Computing Power Is Accelerating—But Collaboration Is Slowing Down
As a frontline delivery expert, over the past few years I’ve observed a rather surreal phenomenon: the speed at which people write code and draft proposals is visibly accelerating—but overall corporate decision-making feels like it’s hitting the brakes.
Many enterprises are rushing to integrate various third-party AI assistants and intelligent work agents. Employees use AI-powered office tools to generate ten-thousand-word reports in seconds; design proposals pour out in batches.
Yet what’s the result? Information production has exploded—but organizational bandwidth for digesting that information hasn’t kept pace.
Sales teams dump fifty-page AI-generated client analyses directly into Docs; product and R&D teams frantically scroll through cascading streams of IM messages just to spot key points; managers pack their Calendars with “alignment meetings,” yet when it comes time to make decisions, even a simple Approval stalls for hours, going nowhere. No matter how powerful computing capacity becomes at any single point, it cannot bridge the invisible chasm between departments.
Companies buy more and more tools—yet cross-departmental information flow grows slower and slower. When point-level computing power becomes infrastructure, the meager efficiency gains it delivers are quickly consumed entirely by the friction costs of collaboration.
What Determines Efficiency Isn’t Computing Power—It’s Production Relations
We often fall into a misconception: that equipping employees with third-party AI assistants will instantly lift the entire organization into orbit. This is, in fact, an illusion born of technological determinism.
From a systems-theory perspective, AI elevates productivity—but organizations operate on production relations. If you simply pile up isolated intelligent work agents without integrating underlying data, you’ll only deepen information silos.
Consider this: deep insights generated by AI remain trapped in Docs, unread by anyone; product and R&D teams continue debating minor details back and forth in IM; after a one-hour Video Meeting, management still hasn’t established a concrete Approval workflow.
Ultimately, what strangles enterprise performance isn’t insufficient computing power—it’s excessive resistance during information flow.
No matter how fast computing power becomes, it cannot penetrate departmental walls. AI can help you write code and craft copy—but it cannot cure chronic organizational ailments like vague business-line requirements or leadership’s inability to drive change.
Building a Collaborative Foundation to Harness AI Productivity
To break down departmental walls, adding more tools won’t help—you must reconstruct the foundation. That’s why we consistently advocate integrating intelligent work agents into the Lark ecosystem.
Even the most powerful computing needs a riverbed; even the smartest AI needs a foundation.
Insights generated by third-party AI assistants can be directly archived in Lark Docs, transforming them into team-wide consensus. Core data extracted from those insights can be effortlessly entered into Multi-dimensional Tables, becoming dynamic, real-time operational dashboards.
When a project hits a bottleneck, simply create a group chat in IM to align stakeholders. When disagreements arise, launch a Video Meeting on the spot—and use the Calendar to schedule next steps right there. After the meeting, push decisions straight into the Approval workflow.
There’s no jarring system switching here—only natural alignment among people, business processes, and AI. Tools cease to exist as isolated islands floating on the surface; instead, they become fully integrated organs embedded within business workflows.
True efficiency gains don’t come from pushing AI to run faster—they come from ensuring everything AI produces flows smoothly through the organization’s business bloodstream.
From Tool Procurement to Reshaping the Organizational Collaboration Network
Many enterprises still purchase AI using the outdated mindset of “buying software.”
They assume stockpiling more third-party AI assistants will somehow assemble combat readiness. But reality is stark: no matter how powerful point-level computing may be, without a robust collaboration network to absorb and activate it, the result is usually little more than an expensive toy.
Today, what determines competitive advantage is no longer who buys the most tools—but who best weaves existing tools into a cohesive network.
That demands a shift—from a “tool mindset” to an “ecosystem mindset.” Build a digital workplace environment suited for the AI era, anchored on Lark. Let insights produced by intelligent work agents flow naturally into Docs and Multi-dimensional Tables; let every Video Meeting and every Approval become tangible, actionable nodes within business operations.
Only then can point-level technological advantages be fully transformed into organization-wide collaborative moats.
As AI tools flood the market, the entity holding the smoothest, most resilient collaborative foundation will hold pricing power in the new era.