The Equifax data breach revealed the devastating effects that a cyberattack can have on a company’s finances and reputation – causing organisations to assess their security posture and exposure. And concerns around security only continue to grow given the increased use of IoT devices in the workplace, e.g. Amazon’s Alexa for Business.
However, certain technologies that utilise IoT can be used internally to prevent security breaches, as malicious actors are unable to access closed systems via unsecure apps. This technology also allows companies to have a broad overview of activity within their environment.
Organisations should not rely on security vendors to build products to address all vulnerabilities – a robust security strategy should originate from the C-suite. As such, the CFO will play an increasing role as the gatekeeper for a company in terms of hiring a new team or investing in the best available technology. In 2018, security becomes a top priority for CFOs.
Enterprise IoT will allow us to reimagine the concept of “identity” — in and out of the workplace.
Over the past year, digital identity has been woven into different aspects of life, especially through social media. In 2018, we'll see even more identities dematerialise from their current form and go digital. New forms of IDs will interact with technology to change the world in front of us, touching areas like security, productivity, and more.
Metadata will have its moment in 2018, acting as a “Rosetta Stone” for machine learning.
The potential applications of machine learning (ML) and natural language processing (NLP) have been discussed at length in 2017, and in 2018, these applications will be put into practice. One of the applications of ML and NLP is in processing large amounts of data quickly, particularly if this data has been labelled and categorised properly. Companies who have been collecting metadata for years, labelling and categorising it, have built the framework necessary for success with ML and NLP. Their systems will be able to more accurately utilise this new technology and will be better positioned to trust conclusions that machines have reached following analysis.
