Why Your AI Is Advancing — and Your Enterprise Isn’t

The five friction points preventing your AI investment from delivering real business impact.

작성자: Peter Doolan, Chief Customer Officer, Slack2025년 12월 16일

Looking back at 2025, I’ve had the privilege of sitting down with hundreds of C-suite leaders at our innovation summits, in boardrooms, and in working sessions across the globe.

These are sophisticated executives with ambitious visions for agentic work. They have run the pilots. They have refined the prompts. They have the data. And yet, in conversation after conversation, a specific frustration surfaces:

“We’ve deployed AI everywhere, but our organization feels less intelligent than before.”

This is the Intelligence Disconnect.

Technology isn’t the problem. AI agents are generating brilliant insights, but only within the confines of everything it has access to, which is usually a single department or team. This intelligence doesn’t reach the people who need it, when they need it. Instead of a unified brain, organizations have built a collection of brilliant, isolated islands.

Through all our conversations this year, we’ve identified the culprits. It’s not one single roadblock; it is five specific friction points that are preventing your AI investment from turning into business impact.

The five friction points stalling enterprise intelligence

Most organizations aren’t facing these sequentially; they are facing them all at once, creating a compounding drag on speed and innovation.

  1. The Org Chart trap. Your org chart is a map of where intelligence stops flowing. When you deploy AI into a rigid structure, you simply encode that isolation into software. A Service Agent might spot a churn pattern, but if that insight hits the wall of the Service department and never reaches Product or Sales, the organization remains reactive, not proactive.
  2. Tool sprawl. Departments often solve visibility problems by buying specialized tools. Individually, each tool makes sense. Together, they create legacy debt. This fragments the landscape before intelligence can move. We see teams drowning in logins and dashboards, trying to piece together a picture that should be presented to them whole.
  3. Data Fragmentation. Your CRM calls a human a “lead.” Marketing calls them a “prospect.” Sales calls them an “opportunity.” Same human, different identities, no shared history. This fragmentation leads to what researchers are now calling workslop: AI-generated content that creates the illusion of progress but lacks the grounded substance to be actionable.
  4. High-speed AI in Low-speed queues. We are currently plugging agents capable of instant, millisecond decisions into workflows designed for human-to-human coordination. The result? Bottlenecks. High-speed intelligence sits waiting in approval queues built for a different era.
  5. The “last mile” context fail. Even when organizations fix the data and the tools, the “last mile” fails. Knowledge workers switch between ten or more applications daily, hunting for context. By the time they have gathered the information they need to make a decision, they’ve lost an hour—and the market has moved on.

Solving the Intelligence Disconnect with proximity

Recognizing these friction points is the first step. Solving them requires a shift in mindset.

We found that intelligence value correlates directly with proximity: how close the insight is to where the work is actually happening.

Consider two scenarios:

  • Scenario A: Your Sales Agent generates a critical risk factor on a deal. That insight lives in a database record. To act, an account executive must log into your CRM platform, navigate three screens, and interpret the data.
  • Scenario B: That same insight surfaces directly in the Salesforce channel in Slack where the account team is already debating strategy. It appears in context. In real-time.

In Scenario B, the friction dissolves.

This is the vision behind the Agentic OS. It’s about configuring your collaboration platform not just as a place to talk, but as intelligence infrastructure. At Salesforce, we have become “Customer Zero” for this approach. Our Engineering Agent has handled 18,000 support interactions; our Sales Agent supports 25,000 sellers. The results are significant not because the agents are smarter, but because they live where our people work.

Ready to map out your AI strategy for the year ahead?

As you finalize your strategy for the coming year, I challenge you to look at your organization through the lens of these five friction points.

Where is the flow breaking down? Are your investments working for you, or are they creating new silos?

To start bridging the intelligence gap, download ‘Building for the AI Era: A Playbook for Scaling Business Intelligence which includes a 90-minute hands-on diagnostic workbook  to pinpoint exactly where your organization’s intelligence flow is breaking down.

The gap between AI investment and business impact isn’t a mystery. It’s a proximity problem. And the good news? It is entirely solvable.

Onward.

이 포스트가 유용했나요?

0/600

훌륭해요!

피드백을 주셔서 감사합니다.

알겠습니다!

피드백을 주셔서 감사합니다.

죄송합니다. 문제가 발생했습니다. 나중에 다시 시도해주세요.

계속 읽기

새 소식

Slack에서 에이전트 중심의 워크스페이스 구축하기

Slackbot: 에이전트 에코시스템을 위한 대화형 단일 인터페이스

새 소식

대화하듯 고객 데이터를 관리하도록 새롭게 구성된 Slack의 CRM

Slack에서 신뢰할 수 있는 엔터프라이즈 데이터를 최대한 활용하여 거래를 성사하고, 사례를 해결하고, Agentforce로 빠르게 성장할 수 있도록 지원하세요.

새 소식

Salesforce 채널: 팀워크의 미래, 이제 Salesforce와 Slack에서 만나보세요

정보 단절을 없애고 모든 팀을 연결하며 모든 대화의 실시간 고객 데이터를 통해 더 빠르게 움직이세요.

생산성

직원 생산성에 혁신을 가져올 AI 에이전트

Slack의 최신 보고서에서는 AI 에이전트가 업무 환경을 변화시키는 방법과 기업이 계속 앞서 나가려면 디지털 노동력 플랫폼을 도입해야 하는 이유를 알아볼 수 있습니다.