#enterprise-adoption

#enterprise-adoption

The round was led by Google Ventures , with participation from existing investors, underscoring continued appetite for applied AI products that have already found a clear commercial use. Synthesia builds generative AI tools that let companies create videos using AI-generated avatars instead of cameras, studios, or presenters. The technology has found a strong foothold in corporate training, internal communications, and product explainers, areas where speed, scale, and consistency often matter more than production gloss.

Meanwhile, small teams are shipping products that would have required 100-person companies two years ago. The gap between the AGI debaters and the builders (those who are developing AGI systems) isn't philosophical-it's economic. While everyone waits for perfect AI, builders are dominating markets with today's "broken" tools, those that are functioning, albeit with some quirks, that will be worked out as the technology evolves. They aren't betting on future breakthroughs, they're betting on momentum.

Anthropic has announced a beta integration that lets you control Claude Code directly from Slack. Developers can now delegate coding tasks via a simple @Claude mention, with context from Slack conversations automatically included. The integration is available as a research preview. The new link is intended to reduce the transition between technical discussions and actual implementation. Bug reports, feature requests, and debugging discussions often arise in Slack, while the solution is worked out elsewhere.

Drawing on data from OpenRouter, closed models account for around 80% of overall usage globally while also generating roughly 96% of revenue. This dominance isn't driven by a "substantial performance gap", however. In fact, open models "routely achieve 90% or more" of the performance of closed counterparts. These models also benefit from "significantly lower prices" compared to closed models, researchers found, with operational costs up to 84% lower.

Most haven't even defined what they want their AI agents to do. The networking hardware manufacturer found in its 2025 AI Readiness Index that most companies are planning to deploy additional AI agents in the next few years, and 86 percent expect it to improve employee productivity within three years, but those expectations don't necessarily match the reality of what it takes for such an initiative to succeed.

It's the fastest growing product in our history,

For all the hype around blockchain, many enterprises remain hesitant to make the leap. The hesitation is not about whether blockchain has potential. It is about risk. Most blockchain projects today require committing to a single chain, which is placing a long-term bet on a rapidly shifting market. If the chosen chain fails, becomes too expensive to operate on or is outpaced by competitors, that investment could quickly unravel.

Enterprise customers clearly don't agree, or at least they didn't in January, when analysts spoke of tepid sales figures. Many biz users felt the 57 percent higher average purchase price and a lack of killer apps just didn't tick the box. When we looked again in July, the situation wasn't any better. Businesses didn't care about exclusive features such as Recall.

AI hype is following a well-worn path. During the dot-com boom, we were promised the internet would bring an overnight revolution. While it was revolutionary, some changes arrived quickly, but most unfolded over years, marked as much by failures and false starts as by lasting breakthroughs. I was at Inbound in San Francisco last week, and the AI hype was overwhelming. Conversations were either focused solely on the tactical use of AI or, interestingly, on reframing AI in our minds.