I’ve been watching the institutional side of digital assets for years, and every so often a single conversation shifts the tone of the entire sector. Last week that moment arrived when Brad Garlinghouse sat down at the SALT Wyoming Blockchain Symposium and spoke with unusual clarity about artificial intelligence, headcount, and the kind of revenue growth most private companies prefer to keep quiet. What he said was not the usual corporate fluff. It was a direct statement that Ripple intends to more than double its annual revenue in 2026 while continuing to hire, not shrink, its workforce.
Why This Moment Feels Different
Most executives these days treat AI like a magic wand they wave whenever the board asks hard questions about costs. Garlinghouse took the opposite path. He called the technology an enabler and an accelerant, not a replacement strategy. In his view, if a business already has real demand and working solutions, AI simply lets that business move faster and serve more clients without the usual friction. That framing matters. It separates companies that are genuinely scaling from those that are quietly cutting and hoping no one notices.
Ripple currently employs roughly 1,500 people around the world. Garlinghouse mentioned about 150 open positions. When I checked the public careers page a short time later, 94 roles were listed. The gap is normal. Some openings travel through internal channels or executive search firms. What stands out is the direction: the company is still adding talent while many others are freezing or reducing headcount. That alone tells a story about confidence in the pipeline.
The Revenue Claim That Turned Heads
Garlinghouse did not hedge. He said the firm expects a record year and will more than double revenue year on year in 2026. Because Ripple remains private, we do not get the audited quarterly statements public companies must file. The number is guidance, not a certified filing. Still, guidance of that size from a company that has spent more than a decade building payment rails, custody, and now prime brokerage services carries weight. Markets notice when a well-capitalized player talks about doubling the top line in a single calendar year.
The backdrop is not especially friendly. Digital asset prices have been choppy, and institutional budgets remain cautious. Against that backdrop, the projection feels aggressive. Yet the company has spent the past two years expanding far beyond its original cross-border payment focus. The $1.25 billion acquisition of Hidden Road, completed in October 2025 and rebranded as Ripple Prime, is the clearest example. That business now clears more than $3 trillion annually for over 300 institutional clients. According to the company, the prime brokerage operation tripled in size between announcement and closing. Again, those are company-supplied figures, but they help explain why leadership is willing to talk about rapid top-line expansion.
AI as an Expansion Tool, Not a Headcount Cutter
One of the more refreshing parts of the conversation was Garlinghouse’s refusal to blame AI for mass layoffs. He suggested that when companies announce large reductions and then point to artificial intelligence, they are often covering for earlier over-hiring. In his words, the technology becomes a convenient excuse for decisions that were already necessary. I tend to agree. Over the past eighteen months we have seen plenty of firms that expanded too quickly during the last cycle and are now using the AI narrative to tidy the balance sheet. Ripple’s stance is the mirror image: grow the business, keep hiring, and let AI multiply the output of the people already on the team.
AI, if you are in a business that has opportunity to grow and you’re serving customers and have compelling solutions, AI just lets you do that better and faster and stronger.
That sentence is worth sitting with. It assumes the company already has product-market fit and customer demand. AI then becomes a force multiplier rather than a replacement layer. Inside Ripple the approach shows up in concrete job postings. One senior engineering role, for example, calls for an “AI native operation” that uses agentic development methods to expand the payout network without relying solely on traditional headcount growth. The language is careful. It does not say fewer people. It says more capability per person.
Institutional Services Are the Real Engine
Garlinghouse spent a fair amount of time on the institutional side of the business. He believes more market participants are finally recognizing that the infrastructure layer, not the speculative trading layer, is where durable value sits. Ripple’s product suite now includes payment networks, custody, stablecoin issuance and management, prime brokerage, and corporate treasury tools. The recent acquisition of GTreasury brought an enterprise platform for managing digital assets and liquidity into the fold. These are the kinds of services large financial institutions actually buy year after year.
I’ve found that the companies quietly winning in this space are the ones that treat digital assets as another asset class to be serviced rather than a revolution that will replace everything overnight. Ripple’s messaging has stayed consistent on that point for years. The firm positions itself as a bridge between traditional finance and decentralized rails. When Monica Long, the company’s president, spoke earlier about 2026 predictions, she described AI models working alongside blockchains to automate liquidity management, margin calls, and portfolio rebalancing. That vision does not eliminate human teams. It increases the volume of activity those teams can handle.
Hiring Plans and the Public Careers Page
At the time of writing, Ripple’s public careers portal listed 94 open roles. Engineering positions focused on AI-driven operations featured prominently. The difference between the 150 figure Garlinghouse cited and the public number is not unusual. Recruiting pipelines move. Some roles sit with retained search firms. What matters is the signal: the company is still building capacity. In a market where many technology and financial firms have slowed or reversed hiring, continued expansion is itself a data point.
Perhaps the most interesting aspect is how AI is being framed inside those job descriptions. The language centers on agentic systems and AI-native workflows that allow existing teams to cover more ground. That is a very different posture from the cost-cutting narratives that dominate other boardrooms. It also aligns with the broader institutional thesis. Serving banks, asset managers, and large corporates requires reliability, compliance, and scale. AI can compress the time required to deliver those qualities, but it still needs skilled people who understand both the technology and the regulated environment.
What the Numbers Actually Suggest
Let me put the pieces side by side for a moment. Roughly 1,500 employees. Plans to keep hiring. A prime brokerage arm clearing more than $3 trillion a year for over 300 institutional clients. A stated expectation of more than doubling revenue in 2026. And an explicit rejection of the idea that AI must lead to headcount reduction. Taken together, the picture is of a private company that believes its addressable market is still expanding and that technology can help it capture that market faster.
Of course, private company guidance should always be treated with appropriate caution. Without audited public filings we cannot verify the baseline revenue number against which the doubling will be measured. We also cannot see the precise contribution of each business line. Still, the qualitative signals are consistent: continued investment in people, aggressive product expansion, and a clear institutional focus.
Separating Company Growth From Token Performance
One point that often gets lost in these discussions is the distinction between Ripple the company and XRP the digital asset. The firm can grow its payment, custody, prime brokerage, and treasury businesses without creating a one-to-one increase in demand for XRP. Many of the newer institutional services can operate with multiple settlement assets. Readers who assume every positive development for the company automatically translates into price appreciation for the token are making a category error. The commercial story and the token story overlap, but they are not identical.
That distinction matters for anyone trying to interpret the news. Garlinghouse was talking about corporate revenue, headcount, and product strategy. He was not issuing a market call on any digital asset. Keeping those lanes separate helps avoid the kind of over-interpretation that frequently follows executive appearances.
The Broader Context of AI in Financial Infrastructure
Across the industry we are seeing two parallel approaches to artificial intelligence. One treats the technology primarily as a cost lever. The other treats it as a capacity lever. The first group tends to announce large workforce reductions and then attribute them, at least in part, to AI. The second group keeps hiring while embedding AI tools that raise output per employee. Ripple has placed itself firmly in the second camp. Whether that choice proves correct will depend on execution and on whether institutional demand continues to materialize at the expected pace.
I’ve spoken with enough operators in the space to know that the practical challenges are real. Integrating agentic systems into regulated payment and brokerage workflows requires careful design. Compliance, audit trails, and operational resilience cannot be afterthoughts. The companies that succeed will be those that treat AI as infrastructure rather than as a marketing slogan. From the outside, Ripple’s public job descriptions and executive comments suggest they understand that distinction.
Looking Ahead to 2026
The next measurable tests are straightforward. Will the company continue to post meaningful numbers of open roles through the remainder of this year and into next? Will the revenue trajectory match the guidance once 2026 numbers eventually surface, whether through private reports or an eventual public listing? And will the institutional pipeline, particularly the prime brokerage and treasury businesses, keep expanding at the rates management has described?
None of those questions have answers yet. What we do have is a clear statement of intent from the chief executive of one of the more established players in the digital asset infrastructure space. The company is not waiting for a more favorable market. It is investing in people and technology now, on the assumption that demand for institutional-grade services will keep rising.
In my experience, the firms that treat soft markets as opportunities to build rather than as reasons to contract often emerge in stronger positions when conditions improve. That is not a guarantee. It is simply a pattern that has repeated often enough to be worth noticing. Ripple’s current posture fits that pattern.
Key Takeaways for Market Watchers
- Ripple is projecting more than double revenue in 2026 while continuing to hire rather than reduce staff.
- AI is being positioned as a growth accelerator, not as a justification for large-scale layoffs.
- The Hidden Road acquisition, now operating as Ripple Prime, has expanded the firm into high-volume institutional brokerage services.
- Public job listings emphasize AI-native engineering approaches aimed at scaling operations without proportional headcount growth.
- Company growth and token performance remain related but distinct stories.
The conversation at SALT Wyoming did not resolve every open question about Ripple’s future. It did, however, provide a clearer window into how one of the sector’s longer-standing companies is thinking about technology, talent, and growth at a moment when many peers are still retrenching. For those who follow the institutional side of digital assets, the remarks are worth tracking against the actual hiring and revenue outcomes that will unfold over the next eighteen months.
Markets move on narratives as much as on numbers. Right now the narrative coming out of Ripple is one of continued expansion, deliberate use of artificial intelligence, and confidence that institutional demand will support aggressive top-line targets. Whether that narrative holds will be decided by execution. For the moment, the company has drawn a clear line in the sand. The rest of the industry will be watching to see if it can hold it.
One final observation. In an environment where AI is frequently invoked as a reason to do less with fewer people, it is unusual and instructive to hear a chief executive argue for doing more with more people, augmented by better tools. That difference in posture may turn out to be one of the more important signals of the current cycle. Time will tell whether the confidence is justified. Until then, the stated plan remains ambitious, consistent, and worth following closely.
The institutional infrastructure layer of digital assets is still early. Companies that can combine reliable technology, regulatory awareness, and genuine customer traction stand to benefit as more traditional players move from exploration to production. Ripple’s current strategy is built on the belief that those conditions are already forming. The combination of AI investment, continued hiring, and a stated revenue doubling target is the concrete expression of that belief. For market participants trying to separate signal from noise, the coming year will provide the first real tests of whether the belief matches reality.
