Without clean and accurate data, AI is less effective. Yet, without AI, the potential of data is not maximized …

AI is forming the technological foundation for the future digital economy. Organizations across the public and private sectors are already gaining much from AI, especially in ultra-complex areas like automation, data analytics and digital assistance.

Through machine-displayed intelligence that combines machine learning and deep learning techniques to simulate human thinking, massive amount of data can be processed at great speed.

The benefits of AI can be realized across multiple industries like agriculture, financial services, healthcare, manufacturing, and retail. For instance, the technology is used in banks and retail shops to enhance customer experiences and fraud prevention. In robotics, AI processes data in real time to sense obstacles and pre-plan routes for autonomous robots used in factories and hospitals.

Putting data at risk

As useful as AI is, a key element that cannot be neglected is the security of sensitive data. Data protection must be integral to the development of advanced AI systems for organizations to glean technological benefits without compromising data privacy.

As many emerging technologies—including AI—require large volumes of it to be transferred at high speed, data is increasingly exposed. It is critical that IT teams have solid data protection strategies in place with a clear understanding of data protection contingencies as their organizations progress on their digitalization journeys.

As teams leverage data for AI applications, it is also crucial that they ensure that processes adhere to data privacy and protection guidelines and regulations. This is particularly important now as many organizations adjust to a remote-working model: a distributed workforce means greater data exposure and higher risks of data compromise.

AI as a ‘data guardian’

When we look at the issue from a different perspective, we find that AI can be a formidable tool for data management and protection, too.

AI processes can help identify patterns and, more importantly, identify the anomalies that occur in many organizational operations. AI bots can be used to recognize, route and service privacy data, attending to requests faster and more accurately. This is similar to how we use AI chat bots like Alexa or Siri to manage complex requests today.

Additionally, AI can be used to manage data classification. As mentioned, AI can handle the identifying and classifying of data in a much more accurate and faster way than humans can. The technology is already being applied to the analyzing of siloed data stores. Similarly, it can do well playing a role of ‘data guardian’ for privacy and compliance tasks, as well as to manage and safeguard sensitive data.

The technology can be applied to eliminate malicious vectors, and it can perform especially well when guarding sensitive data that involves human data handlers or operators. AI can analyze large amount of data while simultaneously weeding out any malicious human intervention, leaving critical asset data secure.

AI can especially play a key data safeguarding role in the management of sensitive data, such as financial or healthcare records, where we are dealing with data that is prone to misuse, cyberattacks and human errors. In fact, AI is slowly gaining a reputation for its reliable management of sensitive data. Managing risk, fraud and cybersecurity threats is the top-ranked AI Applications for 2021, according to a PwC study.

AI as a ‘data wingman’

An area where AI is underutilized today is in data backup and recovery solutions. Backup usually encompasses critical and sensitive data, as well as applications that are essential to daily operations. Besides facilitating data protection and management, backup providers—with access to the full wealth of organizational data—can empower organizations to derive value-added insights for exceptional business innovation.

AI has hence been spotlighted by data and software management enterprises that are making significant investments in the field. Backup software and recovery tools are beginning to include AI and machine learning to predict possible data breaches, while simultaneously identifying other threats such as ransomware. Backup solutions today also utilize predictive analytics to enhance administrators’ efficiency and speed, while automating tasks that previously consumed valuable manpower.

However, while AI possess vast potential, the onus of using it responsibly lies with organizations. Protecting data is a foundation that must be established before we can reap the benefits of advanced AI technologies.

As we become increasingly reliant on AI, the only way to ensure its sustainability is to make AI usage secure and robust enough for daily operations. In tandem, organizations can also look to advisory authorities to minimize risks of malfunction or misuse of critical systems.