Harnessing data and AI to enhance business value, a CDO's take.

An opinion piece by Andy Markus , chief data officer of AT&T, one of the largest telecom companies in the world.

Since helping to pioneer artificial intelligence in the 1950s, AT&T has been?shaping?machine learning (ML) and AI technologies for decades. This innovation continues at AT&T, guided by the Chief Data Office (CDO) team as the North Star for data, analytics and AI strategies and implementation.

As one of the world’s leading modern communications and technology companies, AT&T carries more than 534.7 petabytes of data across its global network every day. To manage data at this scale, the CDO team has defined a common approach to how data is stored, managed, accessed and shared across AT&T.?

We established a ‘single version of truth’ for each defined data product so people are not using different sets of data on the same projects and coming up with conflicting answers to the same questions. We created a common data catalog for data findability, and implement data quality checks and security patterns across the data pipelines. In addition, we established a data governance council that includes all core data user groups across the firm to get and stay aligned on this common approach to data.?

This discipline enables our CDO team, hand in hand with our business partners across the firm, to harness this massive flow of data to help solve a diverse array of AT&T’s most technically challenging problems. Here are some examples of how data experts from CDO worked side-by-side with their business unit counterparts to create value for our customers:

• Avoiding network outages: Predictive models using the latest AI and statistical algorithms scan more than 52 million different network records, devices and customer circuits and analyze over 1.2 trillion daily network alarms/alerts to anticipate and avoid network service outages – often in real-time.
• Blocking nuisance robocalls:?A revolutionary network-level AI-based solution has blocked more than 6.5 billion robocalls. The 24/7 solution uses sampling, predictive modeling, multivariate analysis and more, filtering through billions of daily records looking for patterns and suspicious qualities indicating likely robocallers.

Insider's Note: We've seen a lot of this in the sector, RealNetworks' KONTXT has also been rolled out by Vodafone this year .

• Preventing device fraud:?A world-class, multi-stage AI-based fraud management tool evaluates millions of daily transactions across all AT&T sales channels in near real-time, inspecting each event within milliseconds against hundreds of rules to detect fraud patterns. The CDO team equipped the solution with an intuitive, flexible user interface to enable frontline members of the fraud team with minimal technical background to write, test, and deploy rules themselves, with little-to-no engineer involvement.
• Improving collections experience:?An ecosystem of AI-based natural language applications, ML models and other technologies (including intelligent voice routing, Webforms, and Bots), power AT&T’s first-ever voice virtual assistant to handle roughly 400,000 delinquent payment calls per year. The fully automated self-service solution guides customers through a frictionless, step-by-step decision engine that negotiates flexible payment terms, capturing a higher percentage of delinquent account balances than ever before.
• Enabling climate-risk planning: The telecom industry’s first hyperlocal climate risk visualization and planning solution predicts potential risks and impacts of environmental events on company infrastructure – up to 30 years in the future. The CDO team uses sophisticated ML and AI algorithms to analyze and predictively map millions of meteorological data points against hundreds of schematic layers tracking AT&T’s assets.

Andy's column continues at AIBusiness.com, read it in full here .