LinkedIn’s New Tool Lets You Test the Outputs of Various AI Models

Why It Matters

Crosscheck gives professionals a data‑driven way to choose AI solutions, accelerating adoption while providing developers real‑world feedback. It also highlights the growing influence of platform‑level AI curation in the enterprise software market.

Key Takeaways

• Crosscheck lets Premium users compare AI model outputs side‑by‑side.
• Users rate responses; feedback is shared with model developers.
• Leaderboards rank AI tools across professional verticals.
• Microsoft’s OpenAI investment may influence model weighting.
• Study shows 89% execs see little productivity gain from AI.

Pulse Analysis

LinkedIn’s Crosscheck arrives at a moment when enterprises are scrambling to make sense of an ever‑expanding AI landscape. By aggregating access to models from OpenAI, Anthropic, Google, Microsoft and others, the tool removes the friction of juggling multiple accounts and APIs. Users simply enter a prompt, receive two anonymized responses, and rate them, creating a crowdsourced benchmark that reflects real‑world professional use cases. This approach not only democratizes model comparison but also positions LinkedIn as a neutral testing ground for AI performance across sectors.

The feedback loop embedded in Crosscheck is a strategic win for AI developers. Every rating is relayed back to model creators, offering granular insights into how their systems handle business‑centric queries. Such data can accelerate fine‑tuning and highlight gaps that traditional lab testing might miss. However, LinkedIn’s corporate parent, Microsoft, has poured billions of dollars into OpenAI, potentially tilting the leaderboard in favor of OpenAI’s offerings. While the platform claims anonymity, the underlying partnership dynamics could subtly influence which models rise to the top, prompting observers to watch for bias in the rankings.

Beyond the platform itself, the broader market signals a cautious optimism about AI’s impact on productivity. A recent National Bureau of Economic Research study of 6,000 executives across the U.S., U.K., Germany and Australia found that 89% saw virtually no change in labor productivity over the past three years despite widespread AI adoption. Tools like Crosscheck may help bridge that gap by guiding firms toward models that deliver measurable gains. As AI matures, data‑driven selection mechanisms will become essential for translating hype into tangible business outcomes.