As a CTO with over one and a half decades of expertise in the ever-changing field of cybersecurity, I have been observing the immense impact that artificial intelligence (AI) has had on the wide technological landscape. Also, I have witnessed how AI-based solutions have emerged as a crucial aspect of enhancing processes in various fields and disciplines over the years. And the cybersecurity field is no exception. The ability of AI-based machine learning (ML) models to identify patterns and make data-driven decisions and inferences present a highly innovative approach to quickly identifying malware, directing incident response and even predicting potential breaches before they occur. Given the significant potential of AI in the field of cybersecurity, this article explores how AI fits into the broader cybersecurity landscape and how it can be effectively leveraged to enhance the security of businesses and their users, along with some of its limitations.

Businesses need to think about ethics from ground zero when they begin conceptualising and developing artificial intelligence (AI) products. This will help ensure AI tools can be implemented responsibly and without bias. The same approach already is deemed essential to cybersecurity products, where a "security by design" development principle will drive the need to assess risks and hardcode security from the start, so piecemeal patchwork and costly retrofitting can be avoided at a later stage. This mindset now should be applied to the development of AI products, said Kathy Baxter, principal architect for Salesforce.com's She noted that there were many lessons to be learned from the cybersecurity industry, which had evolved in the past decades since the first malware surfaced in the 1980s.

In this special guest feature, Justin Beals, CEO and cofounder of Strike Graph, outlines key considerations when using AI tесhnоlоgіеѕ to іmрrоvе a startup's суbеrѕесurіtу capabilities and manage суbеr rіѕk more efficiently аnd еffесtіvеlу. As a serial entrepreneur with expertise in AI, cybersecurity and governance, he started Strike Graph to eliminate the confusion related to cybersecurity audit and certification processes. He likes making arcane cybersecurity standards plain and simple to achieve. As the CEO, Justin organizes strategic innovations at the crossroads of cybersecurity and compliance and focuses on helping customers get outsized value from Strike Graph. Justin earned a BA in English and Theater from Fort Lewis College.

In this article, I will look at how Artificial Intelligence (AI) can help improve cybersecurity practices in an environment of ever-increasing threats and discuss the role of AI in alleviating the perennial talent shortage in the field of cybersecurity. Remember that the current wave of AI, driven by advances in deep learning, started around 2015, but the talent short- ages in cybersecurity precede that. I also caution that if we are not careful, AI can even be a double-edged sword when it comes to cybersecurity. Let me start with a flashback. About a decade ago, I used to audit the information security practices and cybersecurity preparedness of large global enterprises.

Artificial Intelligence, the term which first originated in the 1950s has now emerged as a prominent buzzword all over the world. More than 15% of companies are using AI and it is proving to be one of the most powerful and game-changing technology advancements of all time. From Siri to Sophia, the technology has people noticing it and wondering how this will impact their future. Presently, Artificial Intelligence is seen everywhere. Major industries like healthcare, education, manufacturing, and banking are investing in AI for their digital transformation. Cybersecurity, being the major concern of the digital world, is still uncertain about the impact AI will have on it. With the fast-growing cyber attacks and attackers, cybercrime is growing to become a  massively profitable business which is one of the largest threats to every firm in the world. For this very reason, many companies are implementing Artificial Intelligence techniques which automatically detect threats and fight them without human involvement. How AI Is Enhancing Cybersecurity Artificial Intelligence is improving cybersecurity by automating complicated methods which detect attacks and react to security breaches. This leads to improvement in monitoring incidents leading to faster detection of threats and its consequent responses. These two aspects are quite essential as they minimize the damages caused. Various Machine Learning algorithms are adapted for this process depending on the data obtained. In the field of cybersecurity, these algorithms can identify exceptions and predict threats with greater speed and accuracy.

Leading experts in cybersecurity and ethics from Oxford Internet Institute, University of Oxford, Dr Mariarosaria Taddeo and Professor Luciano Floridi, and Professor Tom McCutcheon from Defence Science and Technology Laboratories believe the current approach to defining standards and certification procedures for Artificial Intelligence (AI) systems in cybersecurity is risky and should be replaced with an alternative method. Their new paper "Trusting Artificial Intelligence in Cybersecurity: a Double-Edged Sword", published in the journal Nature Machine Intelligence argues that defining standards based on placing implicit trust in AI systems to perform as expected, without any degree of any monitoring or control, could leave us at risk of new forms of AI attacks, disrupting systems and changing their behaviour. Current'trust' based standards and certification procedures in AI typically see tasks being carried out with either no or minimal control on the way the AI-driven tasks are performed. In their paper, the cybersecurity experts present the case for developing'reliable' rather than trustworthy AI in cybersecurity. The experts argue that reliable AI has greater potential to ensure the successful deployment of AI systems for cybersecurity tasks, making them less vulnerable to cyber-attacks.