SEC’s Atkins Charts New Course For Crypto Regulation In Latest Shift Toward Clarity

bitcoinistPublicado em 2026-03-20Última atualização em 2026-03-20

Resumo

SEC Chair Paul Atkins announced a shift in the agency's approach to crypto regulation, moving away from enforcement-driven actions toward clearer, more constructive rules. He criticized the previous strategy for creating uncertainty and driving innovation offshore. The SEC and CFTC jointly issued interpretive guidance clarifying that crypto assets should not be treated as securities and identified four exempt categories: digital commodities, tools, collectibles (like NFTs), and stablecoins. Atkins also disclosed plans for a "startup exemption" and an upcoming safe harbor proposal to allow limited experimentation without full SEC compliance. The new guidance aims to provide regulatory clarity and keep crypto innovation within the U.S.

US Securities and Exchange Commission (SEC) Chair Paul Atkins said that the commission is moving away from a purely enforcement-driven response to digital assets and toward clearer, more constructive rules — a shift he framed as necessary to keep crypto activity onshore.

Clearer Path For Crypto Classification

In a CNBC interview, Atkins criticized the SEC’s prior approach, which relied heavily on enforcement actions rather than publishing concrete rules. He argued that this posture created uncertainty for businesses and pushed innovation and activity to other jurisdictions.

“Perhaps nowhere has the cost of failing to do so been more apparent than in our treatment of crypto assets,” he said, noting that past messaging often amounted to “adapt to us—or else.”

Atkins described the agency’s newly issued interpretive guidance, jointly prepared with the Commodity Futures Trading Commission (CFTC), as the start of a more transparent and pragmatic regulatory path.

The joint guidance, released earlier this week, aims to clarify how federal securities laws apply to a broad range of digital tokens. According to Atkins and the agencies’ interpretation, crypto assets should not be treated as securities.

The guidance further outlines how certain token transactions or structural changes can move a token into — or out of — securities regulation, providing a framework for markets to better assess compliance needs.

As part of the new stance, the SEC has identified four categories of crypto assets that it no longer views as securities: digital commodities, digital tools, digital collectibles such as non-fungible tokens (NFTs), and stablecoins.

The agencies said this position reflects collaboration between the SEC and CFTC and aligns with recent legislative proposals, such as the GENIUS Act, with respect to stablecoins. At the same time, tokenized securities remain deemed as securities.

Upcoming Plans Disclosed By Atkins

Atkins further discussed a “fit‐for‐purpose startup exemption” for crypto assets. He suggested the agency consider allowing early-stage crypto entrepreneurs to raise limited capital or operate for a defined period without being fully subject to the agency’s rules.

The Commissioner also expects the SEC to publish a proposal on crypto safe harbors for public comment in the coming weeks. He indicated that the proposal will incorporate the innovation exemption, which would carve out temporary relief from securities laws to enable companies to experiment with new business models.

Atkins stressed that the prior ambiguity had real consequences. By leaving rules implicit and relying on enforcement, the agency invited uncertainty that discouraged some firms from operating in the US and complicated compliance for those that did.

The fresh guidance, he suggested, is a corrective measure meant to bring clarity and to keep digital asset innovation within the US regulatory environment.

The daily chart shows the total crypto market cap dropping toward $2.37 trillion. Source: TOTAL on TradingView.com

Featured image from OpenArt, chart from TradingView.com

Perguntas relacionadas

QWhat is the main shift in the SEC's approach to crypto regulation as described by Chair Paul Atkins?

AThe SEC is moving away from a purely enforcement-driven response and toward establishing clearer, more constructive rules to provide regulatory certainty and keep crypto activity onshore.

QWhat was the joint guidance issued by the SEC and CFTC intended to clarify?

AThe joint guidance aims to clarify how federal securities laws apply to a broad range of digital tokens, stating that crypto assets should not be treated as securities and outlining how transactions can move a token into or out of securities regulation.

QAccording to the new SEC stance, what are the four categories of crypto assets that are no longer viewed as securities?

AThe four categories are digital commodities, digital tools, digital collectibles such as NFTs, and stablecoins.

QWhat is the 'fit-for-purpose startup exemption' that Commissioner Atkins discussed?

AIt is a proposal to allow early-stage crypto entrepreneurs to raise limited capital or operate for a defined period without being fully subject to the SEC's rules, providing temporary relief to enable experimentation with new business models.

QWhat negative consequence did Atkins attribute to the SEC's prior regulatory approach of relying on enforcement actions?

AHe stated that the prior approach created uncertainty that discouraged some firms from operating in the US and complicated compliance for those that did, effectively pushing innovation and activity to other jurisdictions.

Leituras Relacionadas

From South Korea to the United States: Blue-Collar Jobs Are Becoming Increasingly Popular, Thanks to AI

AI is reshaping the labor market's value proposition. The traditional four-year college degree is losing its appeal as a guaranteed career path, while skilled blue-collar trades like electricians, welders, and plumbers are experiencing historic demand and wage premiums. This shift is driven by dual pressures: AI's displacement of certain white-collar roles and a booming need for physical infrastructure and data center construction. Data confirms the trend. In the U.S., vocational school revenue surged, and a significant portion of recent layoffs are AI-related. Surveys show a majority of Gen Z adults plan to pursue blue-collar work, citing better job security against AI automation. Vocational education interest has exploded recently. Experts cite a psychological shift as younger generations seek tangible, AI-resistant careers and avoid high student debt. In many cases, salaries for skilled trades now match or exceed those requiring a bachelor's degree. In South Korea, semiconductor vocational high schools boast near-total employment, with graduates securing high-paying roles at companies like Samsung. The shortage is structural, exacerbated by a retiring baby boomer workforce and massive infrastructure projects. Companies like JPMorgan Chase, Meta, and Lowe's are investing heavily in training programs. However, overcoming historical stigma and a "perception gap" around trade careers remains a key challenge to closing the talent gap.

marsbitHá 21m

From South Korea to the United States: Blue-Collar Jobs Are Becoming Increasingly Popular, Thanks to AI

marsbitHá 21m

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

Qualcomm reported its Q3 FY2026 results (ending June 2026), with revenue of $9.95B, down 4% YoY but above expectations. Gross margin declined to 53.1%, pressured by rising costs across manufacturing and memory. Key business segments showed mixed performance: Handset revenue fell 19.6% YoY to $5.09B, dragged by an 11% decline in non-Apple Android shipments and weaker high-end mix. Conversely, Automotive revenue surged 61% to $1.59B, and IoT grew 9% to $1.83B. Core operating profit dropped 41% YoY due to margin compression and higher expenses. Management's Q4 FY2026 guidance projects revenue of $9.7B-$10.5B, in line with consensus, but Non-GAAP EPS guidance of $2.05-$2.25 fell short of expectations. Amidst persistent weakness in its core handset market, Qualcomm is pursuing growth in AI, focusing on Edge AI (smartphones, PCs, automotive) and Data Center AI. Its data center strategy includes four pillars: AI accelerators (e.g., AI200), commercial CPUs (Dragonfly C1000), custom silicon, and connectivity solutions. While these initiatives initially boosted its stock, concerns over AI capital expenditure sustainability have since erased those gains. The company targets $5B in data center revenue for FY2027 and $15B for FY2029. The report concludes that with the traditional handset business still under pressure, the data center opportunity is currently viewed as a longer-term option, and a more conservative valuation based on core operations may be warranted until AI contributions materialize.

marsbitHá 25m

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

marsbitHá 25m

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

At the 2026 YC Startup School, Jeff Dean outlined his vision for AI's next phase, shifting focus from simply scaling models to building intelligent, autonomous systems. He believes AI's progress is no longer just about creating smarter models, but about integrating them into systems capable of long-term, iterative work, automated experimentation, and continuous learning. This evolution moves the competition from "who has the bigger model" to "who can best organize intelligence." Dean suggests AI capabilities are now comparable to a junior engineer, enabling the automation of complex workflows. However, the true challenge and opportunity lie in managing these AI "workers" at scale. He emphasizes the importance of **context engineering**—structuring tools, memory, and feedback loops—over raw model power. For startups, this means building deep expertise in niche domains where general models currently fail (near 0-1% success rates), leveraging proprietary data, specialized tools, and domain-specific evaluators. A recurring theme is re-examining fundamental constraints. Dean's past work, like moving Google's search index to memory or creating the TPU, stemmed from questioning outdated assumptions about hardware and cost. He sees similar inflection points today, particularly in **specialized inference hardware** to drastically reduce latency and energy consumption for real-time Agent operation. Notably, he points out that in modern AI systems, the dominant cost is often not computation but **data movement**. Reliable, long-running Agents require robust system design, borrowing concepts from distributed computing like checkpointing, state management, and parallel exploration to handle failures and maintain progress over days or weeks. As AI automates execution, the scarcest human skills will shift to **defining clear specifications**, **judging what problems are worth solving** (taste), and designing effective feedback loops. Ultimately, Dean's framework prioritizes understanding the problem deeply, identifying the true bottlenecks, and systematically building closed-loop systems where AI can not only perform tasks but also improve AI itself.

marsbitHá 25m

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

marsbitHá 25m

Trading

Spot
活动图片