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AT&T CDO: Harnessing data and AI to enhance business value

Article ImageAn opinion piece by the 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.
  • 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.

Democratizing data and AI

The CDO team acts as a catalyst to spread reusable capabilities across AT&T to support greater data-driven decision-making at all levels of the company. We have empowered business managers with self-serve access to ‘single version of truth’ datasets using business intelligence tooling. We are also extending low/no-code AI creation capabilities across the firm. This unlocks a larger segment of analytic talent beyond just our code-savvy cohort within AT&T to create optimized and responsible AI solutions.

The CDO team is focused on analytic skill development and employee growth to mobilize this larger segment of analytic talent that we call our ‘citizen data scientists.’ We are revolutionizing how employees across AT&T navigate the data and AI lifecycle − from finding and getting data, to engineering the data for machine learning, to creating, deploying, monitoring and governing machine learning models used in artificial intelligence.

To support the front end of the data and AI lifecycle, the CDO team created two capabilities to speed up the process. 

First, the CDO team built a centralized data intelligence platform that inventories all of AT&T’s data and takes advantage of metadata search capabilities that speeds up the process of finding information scattered around the company. This platform provides a single enterprise-wide entry point to AT&T’s more than 160 million data assets, regardless of where they are stored across the company’s legacy systems and reference catalogs.

The functionality, using best-in-class solutions like Collibra, includes a simple-to-use, natural language search interface, making it easy for users to find and filter a wide range of reusable customer and operational business intelligence and AI building blocks (i.e., reusable software code and visualization tools). In addition to enabling the search across the company, we have enabled collaboration at all levels of expertise in data analytics so that we can both accelerate analytics and get broader input on our overall business and technical strategy.

Second, to get a deeper look at those data and AI tools within our catalog, AT&T and Silicon Valley startup co-created an AI Feature Store − a computation and storage platform filled with production-ready machine learning features for model development. The Feature Store makes these AI building blocks discoverable, usable, shareable and reusable across the enterprise. 

A visual interface enables users to browse the store catalog to review available features, identify the most popular ones, and determine their fit for reuse in new models. In many cases, features used for past models can be reused to immediately start new ML projects – significantly shortening time-to-market. Plus, users can see detailed data and source code on each feature as well as each model’s current and past performance. Because the Feature Store is constantly updated with pipeline code tweaks or newly arrived data, it also automatically validates and sends new feature recommendations and updates to users – an industry first.

With these data sets and features in hand, we turn to the cloud where we utilize cutting-edge tooling to develop the best machine learning models for the job. We collaborated again with to start the journey by automating model development, using the latest systems to suggest the best AI given the data and features at hand.

Our crew of data scientists can customize and manipulate the features, data and models in notebooks powered by Databricks. Models can be improved even further − collaborating and competing with our internal AI crowd-sourced competition platform, where data scientists compete to make the best fit model given the business case and the data.

We publish the best models and integrate them into software to enable the AI to make decisions at scale – sometimes thousands per day. Models published are automatically documented in a standardized way so that at any given moment, we know what our AI decides.

All AI models are monitored and governed. We not only check that the data coming into the AI for scoring is of the right quality, but also make sure the model does not drift and continues to provide relevant decisions. We use the latest techniques to be sure that the data, features and models that we use are diverse enough to represent all situations our customers may encounter.

Shaping the industry

AT&T supports AI and ML innovation beyond our walls while also giving our employees the resources to be data experts throughout their careers. The CDO team does this by ensuring the best brains from the best companies worldwide are working together to shape the future of these technologies.

AT&T’s data scientists, developers, engineers and researchers frequently publish their work pushing the boundaries of data science and AI for the future. They also participate in industry forums and research groups, sharing and adopting best practices and new tools and ideas. In addition, our talented employees are a significant component that contributes to AT&T’s place as the U.S. company with the sixth most AI-related patents.

The CDO team also maintains academic and tech partnerships to cultivate the next generation of experts in statistics and machine learning, statistical computing, data visualization, text mining, time series modelling, data stream and database management, data quality and anomaly detection, data privacy and more.

For example, we recently launched the inaugural Data Science Scholars Program in conjunction with Southern Methodist University in Dallas. This program, which attracts a very diverse set of candidates, selected nine SMU students to complete both an on-campus data science curriculum and a summer data science internship with AT&T. Our plan is to offer each student interviews for full-time employment with AT&T upon completion of their coursework and internship, setting up a fantastic and incremental pipeline of great talent that will fuel AT&T’s ever-increasing need for data scientists.

The CDO team also invests heavily in its own workforce, offering funding, continuous education, learning opportunities and mentorship to ensure its data scientists and engineers stay up-to-date in the dynamic market and to help them continue moving forward into their professional futures.

AT&T has delivered data and AI-driven value across our operations, but there is much more to do. The entire business is transforming at a pace toward a future when data and AI are completely embedded in the organization. With the CDO team setting the pace for data and AI strategy, AT&T is primed to lead the industry in defining the future of what’s possible.

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