The adoption agency for ServiceNow AI
The AI you bought
only pays off
when it's used
Your ServiceNow investment already includes powerful AI. We help turn it into operating performance — with the foundations, governance, and adoption metrics to prove progress over time.
The Mandate
AI is now a mandate. Operationalizing it is the hard part
Your ServiceNow roadmap now includes AI expectations from the board, the business, and your employees. But the value depends on more than turning features on: knowledge quality, workflow design, governance, measurement, and teams ready to work in new ways. Most organizations are in the same place — the mandate is clear, but the operating foundations are still catching up:
94%
of organizations with deployed AI report no significant value from it.
McKinsey · State of AI, 2026
~40%
of companies that measured AI outcomes landed at 0–10% cost reduction — while 37% had targeted 11–20%.
Bain & Company · 951 global companies
The opportunity is real. The operating model has to catch up
How it works
Four phases Then ninety days of proof
Everything happens inside your own ServiceNow instance, on capabilities you already own. Success criteria are set in week one — the engagement is done when adoption is measurable, sustained, and improving — not simply when the feature goes live.
01 · 1 week
Measure readiness
We assess your readiness against the specific workflow being deployed — and set the success criteria the whole engagement answers to.
02 · 1–3 weeks
Fix the foundations
Our diagnostic engine finds and fixes what breaks AI — stale, contradictory, human-only knowledge — while we set up governance and bring your team along. In scope, not your prerequisite.
03 · 2–6 weeks
Deploy the capability
The AI in your tier, configured for the workflow it serves and connected to the data it needs — on your instance, not beside it.
04 · 1–2 weeks
Go live, supported
Launch with your team supported through the first real workload — then the proof window begins.
McKinsey · State of AI, 2026
90 days of adoption tracking — so leaders can see which interventions are working, where friction remains, and how progress is improving over time.
Ecosystem Fit
One adoption model Applied across the ServiceNow AI stack
ServiceNow AI value rarely comes from a single feature in isolation. OnBaseAI helps teams connect the right capability to the right workflow, prepare the operating foundations around it, and measure whether the intended audience is actually changing behavior over time.
AI Roadmap & Portfolio
Prioritize what is worth adopting next
We help leaders move from AI inventory to AI sequencing: which capabilities are ready, which foundations are blocking value, and which interventions will create the strongest near-term proof.
AI Control Tower
Governance that leaders can use
We help translate AI governance into an operating rhythm: ownership, risk visibility, intervention tracking, and executive reporting that shows where AI is creating value and where controls or enablement are needed.
Knowledge & CMDB
The foundations AI depends on
We diagnose stale, conflicting, missing, or human-only knowledge and the operational data gaps that limit AI performance — prioritizing remediation by adoption impact, not generic cleanup volume.
Now Assist
From feature launch to daily
workflow
We identify the best-fit use cases, clean up the knowledge and workflow inputs that affect answer quality, enable agents and employees, and track adoption against the work Now Assist is meant to improve.
Otto / EmployeeWorks
Employee adoption for AI-powered work
We help teams apply Otto and EmployeeWorks to the moments where employees need faster answers, clearer guidance, and less swivel-chair work — then align knowledge, workflows, enablement, and measurement so the experience becomes part of how work gets done.
Agentic AI / AI Agents
Prepare workflows for autonomous action
We help teams identify where AI agents can safely move from recommendation to action — clarifying ownership, guardrails, exception paths, and adoption measures before autonomy becomes part of the operating model.
Engagements
Choose the right starting point Keep the same adoption discipline
Every engagement is fixed fee, fixed timeline, single SOW — sized around the workflow, audience, and integrations required to create visible adoption inside a fiscal quarter.
small
4 weeks
One capability, one workflow
Best for teams that want a focused, low-friction start: one use case, one accountable owner, one adoption plan, and clear before/after measures.
- Readiness baseline and success criteria
- Knowledge and workflow gap remediation
- Launch enablement for the primary user group
Medium
8 weeks
A capability across workflows
Best when the same capability needs to work across related workflows, groups, or service channels — with deeper readiness work, stakeholder enablement, and governance built in.
- Multi-workflow adoption and intervention plan
- Stakeholder mapping and manager enablement
- Governance rhythm for continuous improvement
Large
12 weeks
Cross-department, custom integration
Best for cross-functional programs where adoption depends on integrations, multiple teams, or more complex change management. We define the path, dependencies, and success measures up front.
- Cross-department operating model and RACI
- Integration readiness across ServiceNow and adjacent systems
- Executive reporting cadence for adoption progress
Why trust us
Built for accountable adoption Structured to reduce delivery risk
Risk controls built in
Fixed price. Fixed timeline. Success criteria set before work begins — with a defined remediation path if adoption progress falls short of the agreed measures.
The team behind it
A founding team with a prior-career record deploying and operating enterprise AI at scale — combining product, adoption, governance, and enterprise change experience.
See it before you buy
A complete demonstration engagement walks every phase end to end — readiness diagnosed in days, a working capability in weeks, and adoption progress tracked across 90 days. Ask for the walkthrough
Frequently Asked Questions
What teams usually ask before starting
A few practical answers about scope, readiness, measurement, sponsorship, and what remains after the engagement.
A current ServiceNow environment and an owner for the workflow you want to improve. We verify entitlements before the SOW is signed, then assess knowledge, governance, workflow fit, stakeholder readiness, and measurement needs as part of the engagement.
We establish a baseline, define success criteria, and track progress over time across usage, workflow outcomes, knowledge improvements, stakeholder readiness, and intervention effectiveness. The goal is not a static report — it is a repeatable way to see what is improving and what still needs attention.
No. Knowledge quality is one foundation, but the deliverable is a deployed and adopted AI capability. The work can include workflow design, governance, stakeholder enablement, intervention planning, and adoption measurement — not just cleaner documents.
Your team keeps the deployed capability, the governance model, the adoption tracking approach, and a named steward to continue the operating rhythm. The engagement is designed to create internal ownership, not dependency.
We start with the capability tied to the workflow outcome you need — for example employee service, IT service, knowledge, virtual agent, workflow automation, or other AI-enabled ServiceNow experiences. The first step is confirming what you already own, what is ready to use, and what foundations need work before launch.
The model is designed to minimize lift. We need access to the right system context, workflow owners, and a small set of stakeholders for validation and enablement. OnBaseAI carries the diagnostic, remediation planning, adoption design, and measurement work so your team can stay focused on business operations.
That is exactly why readiness is part of the engagement. We identify the gaps that will limit adoption, prioritize the fixes that matter most for the target workflow, and create a practical operating rhythm so quality improves over time instead of becoming a one-time cleanup project.
The best sponsor is the leader accountable for the workflow outcome — often IT, employee experience, HR service delivery, customer service, or operations — paired with the ServiceNow platform owner. We help define the owner, stakeholder map, and success criteria during scoping.
THE FREE AI READINESS ASSESSMENT
Find out where you stand
Receive an executive-ready readiness profile of the AI in your ServiceNow environment — what's ready to deploy, what's blocked, and what's blocking it. No sales call required to see your results.
The adoption agency for ServiceNow AI. We help teams operationalize the capabilities they already own — with the foundations, governance, and adoption measurement to prove progress.
Get Started
Start with a free AI readiness assessment.
©2026, OnBaseAI Inc.