The Drive for Data Modernization and Private Sector Integration. By Shea Carlberg (GW ‘25) and Diya Kumar (GW ‘26)
“We have to imagine a world where technology will outdo the best economists,” said Oliver Wise, executive director of Bloomberg Center for Governance and Excellence, to a room full of economists.
As geopolitical tensions rise, there is a demand for constant innovation. After all, policymakers and economists alike are operating under the belief that the country with faster technological advancement will dominate global ideology. Their strategy: integrating artificial intelligence in governance and federal data collection systems. A wide-scale modernization effort. But what will inch us toward the modernization we think we require?
Acting directors at the nation’s highest statistical bureaus underscored the need for private and public sector data harmonization. The biggest contributor of economic and social data—our long-regarded federal statistical data system—is truly an underleveraged asset.
“We need to do better learning from the private sector and how they stay relevant,” Bureau of Economic Analysis Director Dr. Vipin Arora said.
AI’s rapid displacement of workers has long put economists on alert, especially as businesses prepare for the next wave of innovation. Integrating AI into an institution—whether a federal agency or a private firm—requires far more than new tools for data collection and analysis. It forces changes in labor priorities: who gets hired, what skills are valued, and how organizations maintain public trust while automating more of their operations.
Fact versus Fiction
“It’s a governance problem, not a data science problem,” RAND Senior Policy Researcher Rachel Lyngaas said.
She said the reoccurring issue in the current administration is a lack of cohesion in federal statistics and policy decisions. The executive branch poses a “coercive” risk by feeding into policy decisions with no space for leaders to comprehend, let alone get a hold of, the data independently.
Lyngaas argued that without a shared statistical dialogue across agencies, policymakers end up debating what should be agreed-upon facts. That disconnect leaves the government unprepared for economic shocks and builds vulnerabilities that private-sector data might otherwise illuminate.
Federal data production is simply too slow for the pace of geopolitical competition. Meaningful governance reform is what will allow leaders to make informed decisions during this tumultuous time.
Layers of Responsible Data Sharing
In a way, global competition keeps us moving forward as a nation. At the same time, leaders carry a mistrust for irresponsible data sharing. The need for speed in AI advancement cannot be understated. To constantly innovate is to remain internationally relevant, and widely available, shared data will facilitate innovation. However, in the name of both economic security and a battle for prevalent technologies, U.S. officials and private sector leaders have become choosy with whom they share information. The speakers highlighted this fear of easily abusable data if people with the wrong intentions gain access.
Lyngaas pushed back on this theory when she said this fear has brought us to the current state of federal data overclassification.
Trent Reasons, former partner at EYParthenon, provided context based on his prior role identifying choke holds between federal agencies. He confirmed there’s a lot the U.S. government doesn’t share within its own branches and departments. They fail to share data crucial to informed policymaking, often leading to departments wasting resources on producing a dataset that already exists within government. This is why data harmonization between sectors of the government would help ground the market. At the event, all economists agreed this is where AI is most helpful.
“I’m a big fan of a mosaic approach: Pull a lot of different types of methodologies, see what’s working for which types of participants and try to piece that together into a picture that can be additive for the United States’ methodology,” Reasons said about the country’s blind spots.
Private-sector innovators are already stepping into this void. Companies like Statebook are actively canvassing the national data landscape, aggregating public and proprietary data and building interfaces that make this information usable across industries, and even for government agencies themselves. By standardizing inputs from multiple sources and backtesting (i.e. applying contemporary data to historical data), these firms model the kind of harmonization federal leaders say they need but struggle to implement. Their work demonstrating responsible data sharing is not only possible but already underway. Collaboration with trusted private partners, and in some instances the public, can help close information gaps, reduce duplication, and accelerate the modernization effort we inch toward.
The Missing Link
Georgetown Research Professor Dr. Amy O’Hara emphasized a basic but often overlooked rule: people are more willing to share information when they understand how their data will be used. She noted falling survey participation often reflects collection methods that are confusing, outdated, or poorly matched to the user's needs. Instead of creating new surveys, she argues, agencies could tap into the huge amount of existing data that already sits underused across institutions.
“Since I left government, I’ve been trying to see if some of the work that I would hope agencies do, how you can get that done on the outside,” O’Hara added. She expressed hope for increased collaboration between private sectors, academia, states and the federal government.
When Data Disappears
Should we be investing more to better understand our own economy? The question lingered in the room. But for many economists, the current administration has scaled back, weakening the very tools policymakers need to make sense of rapid technological and geopolitical change. The Trump administration has been diluting funding for national statistics. Funding cuts to core federal statistical programs—along with the Department of Government Efficiency’s decision to end long-running studies tracking youth educational and career outcomes—have erased data once embraced by leaders anticipating workforce needs and designing policy.
These choices extend beyond education. The USDA survey data on household security is also being erased. The recently estimated 40 million individuals experiencing food stamp scarcity since the beginning of the shutdown is a number based on the cancelled report. This is an example of the type of data Reasons emphasized the government needs to account for the American people and our changing economy.
If the U.S. wants to remain competitive in a world where technology and geopolitics race before our eyes, it must rebuild a modern, trusted, and collaborative data system.