What if we told you that the average number of weekly attacks on organizations grew by 58%? The bad news is that it's affecting every sector, such as healthcare, finance, energy, and ecommerce alike.
From ransomware attacks shutting down entire systems to phishing emails that steal sensitive information, vulnerabilities are growing at a rapid pace. Traditional security systems and human oversight simply can't keep up with these evolving complexities.
Meanwhile, cyberattackers have started leveraging AI and ML to penetrate IT environments with sophisticated threats. With the emergence of IoT, devices are increasingly interconnected, making it harder to predict where the next vulnerability will arise.
This interconnectivity means that any weak link can compromise the entire system.
That's why adopting Artificial Intelligence in cybersecurity isn't a nice-to-have option; it's a must-have necessity.
In this blog, we'll take a deep dive into why you should integrate AI in cybersecurity, the benefits it provides, popular AI-based cybersecurity tools, and best practices to create an AI-based cybersecurity strategy in 2025 and beyond.
Why It's Important to Integrate Artificial Intelligence in Cybersecurity
Cybersecurity threats are rising. Over the past four years, the number has almost doubled (from 818 in Q1 2021 to 1,984).
The average number of weekly attacks has reached 1,984, which is 58% higher than two years ago.
But these cyberattacks have been seen in every region and across every industry, of which education has become the most targeted sector, which has received a sheer volume of security attacks.
Reason? That's because of weak security measures, which result in access to sensitive information of staff and students.
This means your organization needs to have a substantial security budget to beat these emerging threats in the global economy.
But if you're still relying on human resources and conventional security systems to beat these ransomware and phishing attacks, then you would be highly vulnerable to such threats.
The only way to prevent your enterprise from such bad actors is to "think outside the box" and invest in Artificial Intelligence to become more vigilant in such a battle.
According to R Ray Wang, founder and principal analyst at Constellation Research:
Artificial Intelligence is transforming the way business leaders run their IT-related and other operations.
Best part? This emerging technology offers a sheer range of benefits, like scanning information and threat detection at a much higher speed that humans simply can't compete with.
Just like every coin has two sides, cybercriminals (bad guys) have been using AI to overcome the world's most obvious cybersecurity defences.
Organizations must make AI part of their strategy for analyzing huge amounts of data at scale and responding to threats instantly.
To combat data breaches, security teams have shifted from static detection (looking for viruses in files) to behavioral analytics (analyzing what malicious software can do).
What Are the Benefits of AI in Cybersecurity?
As attackers have been using automation to disrupt traditional security measures, AI has become an essential tool for enterprises to identify vulnerabilities and threats.
Let's talk about the benefits of integrating AI-enabled technologies in Cybersecurity:
1. Identification of Security Threats in Early Stages
Early detection of cyber threats is important to prevent costly data breaches and protect the reputation of the company that takes years to build.
Still, many organizations rely on security analysts to oversee the monitoring of logs and network traffic to detect any suspicious activity. While they do so, the process takes them hours to find the patterns and detect whether the breach is going to happen.
Even if they found 1,000 alerts, then it would not be possible for a human eye to notice every single pattern of threat.
But Artificial Intelligence can become a great tool for the cybersecurity team as it's good at reading, monitoring, and scanning hundreds and thousands of such patterns.
These can be gaining unauthorized access to sensitive information, abnormal user behavior, or unusual traffic coming to the site.
Then AI can help you create a culture of security by detecting threats in the earliest stages that can go unnoticed by a human eye and can cause disruption in existing IT processes.
2. Improves Vulnerability Management
Artificial Intelligence is not just good at detecting new threats; it has become "all eyes and ears" for the security team. When organizations know these are the weak areas that hackers can target first, they become more proactive in fixing the dangerous issues first.
"The scope of Artificial Intelligence in cybersecurity has evolved. Their team started using AI in the early phases since the 2000s, but now its use case has gone beyond just anomaly detection."
He further said, "Instead of just looking for every possible threat, their team identified the most important threats that needed immediate attention. This way, their team was able to allocate resources for fixing the most important vulnerabilities."
Today, AI-powered cybersecurity tools have come up to improve the vulnerability management process in such a way that they can scan a higher number of threats in the codebase.
For instance, AI detects that the most common threats in the codebase are SQL injections and cross-site scripting.
This way, its algorithms will learn over time, and as it's trained on a huge amount of data, it can even predict the unknown probabilities that can happen in the future.
Those are the threats that security engineers are yet to identify.
The traditional threat mitigation process works in a way that if a threat or incident happens, the security analysts will review it manually, such as reviewing the system logs and data traffic, and then implement corrective measures.
But detecting threats and finding resolutions takes time as the analyst needs to understand the scope of the incident, analyze the damage that the attack can create, and then work on preventing the spread of that attack.
With AI-enabled threat detection systems, threats can be resolved in real time as AI provides automated responses to threats, such as isolating the affected systems or blocking malicious traffic.
This means your security team does not have to scan hundreds of alerts; rather, it will help them to make decisions based on real-time insights and recommendations.
4. Cost Efficiency
Deploying traditional security measures involves significant infrastructure investment such as hardware, software, and licensing costs. But AI-driven solutions can be integrated with existing IT infrastructure, so they can be deployed quickly.
Not just that, the pairing of AI with cybersecurity gives economic benefits (cost savings); it can also respond to threats faster than a human could.
The increasing reliance on AI-driven security systems means the activities that security teams used to perform earlier, such as log analysis, monitoring, threat detection, and responding to threats, can now be done with greater accuracy.
How Different Industries Are Using AI for Cybersecurity
Artificial Intelligence is no longer the buzzword today; it has become the talk of the town. Today, it has become a strategic enabler for every industry, such as finance, retail, healthcare, and government.
1. Finance
As cyber threats are rising, the banking and financial industry has become a targeted segment for scammers and fraudsters. These industries are appealing to them as they deal with high-value information such as customer records and other financial information.
A study from Juniper Research states that online payment fraud in the payment industries is expected to go beyond $362 billion in 2028.
And AI in Finance is helping the financial service industry, especially in the areas of fraud detection and prevention. The sad truth is that hackers have become super smart in using AI to create better things, such as ransomware messages or convincing phishing emails to trick people.
While the traditional security systems just focus on detecting threats by analyzing known patterns.
But Artificial Intelligence can spot the patterns based on behavior or unusual activity. As they can identify the behavioral patterns, this one feature makes it different from old security systems.
For instance, if an employee account starts transferring millions of dollars of funds at 3 AM tonight, then the benefit of AI in cybersecurity is that it will flag the transaction as suspicious.
2. Healthcare
Just like other sectors, the healthcare industry reports the maximum number of data breaches. Studies state that healthcare breaches have increased by 3x from 216 to 745 during the period of 2010-2023.
Think of it this way: just like for financial firms, user IDs and passwords have been considered immutable records. Similarly, for healthcare institutions and hospitals, patients' medical information is vital.
Once these data breaches occur, they cause emotional distress among patients and healthcare providers. With the digitalization of healthcare records, you need to create an AI in Healthcare -enabled cybersecurity strategy.
Unlike traditional security methods that react after an attack, AI can scan massive amounts of data from hospital networks. It scans for threats before they happen by looking for patterns and abnormalities such as unusual login attempts or unauthorized access to EHRs.
Through Artificial Intelligence, healthcare organizations can shift away from the "watch and wait" mindset, meaning they can ingest huge amounts of healthcare data in real time.
If there's any suspicious attempt or unauthorized login to healthcare systems, then AI will block suspicious accounts or isolate such systems.
Result = Faster response times result in better treatment decisions.
3. Ecommerce
The ecommerce sector has become the favorite point for cybercriminals. Supposedly, you developed an online store, your website loads quickly, and customers started signing up for your products/services.
But what if a hacker tries to hack your basic login system and steal your customers' sensitive information? Would that mean that your online stores need an extra layer of protection?
Today, cybercriminals have become super smart, and they love using AI technology for attacking your systems.
That's where you need a watchdog, aka a 24/7 AI-enabled monitoring system that scans millions of ecommerce transactions, mimics customer behavior, and looks for patterns.
Suspicious transactions such as unusual login attempts at 3 AM or buying 10 iPhones late at night or if there's a sudden spike in purchasing frequency—all these indicate something bad has happened.
With traditional security systems, you can miss it.
But AI-based fraud detection systems do the behavioral analysis (analyze the transaction) and assess the risk factors like whether the transaction is super expensive, and the same credit card number was used in different locations.
It then tries to look for known patterns. Like if it was a case of stealing credit card information, it then flags the transaction as suspicious and sends the OTP to the registered mobile number.
4. Energy Sector
With rapid technological advancements in the energy sector, there come higher cybersecurity risks. If critical infrastructure (smart grids, power stations) is hacked, then it can result in power outages or blackouts and disruption in current operations.
Not only does that happen, but the consequence can also be even worse for hospitals that rely on a continuous power supply to run equipment. This means a shortage of electricity can impact the patient's life as well.
Unlike other industries, the energy sector is one that is being influenced by the effects of digital transformation. Initially, what used to operate on traditional power grids is now backed by the power of artificial intelligence.
This means modern power systems rely on smart sensors and automated control systems, and if these are not protected, then they can either manipulate energy flows or disrupt operations.
Today, it's like artificial intelligence and machine learning work like a double-edged sword. They not only enhance the threat detection process, but at the same time, they can be used for automating cyberattacks or creating highly convincing phishing emails.
But AI-enabled cybersecurity acts like a smart guard in the energy sector as it can analyze huge amounts of data from network traffic and then take quick action before such damage occurs, such as blocking harmful traffic or isolating affected systems.
Top AI-Powered Cybersecurity Tools and Platforms
Here are a few cybersecurity tools that enterprises can adopt, which are as given below:
1. Microsoft Defender
Microsoft Defender is an AI-powered cybersecurity solution designed for businesses to protect their corporate networks and keep their users' data safe from cyberattacks.
Best part? Its advanced AI algorithms can protect businesses from ransomware and malware attacks across different devices such as Windows, macOS, iOS, and Android.
It constantly monitors the company's devices, and unlike traditional antivirus software, it goes beyond threat detection.
Not only does this cybersecurity tool enhance the threat detection process, but it also finds the cause, doesn't wait for humans, and stops the threats before they spread.
2. IBM QRadar's Suite
IBM's QRadar Suite uses a combination of automation and advanced analytics to help companies improve their enterprise security solutions.
It's like a security stack that keeps different security tools in one place, so this reduces unnecessary back-and-forth hassle to switch between different systems.
This means QRadar aims to bring unified threat detection.
QRadar’s SIEM
It comes with AI and ML capabilities for detecting threats in a smarter way. Instead of overwhelming teams with different alerts, it highlights the most dangerous threats that need immediate attention.
For instance, if a hacker tries to do an unauthorized login to the system from a different location at odd hours, then the system will raise an alert.
QRadar's SOAR
This AI-powered cybersecurity tool is designed for automating workflows and performing actions that a human would do when a threat occurs. This allows for quick mitigation of threats.
3. Darktrace Cyber AI Analyst
As cyber threats are evolving, and attackers are using adversarial AI techniques, making traditional security systems obsolete. That's why Darktrace AI was developed, which takes a proactive and reactive approach to detecting threats in real time.
This AI-enabled cybersecurity solution keeps on learning the known and unknown patterns so it can distinguish between normal and abnormal behavior.
Once it detects the threats, it can raise an alert and take automated action with no human intervention.
Result – This saves time for security teams to focus on other strategic tasks, such as critical threats that need immediate monitoring, without posing any disruption to ongoing operations.
4. Google Security Operations (Formerly Known as Google Chronicle)
Google Chronicle runs on Google's architecture and works as a security analyst that can detect malicious attacks as and when they happen.
Pairing AI capabilities with Google's Chronicle tool ensures that threats can be automatically detected and speeds up the response time from hours to a few minutes.
Instead of security teams digging through the problems, Chronicle will analyze the security events, detect unusual activity and behavioral anomalies, and provide faster insights to security teams.
This way, the security team can speed up their investigation process.
5. SentinelOne
SentinelOne is an AI-powered cybersecurity platform that offers limitless security. It secures your enterprise from a wide range of threats, such as ransomware and malware.
Their AI-powered dashboard will tell you the top five alerts that should be immediately resolved, along with the level of severity (high, medium, or low).
It will even highlight which high-value assets have high-level alerts.
Unlike traditional security systems, this cybersecurity platform can do behavioral analysis and provide AI-powered insights to security teams to stop threats in real time (no more delays) and deal with those advanced attacks beforehand.
Best part? It provides everything under one umbrella, ranging from the detection of harmful behavior across vectors to providing immediate responses to incidents. Overall, it's good from an organization's internal security point of view.
How Does the Future of AI in Cybersecurity Look?
Given the shortage of cybersecurity professionals, you need to look for smarter, not harder, ways of improving your system security.
In the future, it's not just about using AI for threat prediction; it's more about using AI as a strategic partner that can help you enhance your decision-making skills.
Pairing AI & ML Services with Cybersecurity creates more opportunities in the future, which are as given below-
1. Unified Security Solutions
Today, there are fragmented workflows and disjointed tools that make it next to impossible to deal with modern threats.
The reason is simple: there's no unified security system. So, think of this case when you use different security tools from different vendors; it delays the threat detection process.
Like one tool for cloud security, one for firewalls, and another for monitoring, this means as these tools don't connect with each other, this makes it easy for hackers to exploit them.
But in the future, when all your data flows in the cloud, AI can spot everything faster, from detecting suspicious behaviour to spotting threats quickly.
It's more about diverging from multi-vendor architecture models to unified security solutions that are powered by AI.
Thus, security teams won't have to wait for days or weeks to spot the threats, as cyber threats can be mitigated in a few minutes using AI.
2. AI in Security Operations
As security teams feel overwhelmed with thousands of alerts every day, most of which are false positives. That's where if AI can be paired with security operations, then it will act like a smart filter.
It learns to prioritize the incidents that need to be immediately resolved.
In the future, you can expect more autonomous SOC assistants that will draft investigation reports, spot the false alerts, and at times suggest quick fixes when something wrong happens.
3. Autonomous Governance, Risk, and Compliance Systems (GRC)
While companies should comply with regulations such as HIPAA and GDPR, they need to ensure that compliance requirements are satisfied. If there's a risk, they need to communicate the same to business stakeholders.
Businesses need to think they need to meet their organizational goals and manage the risks by confining within the boundary of regulatory requirements. But this is a bit time-consuming process.
In the future, there will be autonomous AI-driven GRC systems that will monitor compliance, assess risks, and adjust strategies accordingly. This way, businesses need not worry about waiting for humans.
Autonomous GRC systems are not just about conventional LLMs that will assist the compliance processes; it's about working this way:
I've reviewed the data, drafted the report, booked the meeting, and we're behind on compliance. It's more like acting autonomously without needing a coffee break.
Best Practices for Implementing Cybersecurity AI
Artificial Intelligence has changed the way companies used to respond to threats. Johna Till Johnson, CEO at Nemertes Research, conducted a global study, and the findings of the study state-
The timeframe within which companies used to spot the attack and respond to it was 28 days, but now with automation, the time is reduced to a few hours.
If companies that are leveraging automation take a few minutes to detect a threat, other companies that still rely on traditional security tools take a few days to a couple of months for threat detection.
That results in reputation loss along with monetary losses.
Integration of AI in cyber security must be adopted with due diligence. Let's discuss some of the practices that can help to reduce risks:
1. Create Data Governance and Privacy Policies
From the start, create well-defined data governance and privacy policies that detail how data will be collected (encryption, anonymization, or privacy policies). When setting such data policies, make sure to involve all the stakeholders.
2. Make your AI Models Transparent
Instead of using black box models, make sure to use AI systems that can provide clear reasoning for how they arrive at conclusions. Such models are known as glass box models, and these include FiddlerAI, DarwinAI, and IBM Watson tools.
3. Train Your AI Models with High-Quality Data
The AI models you use for dealing with cyberattacks should be trained on high-quality and diverse datasets. Make sure to update the AI models with updated data so they can learn to spot and respond to such threats.
Note: If your training data is full of biases, then the results would not be objective. This means a biased AI model might ignore certain potential hazards that are of high severity.
4. Put Your AI Model Against Adversarial Attacks
Provide some fake or malicious data to the AI model so that it can learn how to respond to adversarial attacks such as data poisoning.
5. Monitor Your AI on a Regular Basis
Make sure to monitor your AI models continuously to ensure that they can detect unusual patterns or attacks that can manipulate your data. Retrain your AI model with fresh data so it can learn to respond to ever-evolving threats.
6. Adding the Human Element Is a Must
Human reviewers should always be included in the loop, and AI responses should be double-checked by security professionals. This is done to catch potential biases or false positives.
7. Invest in Your Employee Training
Train your employees and make them aware of the risks associated with AI-powered attacks.
How BigOhTech Can Help You Develop AI Systems for Competing Against Such Cyberattacks?
As cyberattacks continue to grow in 2025 and beyond, security teams need to use AI-enabled tools for identifying threats in the early stages before they escalate.
As an AI development company, we have a dedicated team of AI engineers who create sustainable AI solutions, ranging from creating intelligent bots to agentic AI systems.
Best part? They don't just do coding; they spend at least 70% of their time understanding the data on which models will be trained.
Recently, we helped Digilawyer by building a legal AI assistant that can solve the legal queries of Indian citizens. This AI-powered assistant was developed with the mission of providing affordable justice to everyone.
We trained this legal AI assistant on 10 lakh+ past judgments so it can provide accurate responses.
Result – Research time reduced from hours to seconds.
FAQs
What is the role of artificial intelligence in cybersecurity?
AI plays a vital role in cybersecurity by transforming the way organizations run and protect their digital infrastructure against cyberattacks.
From identifying unknown threats to speeding up the incident response, Artificial Intelligence and Machine learning are trained on vast datasets. They continuously look for patterns and adapt in real time when threats arise.
How does AI improve threat detection in cybersecurity?
AI enhances the threat detection process in cybersecurity as it identifies zero vulnerabilities or unknown threats.
Traditional security systems fail to do so, as they can’t learn from patterns or be trained on historical data to assess the likelihood of a new attack in the future.
How can organizations implement AI in their cybersecurity strategy?
Here are a few ways through which organizations can implement AI in their cybersecurity strategy -
Audit your existing security tools, policies, and processes.
Identify areas where AI integration can create a significant impact. It can be in the threat detection field or sending automated responses upon the threat occurrence.
Train your AI models on quality data so they can predict the vulnerabilities.
As AI threats keep evolving, make sure to retrain AI models with fresh data so these models can learn to respond to emerging threats.
What are some real-world examples of AI in cyber security?
Here are some real-world examples of using AI in cybersecurity-
