The term ‘artificial intelligence’ (AI) was first coined by researchers of the Dartmouth Summer Research Project on Artificial Intelligence in 1956. Artificial Intelligence (AI) and Machine Learning (ML) are buzzwords frequently associated with topics such as Big Data, analytics, and broader technological changes. The terms are used interchangeably, but are not identical. Artificial Intelligence is the overarching concept of machines performing tasks that could be considered intelligent and smart. Machine Learning is a current concept of AI based on the idea that machines should be given access to data and learn for themselves.
Artificial Intelligence is not a new notion and is seen in the Greek myths, for example, as mechanical men such as Talos, designed to mimic human behaviour. Additionally, in the early development of computers in Europe, engineers attempted to create mechanical brains and considered them as “logical machines” with capabilities such as basic arithmetic and memory. Currently, rather than increasingly complex calculations, the field of AI is focusing on mimicking human decision-making processes and carrying out tasks in more human ways.
Artificial Intelligences can be classified into one of two essential groups – applied or general. Applied AI systems are increasingly designed and adopted to trade stocks and shares intelligently and to maneuver an autonomous vehicle and other automation benefits, ranging from predictive outcomes to advanced security options. Although AI encompasses many different technologies, the interest in AI for cybersecurity is being driven by the newfound wealth of data and analysis methods.
Digital trust as a top priority to build and maintain the IT infrastructure for digital transformation
With data breaches becoming more common and day-to-day IT security operations facing greater challenges, losing digital trust can have a substantial impact on brand reputation and the bottom line of most organisations. Consequently, ensuring ‘digital trust’ is a top priority to build and maintain the IT infrastructure for digital transformation. According to a market study by Frost and Sullivan, AI-based cybersecurity can enhance the capabilities of IT staff and help organisations thwart cyber threats. AI and ML are changing the security landscape and are used widely by both hacking and security cybersecurity industries and communities. In a more sophisticated environment coupled with the proliferation of AI-driven attacks in number and frequency, the cost of threat detection and response is escalating. The result is that security professionals need more advanced, smart and automated technologies to combat automated attacks.
While the benefits for consumers of a prioritised digital transformation and connectivity include convenience, efficient services and better experiences, the complications are increased potential risks of cyberattacks on both companies and users. Hence, cybersecurity professionals are leveraging AI and machine learning technologies for responding to the evolving cyber threats faced by individuals, businesses and governments.