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BT Group’s Digital unit has announced the deployment of a new internal machine learning operations (MLOps) platform to shorten the roll-out of new artificial intelligence (AI) deployments from six months to six days.
Explaining the basis of its new AI Accelerator, BT said AI models are the core building blocks needed to make use of AI in practice, delivering value by classifying and making predictions from data in ways that humans can’t. To that end, the new platform orchestrates, accelerates and monitors AI model deployments developed by BT Group’s data community, assessing their efficacy and behaviour to drive value from the business’s 29-petabyte data estate.
BT said that through the use of common frameworks and templates, AI Accelerator will “drastically” reduce the administrative and technical processes involved with taking a new AI use case from prototype to production. In keeping with its Responsible Tech principles, the group says AI Accelerator has built-in triggers to make sure new AI use cases are properly assessed in line with data privacy, security and ethics principles, ensuring the safe and responsible use of AI across the business.
Coupled with the rise of modular, reusable data products, the AI-powered intelligence layer on the group’s data estate represents a major step forward in forging BT’s path to becoming an AI-led company, it added.
BT also believes that the combination of tech talent, partnerships and the technology contained within AI Accelerator will reduce the core of this process from six months in April 2022 to six days by March 2023. This acceleration is said to result from the standardisation of tools and data handling, as well as streamlined software update and monitoring, drawn from the enhanced automation and templated best practices provided by AI Accelerator.
BT said it is confident this process will free up months of time for every data scientist and analyst tasked with bringing new use cases to life across the group.
“A core driving principle for BT Group is to find a way to safely accelerate the time to value, pound per petabyte, of data,” said Adrian Joseph, managing director, data and AI, BT Group. “AI Accelerator gives us a path to more rapid value with clear oversight of AI use case parameters and performance.”
The goal of the BT Digital unit is to underpin over £500m of internal value from data and AI in aggregate, through improved customer experience and enhanced efficiency within each of the group’s business units over the next five years, and help power the transformation required to support BT Group’s long-term success.
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Over time, AI Accelerator will provide ongoing monitoring of AI models in production across BT Group’s estate, flagging any “drift” from baseline norms in the way the AI is consuming or deriving insight or outcomes from data. In this way, it will act as a scanner for the group’s Digital Brain, continually assessing each model’s health and prompting expert data scientists, where necessary, to refine and optimise them.
As a result, BT believes data scientists will have more time to focus on future data science projects, driving further innovation and accelerating the use of AI across the group, instead of constantly maintaining each AI model.
BT said AI Accelerator will allow the group to accelerate its build, measure and learn processes for new AI use cases. Examples of these are said to include churn/propensity models, or to test models that personalise apps and services for BT customers, delivering better customer experiences and/or value within its business units. It said many models are already live, generating value both from the identification of revenue opportunities for the group such as customer propensity models in BT Group’s Global business.
The new MLOps platform was built in partnership between BT Group’s growing data and AI teams within its Digital unit, and Datatonic, a data and AI consultancy and Google Cloud partner, and adds to BT Group’s partnership for its data with Google Cloud.
“Thanks to the work the team has done accelerating our migration into Google Cloud, we have a healthy testbed for AI Accelerator and are seeing it catalyse AI acceleration across the group,” said Zoe Webster, artificial intelligence director in BT Group’s data and AI team. “As we progress, we’ll be able to track the health and the performance of our AI use cases in real time, ensuring consistent, safe, ethical delivery of value from our phenomenal data resources.”