Needed: A Data Protection AI Ecosystem
The likelihood of a job being automated can be understood by asking the 4Ds; is the job dull, dangerous, dirty or dear? Not sure about dirty or dangerous but people tell me backup is dull, and it’s often very expensive.
Our ability to keep pace is also a problem. Keeping data protected is a growing challenge as the volume and variety of data increases. And if data is the new oil, then backup also is becoming more of an imperative.
Backup and recovery best practices move slowly from company to company, often only when skilled engineers move jobs. In ecological terms this is the equivalent of DNA mutation; a very slow evolution.
New data points from IoT and the proliferation of cloud computing models all point to data protection becoming a bigger challenge. With increasing regulation and ever more sophisticated malware attacks, we need to accelerate this evolution to keep up in the data protection arms race. Hackers are using AI techniques to steal your, or your customers’, data. It’s time to consider AI for protecting data.
AI in Data Protection
Machine learning is different from regular programming. Rather than developers writing explicit code to perform some computation or task, a machine learning application can use the data to create models.
A use case increasingly used by successful service providers is improving customer satisfaction. An AI-powered customer service chatbot can support and scale business teams in their relations with customers.
Predictive analytics can help answer the question of what will happen in the future based on what is happening now. This technology can be used to identify patterns of backup failures and predict when the next one will occur.
The Right Architecture
In 1957, Frank Rosenblatt built the Perceptron, the first trainable neural network algorithm. To help encourage a neural network to learn, you need a large network. In 2007, when Apple launched the first iPhone, Steve Jobs insisted developers use only web apps via the Safari browser. This was a failure because it was a closed ecosystem and inward looking. Only when Jobs allowed an SDK to be published did third party developers stream in, creating an unprecedented wave of innovation.
AI is about asking questions. Since no one person has all the answers, in AI no one person has all the questions, either. Apple’s success is built on the principle of a large ecosystem, or network, in which many people ask and answer questions.
For the successful adoption of AI in data protection, we believe that the learning platform must be separated from the underlying applications. Developers must have access to the metadata, so they can ask the questions to turn dumb backup data into smart insights. Large enterprises can use multiple backup tools, so having your AI platform out-of-band will create more training data for machine learning.
An Open Mindset
We believe that the service provider and vendor channel community will be at the heart of future AI innovation in data protection. Managed and cloud service providers, as they scale, will turn to AI to solve the toughest problems in backup and recovery. The most successful AI platforms will need to embrace the channel ecosystem.
Seventy-thousand years ago, at the time of the first cognitive revolution, homo sapiens learnt to change and adapt the stories they were telling. This allowed them to form larger groups and networks. These groups learnt to work together to defeat enemies (human and animal), which were individually stronger than them.
In the London of the Middle Ages, merchants and craftsmen formed livery companies to protect themselves and their customers. Highly skilled artisans, such as the leather sellers and the pewterers, even though competitors, would join together to gain network effects. Today, despite a global communications revolution, clusters still exist. Hollywood is where movie makers congregate, Silicon Valley for tech start-ups, and in Oxfordshire, UK, exists a hub for Formula One teams.
So if we are to apply the same logic to today’s worldwide digital age, just as economies prosper when trade is unrestricted, AI in data protection will flourish with companies that provide open architectures, which in turn will foster innovation across a wide ecosystem.