The AI conversation is everywhere but what do knowledge management leaders really think about AI adoption, readiness, and results? 

During our recent KMWorld webinar, “Fact, Failure, or Fantasy: Navigating How to Win with AI in Knowledge Management”, we asked the audience to weigh in on seven bold statements about AI in the enterprise. Hundreds of participants, from IT leaders to customer experience pros, responded in real time. 

The results? A candid look at what’s working, what’s not, and where AI + KM is headed next.

Here’s quick look at a few of the things we learned from Paychex during the session. Head over to our session wrap up blog for a deeper dive into the whole agenda. 

Poll 1

“We started with a homegrown AI initiative, trying to fast-track success across the company.” 

Poll results: 

Homegrown AI: Ambitious, but Often Unrealistic 

• 44% of leaders say internal AI builds are fantasy or failure
• 80% of AI pilots stall before scaling
• Without infrastructure and expertise, homegrown AI can’t deliver enterprise results

Nearly half of respondents admitted that building AI in-house is more of a fantasy than a fast-track to success. Paychex, our guest speaker, learned this lesson early, as they started with a homegrown generative AI project before pivoting to an enterprise-ready platform. 

Insight: Scaling AI isn’t just about talent or tech. Without deep expertise and the right infrastructure, homegrown projects often stall before they deliver value. 

The AI profit drought continues: 95% of organizations see no measurable return on AI efforts, despite massive investment.

The New Yorker

Poll 2

“Only the IT and product teams were involved at first. Business stakeholders came in later.”

Poll results: 

IT Can’t Go It Alone 

• Only 44% said IT-only pilots worked
• Adoption accelerates when business users are included
• Bring frontline users in early. Context = better answers

This one was almost evenly split, but here’s the truth: AI success takes a village. While IT and product teams often lead early pilots, broader business involvement drives adoption and accuracy. 

Lesson: Bring frontline users into the conversation early. Their real-world context helps shape AI into a tool that delivers meaningful answers faster. 

Poll 3 & 4

“The AI use case was practical, so adoption would come easy.” and “AI would just fit naturally into how people already worked.” 

Poll results: 

Adoption Isn’t Plug-and-Play 

• Over 90% say AI adoption isn’t easy
• Change management & training = non-negotiable
• AI is a journey, not a switch

AI won’t just fit – you have to make it fit

• 77% say AI doesn’t naturally integrate into workflows
• Training and workflow alignment drive real usage

These two polls tell a clear story: AI adoption takes effort. 

Employees must unlearn old habits like keyword search and learn how to interact with AI-powered systems naturally. Training and change management aren’t optional; they’re the foundation of successful implementation. 

Takeaway: AI isn’t magic. It’s a partnership between technology, people, and process. 

Poll 5

“There was real urgency so we wouldn’t lose our competitive edge.” 

Poll results: 

The AI Race is On, and the Urgency is Real

• 83% feel real urgency to adopt AI
• 50%+ of enterprises report AI-driven efficiency gains
• The question isn’t if you’ll adopt AI. It’s how fast and how well.

A staggering 82% of participants said urgency is real. Organizations know they can’t afford to lag behind as AI reshapes customer support, operations, and employee productivity. 

Opportunity: Urgency is a powerful driver, but without a strategic roadmap, speed can lead to false starts and failed pilots. 

Poll 6

“AI success depends more on managing people than managing technology.” 

Poll results: 

People > Technology, AI Success = People First

• 92% agree people drive success more than tech
• Training, trust and change leadership make adoption stick
• AI thrives when humans are ready

If there’s one insight everyone agrees on, it’s this: AI success depends more on people than on technology. 

The best platforms can’t deliver results if your people don’t trust, understand, or adopt them. Change management, governance, and clear communication make the difference between stalled pilots and scaled wins. 

Poll 7

“Now that we’ve scaled AI with knowledge management, it’s finally delivering consistent wins for the business.” 

Poll results: 

Consistent Wins Take Maturity

• Only 50% say AI delivers consistent wins today
• Companies with mature KM see 3x faster ROI
• Invest in KM first, scale AI second

Here, the audience was split. Half say they’re already seeing consistent wins, while the other half are still in early adoption phases. 

Why the split? Organizations with mature KM frameworks, like Paychex with its 60,000+ articles and 30,000 daily views, are the ones seeing faster, measurable ROI from their AI investments. 

The Big Picture 

These seven polls paint a clear picture of where the industry is today: 

• Urgency is driving AI adoption, but speed without strategy creates risk. 

• Success comes from people-first adoption, backed by training, governance, and a strong KM foundation. 

• Enterprises with mature, integrated knowledge management are the ones turning AI from hype into real, scalable results. 

Next Steps 

Want to see how your organization compares? Download our latest report, The Knowledge Activation Gap, created with Metric Sherpa, and get your AI Readiness Scorecard to benchmark your maturity. 

Get the Report

Want to read more? 

We have a full wrap up ready to go. Read KM Webinar Recap: How Paychex Mastered AI in Knowledge Management here.  

Read the Blog