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It’s All About Data: How to Drive Secure Use of AI



Although artificial intelligence (AI) has been with us for some time, the technology seems to be everywhere these days, as vendors and end users get more vocal about its benefits. They’re right to be enthused. McKinsey estimates that AI could unlock trillions of dollars worth of value globally across functions in 19 sectors. In some areas, it’s no longer about even carving out competitive differentiation, but merely delivering what is expected by customers and employees.

Yet AI is ultimately built on data. So, organisations that fail to adequately protect this data are building their strategic growth plans on quicksand.


The value of AI

There are various flavours of AI. But, however it’s being used, the technology has undeniably become a strategic asset for organisations that can deploy it most effectively. Consider the following use cases:

Automating manual processes: Robotic process automation (RPA) can help to replace repetitive and mundane tasks, reducing human error and freeing up staff to work on higher-value tasks.

Authentication: AI-powered facial recognition and other biometric tools can boost customer and employee checks to enhance security and the end-user experience.

Strategic planning: Predictive AI trained on historic corporate data can help business leaders make better-informed decisions about the future – everything from geographical expansion to new product development.

App development: Generative AI (GenAI) tools can help DevOps teams accelerate the development of new applications designed to enhance the customer and/or employee experience.

Customer service: GenAI can also power 24/7 chatbots capable of using natural language interactions to answer customer queries – freeing service staff to focus on more complex customer problems.


Understanding the risk

Broadly speaking, AI’s power comes from applying intelligent algorithms to large volumes of data. But what if a threat actor were able to access that training data?

They could potentially:

There are also compliance risks involved in unauthorised internal users gaining the ability to access specific datasets. Organisations might find themselves on the wrong side of the GDPR or its equivalents in the US (including the CCPA) if they don’t have strict access controls in place. Failure to put the appropriate checks and controls in place could lead to significant reputational and financial damage – not just from regulatory fines but other breach costs. The average data breach today costs an estimated $4.45m, although it rises to $9.48m in the US.


Start security with the data

Given that the success or otherwise of an AI model is derived from the data on which it is trained, keeping that data secure must be a priority. Organisations need a robust, streamlined way to find and protect this data, wherever it resides in the enterprise. Crucially, the data must also be protected in a way that enables its use in AI systems.

This is where comforte’s Data Security Platform comes into its own. It:

Data-centric security like this is a great start for organisations looking to drive AI-powered growth. However, it must be deployed as part of a holistic data governance strategy, which includes regular staff awareness training sessions to help create a security-by-design culture.

With everyone in the organisation pulling in the same direction, it becomes much easier to optimize the use of emerging technologies like AI. Organisations that get this right will find themselves in the driving seat for sustainable growth.

Learn how to discover, classify, and protect all sensitive data.

Click the button below to download the solution brief for our Data Security Platform:

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