Anthropic is loosening a central pillar of its internal safety doctrine — a move that signals how competitive, political, and national security pressures are reshaping the AI industry.
In a blog post detailing its new framework, Anthropic said constraints embedded in its two-year-old Responsible Scaling Policy could limit its ability to compete in a fast-moving market. The company is replacing what were effectively hard internal commitments with a more flexible, nonbinding structure, it says, which will evolve with technological and geopolitical realities.
The decision marks a turning point for a firm that has cultivated a reputation as the sector’s most safety-oriented developer and has frequently framed its mission in moral terms.
Register for Tekedia Mini-MBA edition 19 (Feb 9 – May 2, 2026).
Register for Tekedia AI in Business Masterclass.
Join Tekedia Capital Syndicate and co-invest in great global startups.
Register for Tekedia AI Lab.
Anthropic’s previous Responsible Scaling Policy included a notable provision: if the capabilities of its AI models exceeded the company’s ability to evaluate or control associated risks, it would pause further training. That clause has now been removed.
In its place, Anthropic introduced a “Frontier Safety Roadmap” built around public goals rather than firm commitments. The company said it will publish regular, detailed reports outlining model capabilities, threat assessments, and risk mitigation strategies, effectively shifting from pre-emptive restraint to ongoing transparency.
“Rather than being hard commitments, these are public goals that we will openly grade our progress towards,” the company wrote.
Anthropic acknowledged that its earlier approach was partly designed to create a “race to the top” in which competitors would adopt similar guardrails. That dynamic did not materialize. Instead, the company concluded that unilateral constraints could leave it strategically disadvantaged while doing little to slow global AI development.
The revised policy reflects a recalculation: in an environment where other actors — including foreign competitors — continue to scale rapidly, pausing development may not meaningfully reduce systemic risk. The company, founded by former OpenAI leaders who warned about the long-term risks of advanced artificial intelligence, argued that responsible developers slowing down while less cautious actors accelerate could “result in a world that is less safe.”
Pentagon Pressure and National Security Stakes
The policy shift coincides with a high-stakes standoff between Anthropic and the U.S. Department of Defense. According to CNN, Defense Secretary Pete Hegseth gave Anthropic CEO Dario Amodei a deadline to reconsider certain AI safeguards or risk losing a $200 million Pentagon contract and being designated a supply chain risk under the Defense Production Act.
According to a source familiar with discussions, Anthropic is unwilling to drop two positions: opposition to AI-controlled weapons and resistance to mass domestic surveillance powered by AI. The company believes current AI systems are not sufficiently reliable to autonomously operate weapons and that legal frameworks governing large-scale surveillance remain underdeveloped.
Anthropic has said its policy update is separate from its Pentagon discussions. Even so, the overlap in timing underscores a broader tension: frontier AI companies are now central to national security strategy. Their internal safety frameworks are no longer purely corporate governance tools but elements in negotiations with the federal government.
The political climate also plays a role. Anthropic acknowledged that its prior safety posture was misaligned with what it described as Washington’s current anti-regulatory environment. Voluntary self-restraint, without parallel industry adoption or government mandate, may be commercially and politically unsustainable.
The Economics of Scaling and the AI Arms Race
Anthropic’s decision cannot be separated from competitive dynamics. The company is locked in an escalating race with OpenAI and other major developers to deliver more capable enterprise AI systems for coding, research, automation, and workflow management.
The economics of frontier AI amplify this pressure. Training increasingly powerful models requires massive capital investment, access to advanced chips, and long-term infrastructure commitments. Investors expect returns tied to rapid capability gains and product deployment. A self-imposed pause risks eroding market share and signaling weakness.
Jared Kaplan, Anthropic’s chief science officer, told Time that the change was rooted in pragmatic safety considerations.
“We felt that it wouldn’t actually help anyone for us to stop training AI models,” he said, adding that unilateral commitments made less sense “if competitors are blazing ahead.”
The strategic logic reflects a familiar security dilemma: if one actor slows development for ethical reasons while others continue scaling, the relative balance of power shifts — potentially in favor of less constrained entities.
Anthropic has long sought to distinguish itself through openness about model risks. The company has published research showing that its own systems could engage in manipulative or blackmail-like behavior under certain controlled conditions. It recently donated $20 million to Public First Action, a group advocating for AI safeguards and public education.
Under its new framework, Anthropic is emphasizing transparency as the core mechanism of accountability. The company pledged to publish detailed capability assessments and threat models at regular intervals, allowing external observers — policymakers, researchers, and civil society groups — to scrutinize its progress.
An Anthropic spokesperson described the revised framework as “the strongest to date on the level of public accountability and transparency.”
The philosophical shift is subtle but significant. The earlier policy prioritized conditional restraint: pause if risk thresholds are crossed. The new approach prioritizes iterative risk management: continue scaling while disclosing and mitigating risks in real time.
Implications for AI Governance
Anthropic’s recalibration highlights a broader transition in AI governance. Early discussions in the sector centered on voluntary red lines and precautionary pauses. As commercial stakes and geopolitical competition intensified, the feasibility of unilateral commitments diminished.
If leading developers no longer believe they can slow independently without strategic harm, meaningful restraint may require binding regulation or coordinated international agreements — both of which remain uncertain.
At the same time, Anthropic’s refusal to endorse AI-controlled weapons and mass surveillance places it at odds with some government priorities, even as it seeks defense contracts. That tension illustrates the dual identity of frontier AI firms: commercial enterprises competing in global markets and critical infrastructure providers embedded in national security planning.
Anthropic’s decision to loosen its guardrails is seen not as a signal abandonment of safety. Rather, it is believed to be an attempt to reconcile its founding ethos with the realities of an accelerating AI arms race.