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Interactive experience sections

  • Why AI Feels Worse
  • The Execution Gap
  • Friction Points
  • Where AI Stalls
  • The Path Forward
  • Read More
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Interactive experience sections

  • Why AI Feels Worse
  • The Execution Gap
  • Friction Points
  • Where AI Stalls
  • The Path Forward
  • Read More

Why Throwing Money at AI is Making It Worse

Everyone is doing AI. Almost nobody has it working.

woman smiling with a tablet in her hand

The gap between the two has very little to do with how much you have spent, how big your team is, or how early you started.

The organizations pulling ahead are not the ones with the biggest AI budgets. They are the ones asking a different question before they buy anything.

  • 0%51%

    Describe their organization as a slow AI adopter.

  • 0%18%

    Have AI use cases actively in operation.

  • 0%57%

    Are stressed about finding the right solution.

Nearly half of all organizations call AI a top priority. So why does the gap keep growing?

Fewer than 1 in 5 have anything running in production. That distance between intent and execution has a specific shape, and it shows up in the same places across organizations of every size and industry.

The question every CX and IT leader is actually asking right now

AI adoption used to be a question of whether. Most leaders settled that a long time ago. Now the research is catching up to what practitioners already sense: the gap between priority and production is longer and more specific than most expected. And it has very little to do with tools.


“The journey between idea and execution is a lot longer than most organizations thought. This isn’t about hype anymore. It’s about making hard choices with incomplete information.”link to this section

Joel Neeb, Chief Transformation and Business Operations Officer, 8x8

Four friction points that keep showing up, regardless of budget or timeline

Our research surfaces the same blockers across organizations of every size and sector. Recognizing which ones are yours is the first step to getting unstuck.

Unclear use cases

lack of data readiness

Integration complexity

Security and governance concerns

Three places where AI stalls. Most organizations are hitting more than one.

Most organizations assume their blockers are unique to them. The data says otherwise. There are three places where AI stalls. They compound each other, and the organizations that have made it through understand exactly how. The report names them and shows what it takes to move past each one.

What 84% of organizations are worried about, and what the worry is really pointing to

Data security tops the list. But the organizations stuck in our research are working through something harder than a compliance checklist. They are figuring out how AI and people are supposed to function together responsibly, and finding that most governance frameworks were not built to answer that question yet. Only 31% of organizations have formal AI policies in place.


“When AI is tied to real goals, ROI becomes clear quickly. When it’s not? That’s like handing someone a hammer and expecting it to work like a Swiss Army Knife.”link to this section

Hunter Middleton, Chief Product Officer, 8x8

Having a strategy team and a budget is a start. Here is what comes after.

31% of organizations have a dedicated AI strategy team. Half of those teams still describe implementation as slow. A strategy and a budget create the conditions for progress. The report explains what actually separates the organizations that have crossed from pilot to production from the ones still waiting.

Where you are starting from changes everything about where you go next

A third of organizations believe their use of AI could be more effective. They have big ambitions. When we asked them where the gaps were, the answers were many and varied.link to this section

Our research maps three distinct levels of AI sophistication: assistive, augmentative, and agentic. The path forward looks different depending on which stage you are actually at. Most organizations think they are further along than the data suggests. Knowing your real starting point is what makes the next investment land.link to this section

“The most successful organizations don’t start with the technology — they start with asking: What specific CX experience are we trying to improve?”link to this section

Bruno Bertini, Chief Marketing Officer, 8x8

When the foundation is right, the results are hard to argue with

Organizations that have integrated their data and defined their outcomes before deploying see a 26% increase in customer satisfaction and a 23% boost in agent efficiency. Only 28% of companies currently make that data widely available. Closing that gap is where the real work starts.

Conquer Complexity With the 8x8 Platform for CX

The organizations getting AI to work are building on stronger foundations: connected data, clear outcomes, and a platform designed to support both. The full report shows what that foundation looks like and what it takes to build it.

Learn More
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Stay in the Loop. See What’s New.

You're Paying for the Wrong Thing

Stop measuring AI outputs. Focus on the total customer journey and relationship health to achieve true ROI and real business outcomes.

The Cost of Conversations That Don't Count

Why the real bill is bigger than the invoice, and what to do before it grows.

Customer Stories

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