The report evaluates how the fragmentation of antitrust enforcement could affect economies, communities, and markets. Drawing on evidence from the economic literature, policy case studies, and business survey analysis, we document that efforts to expand state antitrust authority pose a central trade‑off. While state‑level policy experimentation may offer some benefits, there are economic costs associated with regulatory fragmentation. This fragmentation can lead to greater legal complexity, uncertainty, and coordination challenges, with broader effects on investment, hiring, and merger activity.
Emma Pollard
In this research report from Coastal and Oxford Economics, 800 U.S. business and technology executives were surveyed to understand how organizations are approaching AI initiatives that deliver direct business impact—things like automating workflows, improving customer service, supporting sales operations, or streamlining back-office functions.
Electricity demand is rising for industrial properties as automation, equipment electrification, and more complex functions are put to work inside of these traditionally low-intensity assets. Industrial users are increasingly competing for power capacity with other high-growth sectors, particularly data centers, where rapidly expanding electricity demand is placing additional pressure on grid infrastructure and availability.
There are reasons for young workers to be optimistic. History suggests the job market will eventually adapt to accommodate AI. Like every major technological shift before it, this transformation will make some roles redundant while creating other opportunities in their place. The question that worries me is how fast this change will take place: will the shift be smooth enough to benefit those entering the workforce now, or will my generation be left behind as collateral damage of the AI transition?
Spending on AI is currently the primary driver of incremental enterprise tech spend growth, with outlays rising rapidly to account for a growing share of total spend, which we forecast will continue over the next decade. Development and use of AI based products will grow to over $1.75 trillion by 2030—22% of total US enterprise tech spend—up from $230 billion today.
We expect enterprise technology spending in the Americas to grow 6.5% in 2026 in US$ terms, and 5.9% in real terms. This remains well above regional GDP growth, supported by AI-led investment as firms scale deployment and expand cloud and data infrastructure, even as overall growth settles to a more sustainable pace.
The rail supply industry plays a critical role in keeping the nation’s freight and passenger rail networks operating, investing, and modernizing. This new Oxford Economics study—supported by the Railway Supply Institute (RSI), REMSA, RTA, and Amtrak—provides the most comprehensive assessment to date of the industry’s economic footprint. Drawing on detailed operational and capital spending data across freight railroads, transit and commuter systems, and Amtrak, the report measures the activity that takes place within supplier firms, the activity supported through their domestic supply chains, and the additional economic activity generated by workers’ spending.
A dystopian future of AI-driven mass job destruction and workers vying for a shrinking pool of low-skilled roles is improbable, in our view. For that to happen, AI would need to generate huge productivity gains and mainly replace workers rather than enhance worker productivity. It’s possible that AI might be better at automating jobs than previous technological developments.
The US warehousing sector has undergone a profound transformation, evolving from traditional storage sites into high‑throughput logistics hubs that handle picking, packing, and goods movement at unprecedented scale. Employment has nearly tripled, mega‑facilities now anchor the industry’s footprint, and the mix of occupations has shifted toward item‑level fulfillment work, automation‑supported workflows, and increasingly technical roles.