Will AI Replace Cybersecurity?

Artificial intelligence (AI) holds great potential within cybersecurity. However, like any technology, the emerging risks associated with AI must be carefully analyzed to minimize security threats. While AI has a variety of potential risks, it’s important to also understand its potential benefits and how cybersecurity professionals can collaborate with AI to implement more efficient and safer cybersecurity.

Expand your knowledge on how AI and cybersecurity professionals can collaborate and learn more about the potential advantages and disadvantages of utilizing AI in cybersecurity.

What is the impact on cybersecurity roles?

The threat of job displacement for cybersecurity professionals is currently an improbable concern. While artificial intelligence has reshaped the cybersecurity industry, it still has constraints based on the data it’s trained on. Humans are necessary when analyzing data because AI does not possess the critical thinking and contextual understanding that humans do. 

Limitations of AI in cybersecurity

Organizations will not completely remove the human element from cybersecurity strategies because AI still lacks contextual awareness and is susceptible to bias. Although AI is becoming an essential element of cybersecurity, cybersecurity professionals still need to guide its learning paths, confirm data analysis, and protect software, data sets, and networks. Although AI can help support a robust cybersecurity strategy, it cannot replace cybersecurity professionals. 

Automation of threat detection

AI-powered automated threat detection enables cybersecurity professionals to accelerate threat identification, streamline response times, and efficiently safeguard user identities and data sets. 

AI capabilities in threat detection

AI can automate the detection and response to cybersecurity threats by identifying shadow data, monitoring abnormal data access patterns, and alerting professionals about potential breaches or unauthorized access to confidential information. Since AI operates in real time, this process will save cybersecurity professionals time and resources, enabling them to identify and resolve security issues quickly.

Effectiveness of AI in cybersecurity

Generative AI (GenAI) and machine learning (ML) tools offer new and more efficient ways to implement cybersecurity strategies. 

AI-driven security solutions 

AI has proven to benefit many organizations when integrated into their cybersecurity strategies. A couple of examples of AI’s success in cybersecurity solutions include the following: 

• According to an article by the University of West Florida, a top US bank incorporated AI into its cybersecurity efforts after learning it was spending too much time investigating illegitimate alerts. Analysts spent an immense amount of time investigating false positives since only three out of 900 alerts were legitimate. After implementing AI, the analysts’ workload was significantly reduced since the AI could immediately determine whether the alert was valid [1]. 

• Doosan Digital Innovation (DDI), a manufacturing company, implemented IBM’s AI-powered security protection to ensure the company would be safe from hackers and scammers. “It takes only one successful hacking attempt to compromise your company. Or even just one non-malicious action by an employee, like clicking on a link they shouldn’t have. And once that back door is open and they’re inside, most companies don’t know they’ve been compromised for over a month. That’s a lot of time to cause some damage. With IBM, we now have an accurate 24-hour view of the world in real-time,” states Robert Oh, Chief Operating Officer (COO) at DDI [2].

Future skills required for cybersecurity professionals

AI is transforming cybersecurity professions as it becomes increasingly integrated into the field. This shift will redefine the responsibilities of cybersecurity professionals, creating new roles and skills required to assimilate into the industry.

Skills in an AI-driven landscape

Cybersecurity experts' points of interest will shift as AI takes over the cybersecurity industry. Skills and necessary responsibilities of cybersecurity professionals in an AI-driven landscape include:

• Monitoring the operation of AI 

• Applying ethical standards

• Implementing policies and creative thinking

• Developing strategies 

• Applying negotiation tactics 

• Addressing the motive of attackers 

Importance of continuous learning

While AI will continue to quickly and efficiently address cybersecurity threats, these threats will become more prevalent as AI evolves. Cybersecurity experts must stay educated about AI's potential threats while leveraging it to their advantage and preparing for the profession's future.

Ethical and privacy concerns

As more companies embrace AI, the risk of potential data breaches and hackers' exploitation increases. Examine some potential concerns to gain a deeper understanding. 

Ethical implications of AI in cybersecurity

Bias and discrimination are essential to consider as potential limitations when utilizing AI in cybersecurity. If you train an AI model on historical data, the model may inadvertently perpetuate biases and discriminate against certain groups based on race, gender, or other attributes. This could result in the users’ lack of trust in AI models. 

Data privacy and security challenges

• Data poisoning: Hackers can “poison” AI training data, enabling them to influence the AI's decisions. If scammers train an AI model on deceptive information, it could potentially disseminate false information to its users. 

• Data leakage: If a hacker transfers an AI model to a third party, they could reverse engineer it to extract confidential data. AI hackers could trick the AI into exposing sensitive data, including medical records or financial information.

• Deepfakes: Hackers are utilizing AI technologies to impersonate people. In short, AI models can replicate a person's voice and face. Cyberattackers exploit these capabilities to target large corporations, often for financial gain. 

Industry trends

Cybersecurity experts rely on AI in fraud detection, risk management, data loss protection, antivirus protection, and various other security sectors. 

Current trends in AI adoption

As AI evolves, it is increasingly used for elements such as:

• Detecting attacks with more accuracy than humans 

• Identifying and reporting suspicious activity in phishing

• Simulating social engineering attacks to train security teams 

• Quickly analyzing massive amounts of data

• Implementing multi-factor authentication (MFA) and encryption

• Adopting blockchain technologies

Future outlook for cybersecurity and AI

Utilizing AI within cybersecurity will allow organizations to predict and prevent future attacks. Hackers will become more prevalent as AI evolves, but AI will also become better at implementing solutions to prevent attacks. New technologies and strategies will emerge to help organizations protect their data from cyberattacks, so professionals need to stay informed about new technologies as they come to fruition. 

Getting started on your AI in cybersecurity journey with Coursera

AI and cybersecurity professionals collaborate well to prevent cyber attacks, and AI advancements will continue to benefit and hinder the industry in various ways as it evolves. Learn more about cybersecurity and generative AI implementations with the IBM Generative AI for Cybersecurity Professionals Specialization, or expand your understanding of cybersecurity practices with the Google Cybersecurity Professional Certificate.