between a Cybersecurity Bootcamp vs. a Degree
Sources:
Cybersecurity & Infrastructure Security Agency, General Information
Cybersecurity & Infrastructure Security Agency, Malware, Phishing, and Ransomware
Cybersecurity & Infrastructure Security Agency, Shields Up: Guidance for Families
Fortinet, “What Is Behavioral Analytics?"
IBM, Artificial Intelligence (AI) Cybersecurity
IBM, Cost of a Data Breach Report 2025
McKinsey & Co., What Is Generative AI?
National Institute of Standards and Technology, AI Risk Management Framework
