The ROI of enterprise AI is the measurable business value its agents and copilots create, calculated as the time they save multiplied by the cost of that time. Nebuly measures it by analyzing the actual conversations between users and AI, estimating how much time each completed task would have taken a person, and converting that time into money. Instead of showing how much AI is used, it shows how much value AI creates.
Most organizations measure AI with adoption metrics: active users, conversations, or requests handled. Those numbers show that employees use AI, not that it produces business value.
Without a way to quantify value, it is hard to justify AI investments and renewals, prioritize initiatives, or compare performance across teams. AI ROI closes that gap by measuring how much value AI creates, not how often it is used.
Nebuly analyzes successful conversations and estimates how much work the AI completed instead of a person. For every interaction it determines three things: whether the task met your success criteria and should count, how much time it saved compared with doing the work manually, and the monetary value of that time based on your hourly cost.
Only conversations that meet your success criteria contribute to the calculation, so the number reflects real value rather than raw activity.
Nebuly uses a proprietary model to estimate how long each type of action takes. Until the model calibrates to your workspace, it applies sensible defaults of 15 minutes per action and $75 per hour, both adjustable at any time in ROI settings. You define your own success criteria and can exclude unsuccessful conversations, so only genuine value is counted.
What the ROI report shows
The AI ROI report updates automatically as new conversations are analyzed. It surfaces:
Total value saved — the net monetary value generated by AI in the period
Total hours saved — working hours returned to your teams
Hours saved per user and per task
Tasks completed — successful AI-assisted tasks that met your success criteria
Task completion rate — the share of conversations that succeeded
Value saved per task — average net value per successful task
ROI trend — how value generated evolves over time
ROI by action — value broken down by user action, so you can see which use cases drive the most return
ROI does not mean the same thing everywhere. Internal copilots prove their value through time saved and AI proficiency, where retention or upsell would not apply. Customer-facing agents prove theirs through revenue signals such as retention and expansion, where time saved is the wrong lens. Nebuly measures both.
What is enterprise AI ROI?
Enterprise AI ROI is the measurable business value that AI agents and copilots create, expressed as the time they save multiplied by the cost of that time. It answers whether your AI is delivering value, not just whether it is being used.
How is time saved calculated?
Nebuly analyzes each successful conversation and estimates how long the same task would have taken a person to complete manually. That estimate comes from a proprietary model that learns the time each type of action takes in your workspace. Time saved is then multiplied by your net hourly cost to produce a monetary value.
What are the default ROI assumptions?
Until the model calibrates to your data, Nebuly uses defaults of 15 minutes per action and $75 per hour. Both are adjustable in ROI settings, and you can fine-tune the time estimates for individual actions and set which conversations count as successful.
How is AI ROI different from AI adoption?
Adoption measures whether people use AI, through metrics like active users and conversation volume. ROI measures the value that use creates. High adoption with low value is common, which is why adoption alone cannot justify AI investment.
Can you measure ROI for customer-facing AI?
Yes. For customer-facing agents, value shows up as revenue signals such as retention and expansion rather than time saved. Nebuly measures both internal and customer-facing AI.
