AI Adoption - Where are you now?

[Khanna Ji]

Hi Everyone,

As AI capabilities continue to evolve rapidly across the ServiceNow platform, I’m interested in understanding where different organizations, customers, and partners currently stand in their AI adoption journey.

Many of us are navigating similar challenges—readiness, data quality, migration prerequisites, technical capacity, budget cycles, and internal alignment. It would be helpful to learn how others are approaching AI adoption in real projects.

Where does your organization stand today? Are you:

1. Exploring AI – reviewing use cases, assessing feasibility, or evaluating Now Assist capabilities
2. Preparing foundations – migrating to Flow Designer, upgrading workspaces, or cleaning data
3. Running pilots – trying out summarization, classification, recommendations, or AI agents
4. Rolling out AI at scale – enterprise-wide enablement, governance, and measurable outcomes
5. Still forming a strategy – need clarity on priorities, ROI, or resource availability
6. Partner-driven – relying on implementation partners for enablement and rollout
7. Hybrid model – partners handle legacy modernization while internal teams focus on AI

It would be great to hear:

• How you’re prioritizing AI relative to other mandatory migrations
• Any blockers slowing down AI adoption
• What’s working well and what isn’t
• Whether your approach differs for small vs. large teams
• How partners are supporting your AI roadmap (if applicable)

Your insights could help others benchmark their readiness and refine their strategy.

Looking forward to the discussion! Are there separate spaces or blots or videos where customers demonstratee their ServiceNow AI Adoption strategy, execution and roadmap?

[srikanthmadabhu]

Great question.

Yes — there are several places where customers and partners actively share their ServiceNow AI adoption strategies, roadmaps, and lessons learned:

• ServiceNow Community – Many customers publish blogs outlining their Now Assist rollout, governance models, and migration journeys.

• Knowledge Conference Sessions (K-Sessions) – Real customer case studies are often presented with architecture diagrams, adoption timelines, and measurable ROI.

• ServiceNow YouTube Channel & Webinars – Recorded customer stories, especially around Now Assist, AI Agents, and Predictive Intelligence.

• Partner-Led Webinars – Implementation partners frequently share anonymized transformation case studies.

• Customer Success Stories on servicenow.com – Industry-specific AI transformation examples.

In addition, some organizations are beginning to publish structured AI roadmaps on LinkedIn and Medium — especially around governance, data readiness, and scaling AI responsibly.

If you're benchmarking AI maturity, I’d recommend reviewing Knowledge session recordings first — they usually provide the most transparent execution details.

[Khanna Ji]

Stop spamming man - I am not looking for imaginary answers from AI

[srikanthmadabhu]

Thank you 🙂

[Silverbogan]

It’s interesting to see how AI adoption is evolving across organizations — many teams seem to be moving beyond early experimentation to actually embedding AI into workflows and processes. With capabilities like Now Assist and AI Agents now available, it feels like the focus is shifting from “learning what AI can do” to scaling and governing AI responsibly so it delivers real value rather than just hype. I’m curious how others are balancing security, governance, and practical use cases as they scale adoption.