Really Simple Licensing for B2B Sites: Should You Adopt RSL or Ignore It?

What Is Really Simple Licensing and Should B2B Sites Adopt It?

Really Simple Licensing, or RSL 1.0, is a machine-readable standard that lets a website state licensing and compensation terms for AI crawling alongside robots.txt, and most B2B companies should not adopt it site-wide because their marketing content exists to be consumed and cited, not licensed for a fee.

RSL emerged in September 2026 as an open standard backed by a coalition of large publishers and platforms, designed to give content owners a way to signal, in a machine-readable format, whether an AI crawler may use their content freely, must pay for it, or may not use it at all. It sits alongside robots.txt rather than replacing it, adding a licensing and compensation layer on top of the existing allow-or-block signal.

The standard was built by and for organizations whose core product is the content itself: news publishers, research houses, and media companies that lose direct revenue every time an AI system summarizes their reporting or analysis without payment or a click-through. A B2B software company, agency, or professional services firm sits in nearly the opposite economic position, and applying a publisher-oriented standard without translating it to that different economics is where most of the coming missteps will happen.

The rest of this analysis works through who should adopt RSL, who should not, the realistic middle path most B2B organizations will land on, and how to make the decision at the level of individual content assets rather than as a single site-wide switch.

What Does RSL 1.0 Actually Do, Mechanically?

Mechanically, RSL lets a site publish a licensing file, similar in spirit to robots.txt, that states per-path or per-content terms such as free use, attribution-required use, paid use, or no use, which compliant AI crawlers are expected to read and respect before ingesting content.

The standard supports multiple licensing tiers rather than a single on-off switch. A site can mark some sections as freely crawlable, others as requiring attribution, and others as requiring a negotiated fee or a per-use payment, all within the same file. This granularity is the standard's main technical contribution over the blunt allow-or-block choice that robots.txt has always offered.

Adoption depends on AI crawlers actually honoring the file, which is not guaranteed the way search engine compliance with robots.txt became a near-universal norm over two decades. Compliance is currently strongest among the coalition members that backed the standard's launch and weaker or unproven among smaller or less cooperative AI systems, which matters directly for how much protection or leverage a B2B site can realistically expect from adopting it in the near term.

Why Is RSL Built for a Different Kind of Business Than Most B2B Companies?

RSL is built for businesses whose content is the product itself, while most B2B companies are in the opposite position: their content is a customer acquisition cost, produced specifically to be found, read, cited, and eventually to influence a buying decision.

A news publisher's article is the revenue event. A B2B company's blog post, benchmark guide, or comparison page is not the revenue event; it is a step in a funnel that leads to a demo request, a trial signup, or a sales conversation. When an AI system cites that blog post in an answer, the publisher analogy says the company lost value that should have been paid for. The B2B reality is closer to the opposite: the citation is unpaid distribution and brand exposure the company would otherwise have to buy through paid media or outbound effort.

This distinction is the single most common thing B2B marketers miss when they hear about RSL and assume it is something they should rush to implement. Applying a licensing wall to marketing content built to generate demand does not protect revenue, it removes the content from the exact answer surfaces where a prospective buyer is most likely to first encounter the brand.

Who Should Actually Adopt RSL?

The organizations that should adopt RSL are those with content that functions as a direct revenue product in its own right, separate from lead generation, such as research firms, data providers, benchmark publishers, and media arms of larger companies.

A market research firm that sells access to proprietary survey data or industry benchmarks has a legitimate case: if an AI system can summarize the firm's paid report for free, it erodes the subscription or report-purchase revenue that funds the research in the first place, in the same way it erodes a news publisher's subscription revenue. A company that operates a paid data feed, a licensed benchmark index, or a subscription research product sits in this same category.

Within a larger B2B company, this often applies to a specific division rather than the whole organization, such as an analyst-style research arm that sells reports as a standalone product, or a proprietary industry benchmark that the company licenses to other vendors. These assets behave economically like publisher content even though they sit inside a company whose broader marketing site behaves like a demand generation engine.

Who Should Leave RSL Alone?

Companies whose content exists primarily to attract, educate, and convert prospective buyers should leave RSL off their marketing site entirely, because restricting AI crawler access to that content works directly against the goal of being found and cited in AI-generated answers.

This covers the large majority of B2B websites: product pages, comparison content, how-to guides, blog posts, case studies, and most gated content used for lead generation. The commercial logic of these assets depends on maximum qualified visibility, not on capturing a licensing fee per crawl. Blocking or restricting AI crawlers on this content sacrifices free distribution in exchange for a compensation mechanism that, for most B2B categories, will not generate meaningful revenue even if AI platforms fully honor the standard.

A useful gut check is to ask whether the company would be upset if a human research analyst read the page, took notes, and summarized it accurately in a report shown to a prospective buyer. For the overwhelming majority of B2B marketing content, the honest answer is that this is exactly the intended outcome, and an AI system doing the equivalent should be treated the same way.

What Does the Middle Path Look Like in Practice?

The middle path most B2B organizations should take is asset-specific: license the narrow set of paid research or proprietary data products under RSL while leaving the marketing site, blog, and product documentation fully open to AI crawlers.

In practice this means a company with a paid industry report or a subscription benchmark tool applies RSL terms only to that specific subdirectory or content type, while every other section of the domain, including the pages designed to build category authority and attract inbound interest, remains governed by a standard, permissive robots.txt policy. This split lets a company protect the handful of assets with real standalone commercial value without touching the much larger set of assets whose value depends on being widely cited.

The practical difficulty is that RSL implementation typically happens at the domain or platform level through a CMS or CDN configuration, so getting this split right requires deliberate, path-level configuration rather than a single toggle, and it requires someone to maintain a clear internal map of which specific assets are licensed and which are open, because that map will need to be revisited every time new paid research or new marketing content is published.

What Is the Operational Cost and Risk of Adopting RSL?

The operational cost of adopting RSL includes ongoing technical maintenance, legal review of licensing terms, and a real risk of accidentally suppressing a company's own AI visibility if the licensing file is applied too broadly or configured incorrectly.

Technical maintenance is not trivial: someone has to own the licensing file, keep it synchronized with which content is actually gated or paid, and monitor whether AI crawlers are respecting it as intended, similar to how larger sites already need a dedicated owner for robots.txt and XML sitemap hygiene. Legal review adds another layer, since setting compensation terms typically involves defining what counts as an acceptable use, which historically takes real negotiation time even in mature licensing markets.

The bigger risk is a misconfiguration that quietly blocks or discourages AI crawlers from marketing pages that were never meant to be restricted. This is a realistic failure mode precisely because RSL is new, tooling around it is still maturing as of this writing, and a mistake made once during initial setup can suppress AI citation volume for months before anyone notices the drop in an AI visibility dashboard, especially at a company that is not already tracking citation frequency as a baseline metric.

How Should You Decide: Asset by Asset, Not Site by Site?

The right way to decide on RSL is to run a simple content asset triage across four buckets rather than making one site-wide decision: content that exists purely to generate demand and should stay fully open, content that has some standalone commercial value but still benefits more from visibility than restriction, content that is a genuine paid product and is a reasonable licensing candidate, and content that is already gated behind a paywall or login where a licensing signal simply formalizes an access rule that already exists.

Running every asset on the domain through those four buckets, even informally in a spreadsheet, forces a company to be explicit about which pages are actually revenue products versus which pages are acquisition costs, and that clarity tends to be useful independent of the RSL decision itself. Lemniscate Growth runs this kind of asset triage as part of its AI intelligence pillar for clients evaluating new AI-crawler standards, because the decision usually reveals more about a company's content strategy than it does about licensing mechanics.

For most B2B organizations, the honest output of this triage is that the fourth and third buckets are small or empty, the second bucket is worth a cautious case-by-case look, and the first bucket, the openly discoverable marketing content, is the overwhelming majority of the site and should stay exactly as open to AI crawlers as it is today.