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Could AI Solve the Data Leakage Challenge?

It may not seem obvious, but your translation supply chain represents an enormous data security risk to your business. Particularly when you consider that hundreds of stakeholders could be involved in creating, translating, managing and delivering just one piece of content to customers. It’s no surprise then, that security and data privacy have become boardroom issues. But recent advances in machine learning and artificial intelligence (AI) are changing everything, offering a fresh perspective and approach to some of the most difficult security challenges.

Here we speak to Matthew Hardy, VP of Customer Solutions at SDL, about the complexities involved with managing a global content supply chain, and how AI brings new and exciting ways for brands to organize content in a way that improves security across all areas of their business.

Firstly, explain how security factors into the content supply chain?

Global businesses have a common problem. Far too much content. Everything from internal documents and emails, web, legal, financial, HR, marketing and customer-related content is being created around the clock. Managing, and delivering all this content to internal and external audiences – particularly in a secure and efficient way – is a major challenge. And depending on how many languages your audiences speak, the problem just gets bigger.

It may not be obvious, but the content supply chain is one of the biggest risk areas for data leakage. One piece of content alone could involve as many as 150 “handoffs," that’s everyone from writers, reviewers, translators, subject matter experts, marketing and compliance all collaborating to get that content over the finish line.

Now most companies we talk to are not aware where that piece of content is at all times. The way global brands operate means the person who wrote the content may not necessarily work within the business, they could be a consultant, agency or third party – which could risk all sorts of data privacy regulations. But there’s also another risk area that companies don’t often consider.

Last year translated contracts, health documents and other sensitive information were scattered across the web. After looking more closely, these documents had been translated by employees using free online translation tools. Making secure, enterprise-grade machine translation available to everyone within your company can stop this problem immediately, while also getting better quality translations.

We’re hearing from more and more brands that they need to find more secure ways of managing this complex content supply chain – from content creation through to translation and delivery. The legislative environment we now live in makes it incredibly difficult for them to comply with regulation and ensure every piece of content is secure. The only real way of addressing this is to put data privacy front of mind and at the beginning of that piece of content’s journey.

Can AI help secure communications for global businesses?

Most organizations classify information on a scale of 1 (public information) to 4 (restricted or material non-public). While staff are trained on content classification, in our experience at any given time, upwards of 30% of content is estimated to be misclassified. Now imagine if you could actually assist in detecting what information should be secure? Even better – tagging it appropriately and managing its life across the entire content supply chain? AI engines can be trained to look for and auto classify a piece of content to ensure that it is allocated to the appropriate workflow with the necessary data governance restrictions, providing an audit trail without relying on employees’ classifications alone.

This may not seem like a big issue – there are of course manual ways of classifying groups of content. Individuals under classify content because they know what the implication of high classification is. You get people just making a mistake, and you have more junior team members saying everything is highly restricted. You can’t blame them for not wanting to get it wrong. But the implications to the wider business runs from inefficiencies to unnecessary spend and potential data leakage. AI can automate all of this, setting processes and workflows to organize and secure information, helping to take the effort away from complying with dozens of regulations.

So where are brands going wrong?

Most companies use their own home grown algorithms to spot and classify potentially sensitive information. Such as Personally Identifiable Information (PII). That’s incredibly difficult when your employees and customers speak dozens of languages.

Based on your line of responsibilities, AI can ensure that the information you work with is appropriate to your role, and shared in a way that doesn’t introduce any risks to the business. An AI enhanced workflow can make sure highly classified content only goes to the right person, and in the financial industry this is vital. Take investment research teams – who deal in dozens of sensitive projects. Extracting and segregating different pieces of content and conversations across any language could all be handled with AI, and securely managed throughout the content’s lifecycle. It’s a powerful proposition when you think about it.