Ever since AT&T helped pioneer artificial intelligence (AI) technology in the 1950s, including coining the term “artificial intelligence,” AT&T has been shaping machine learning (ML) and AI technologies for decades. Today, the company relies on its Chief Data Office (CDO) to determine AT&T’s North Star for data, analytics and AI excellence. Home to many of the world’s leading data scientists, developers, engineers and researchers, the CDO empowers AT&T employees to use data and AI to improve efficiency and deliver better results for customers.
To achieve its goal, CDO has a three-part mission:
- To leverage, share and catalyze insights from the company’s vast data store, while transforming and modernizing AT&T’s data platforms, data supply chain and data science ecosystem.
- To democratize data and AI within AT&T and drive wider adoption of data-driven solutions by putting powerful data analytics capabilities in the hands of every AT&T business leader and employee.
- To contribute back to and help lead and grow the wider data and AI community through open source and industry groups, academic engagement, and workforce investment.
Today I’ll cover that first mission, with future posts on those second two elements.
Harnessing data and AI for business value
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 by AT&T. We’ve created a “single version of the truth” for each defined data product, so people don’t use different data sets for the same projects and come up with conflicting answers to the same questions. That’s why we created a common data catalog for data discoverability and implemented data quality controls and security patterns in the data pipelines. In addition, we established a data governance council that includes all core data user groups across the company to align and stay aligned with this common approach to data.
This discipline allows our CDO team, hand in hand with our business partners across the company, to leverage this massive flow of data to solve a wide variety of AT&T’s technically challenging problems. Leveraging this collaboration with the industry’s experts, the CDO team can devise groundbreaking AI solutions to improve customer experience, increase internal efficiency, and identify business opportunities. Here are some examples of how CDO data experts worked side by side with their counterparts in the business unit to create value for our customers:
- Prevent network outages: Predictive models leveraging the latest AI and statistical algorithms enable the End-to-End Incident Management platform to scan over 52 million different network records, devices and customer circuits and handle over 1.2 trillion daily network alarms/alerts analyze to anticipate and avoid network service outages by detecting and exploiting patterns in these massive data sets – often in real time.
- To block nuisance robocalls: A revolutionary network-level AI-based solution has blocked more than 6.5 billion robocalls. The solution uses sampling, predictive modeling, multivariate analysis and more to work 24/7, filtering billions of daily records looking for patterns and suspicious traits that indicate potential robocallers. The solution then checks detected anomalies against internal and external rules and security measures to prevent legitimate automated calls from being suspended.
- Prevent device fraud: A world-class AI-based fraud management tool evaluates millions of daily transactions across all AT&T sales channels in near real-time, inspecting every event within milliseconds against hundreds of rules to detect fraud patterns. CDO provided the solution with an intuitive, flexible user interface that allows front-line members of the fraud team with minimal technical background to write, test, and implement rules themselves, with little to no engineer intervention, to quickly track market trends.
- Improving the collections experience: An ecosystem of AI-based natural language applications, ML models and other technologies (including intelligent voice routing, web forms and bots) enable AT&T’s first-ever virtual voice assistant to handle approximately 400,000 overdue 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 account balance past due 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 corporate infrastructure – up to 30 years into the future. CDO uses advanced ML and AI algorithms to analyze and predictively map millions of meteorological data points against hundreds of schematic layers that track AT&T’s assets.
These examples show how a modern and connected approach to data is laying the groundwork for the transformative impact of innovative AI solutions to solve challenging business problems. We see a huge positive impact on the business and we have more to do on our data and AI journey ahead.
NEXT ONE: Democratizing data and AI