Humanly shifted from recruiting tools to selling ready-to-hire candidates, a move that shows AI firms chase revenue as much as headlines. Critics say some firms stoke public fear about futuristic risks to distract from present harms and to defend their market position. Others within the industry say safety is a genuine priority and that warnings are meant to prepare regulators and the public. The mix of fundraising, product pivots and public rhetoric changes what AI companies sell and how they win customers.

From tools to services

Humanly began as software for recruiters. The firm automated screening, scheduling and initial communications. It helped reference checks and high-volume hiring. Humanly is based in Bellevue, Washington. It was founded in 2018. The company has raised $52m to date and closed a $25m Series B round that included SEEK Investments, Drive Capital, Zeal Capital Partners and Converge.

Now Humanly is repositioning. Prem Kumar, the CEO, said the company is becoming a "service-as-a-software" business. Instead of only giving recruiters tools, Humanly wants to provide pre-vetted, ready-to-hire candidates. Kumar said they're not pivoting but reinventing how they go to market.

That change is a familiar move in tech. Software firms often translate code and automation into services that customers will pay recurring fees for. In Humanly's case, the market math helps explain the shift. Recruiting software is a roughly $14 billion market. The market for actually placing people in jobs is about $500 billion. The larger pool of revenue changes the incentives.

Fear as a business tactic

Alongside product shifts, corporate messaging matters. Some critics argue that parts of the AI sector amplify fears about catastrophic future systems. They say apocalyptic language keeps attention on hypothetical outcomes.

That attention can help valuations and justify rapid expansion of capability and hiring.

Tech leaders counter that warnings about future risks are sincere. They say safety work needs time and resources. They also say regulators must recognise the complexity of the technology. The debate is consequential. When companies frame themselves as the only ones who can build safe systems, that framing alters the political dynamics around regulation and oversight.

Academics and commentators have flagged a worry. If fear of far-future risks dominates the public story, then present harms can be sidelined. Those harms include biased hiring tools, automation that changes gatekeeping, and platforms that concentrate access to labour markets. The argument in the public debate isn't only about truth. It's about who benefits from the story that gets told.

Mastheads

Small firms and specialised services

Not every technology firm follows the blockbuster publicity route. Some focus on narrow, practical problems. Wayne Tseng, who ran a firm called eTranslate, made that case. His company helped software developers create language variants of their products. ETranslate had a technology arm and a language and cultural services arm.

Tseng's background illustrates a different side of tech. He studied computer engineering and later took a PhD in Melbourne. He lectured at RMIT before launching his company. His firm worked with all three tiers of government and provided cultural communication services to local authorities. Those are concrete contracts. They look a lot like classic software consulting or product work rather than media-friendly visions of general artificial intelligence.

Smaller vendors like eTranslate show how technology companies sell practical value. They find buyers with specific problems. The group offer repeatable services. They build steady revenue instead of attention-driven valuations. That business model matters because it anchors technology development in customer needs. It also shapes how firms allocate engineering time and set priorities for product road maps.

How markets and narratives interact

Investors influence firm behaviour. Funding rounds reward growth prospects and addressable market size. Humanly's move toward supplying candidates taps a much larger market. Investors who backed the Series B are betting that the company can scale a service layer on top of automation.

At the same time, public narratives affect policy. When major firms emphasise hypothetical global risk, they can influence how regulators frame rules. That can slow rules aimed at immediate problems. It can also shift public scrutiny toward a smaller set of issues that match headline narratives.

The combination of investor pressure and public messaging changes incentives inside companies. Engineering teams may prioritise features that scale quickly. Legal teams may craft statements that speak both to regulators and to shareholders. Marketing teams may frame messages to protect valuation. All those choices are business choices. They follow from firm-level incentives rather than from some unique moral character of "AI" as a category.

Humanly provides concrete operational details that show the shift from tool to service. The company said it conducts about 9,000 interviews per day as part of its screening. It's striking that a firm built on automation is now offering a candidate database that aims to be continuously refreshed and pre-interviewed. That product changes the customer relationship. Employers buy candidates as a service rather than software as a licence.

Those figures matter because they show scale and a clear revenue pathway. A company that can run thousands of automated interviews daily can build a supply of screened candidates. That supply is a commodity that clients will pay for if it reduces hiring time and mis-hires. The operational fact therefore explains the strategic move and the investor interest.

Public claims about safety and existential risk aren't just rhetoric. They shape hiring, product road maps and regulation. When industry leaders emphasise long-term dangers, they can win space to develop technologies with less immediate oversight. That can be a deliberate strategy or a sincere stance. Either way, the result affects which problems get fixed first.

For many users and buyers, the immediate effects of AI matter more than distant hypotheticals. Job seekers face application systems that filter them out. Employers face an overload of applicants helped by automation. Governments negotiate oversight that will govern both recruitment software and broader AI systems. The technology's present uses therefore determine the day-to-day stakes for millions of people.

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Humanly's shift to selling candidates, and its reported 9,000 interviews a day, shows how fundraising, product pivots and public rhetoric shape what AI companies sell.

This article was created with AI assistance.