Artificial Intelligence (AI) has become a core driver of business transformation, helping companies improve efficiency, decision-making, and competitive advantage. For corporate leaders, AI is no longer optional, it is essential. However, many organizations struggle to measure the success of their AI initiatives effectively.
This article highlights five key performance indicators (KPIs) that senior executives should track to ensure AI delivers real business value. These KPIs provide a clear framework to evaluate AI projects from pilot to enterprise-wide deployment, helping leaders make informed decisions, manage risks, and maximize returns.
1. Time-to-Value (TTV)
What it is: The time from the start of an AI project to the point when it delivers measurable business results.
Why it matters: A shorter TTV builds confidence among stakeholders, secures ongoing funding, and maintains momentum. Long projects without clear results risk losing executive support.
How to measure:
● Days from project kickoff to first AI-driven automation or process improvement
● Time until measurable improvements in key metrics (e.g., invoice processing speed, customer service resolution)
Example: Hillogy targets pilots that deliver results within 30 to 90 days, enabling quick validation and scaling of AI solutions.
2. Process Error-Rate Reduction
What it is: The percentage decrease in errors after implementing AI automation and validation.
Why it matters: Reducing errors lowers costs, mitigates compliance risks, and protects company reputation. AI reduces manual mistakes and inconsistent decisions.
How to measure:
● Compare error rates before and after AI deployment in specific workflows (e.g., data entry, contract classification)
● Track the number of exceptions flagged for manual review
Example: A client reduced data entry errors from 30% to under 5% using OCR combined with AI validation.
3. Cost-per-Transaction (CPT)
What it is: The average cost to complete a single business transaction, before and after AI automation.
Why it matters: CPT reveals the true financial impact of AI, including labor, technology, rework, and hidden costs like compliance penalties or delays.
How to measure:
● Total process costs divided by the number of completed transactions
● Include labor hours, technology fees, rework costs, and indirect expenses
Example: A detailed CPT analysis can uncover hidden inefficiencies, guiding targeted AI investments for maximum cost savings.
4. User Adoption and Satisfaction (UAS)
What it is: The degree to which employees and customers accept and effectively use AI solutions.
Why it matters: High adoption and satisfaction are critical for AI’s long-term success. Without user trust and engagement, AI tools may fail to deliver expected benefits.
How to measure:
● User satisfaction surveys post-deployment
● System usage data: frequency, task completion, drop-off points
● Support ticket volume related to AI tools (declining volume indicates better usability)
Example: Hillogy supports adoption through tailored change management and training from project start, ensuring sustained engagement.
5. Scalability Score
What it is: A measure of how easily and cost-effectively an AI solution can be expanded across business units, regions, or use cases.
Why it matters: AI’s true value comes from broad adoption. Solutions that are hard or expensive to scale limit long-term ROI.
How to measure:
● Number of use cases enabled from a single pilot
● Average time and cost to scale to new areas
● Level of customization or retraining needed for each rollout
Example: An OCR AI solution scaled from vendor invoice processing to legal contracts and customer forms within 60 days with minimal retraining.
Ready to Track What Matters?
Tracking these five KPIs: Time-to-Value, Process Error-Rate Reduction, Cost-per-Transaction, User Adoption and Satisfaction, and Scalability Score provides senior leaders with a clear framework to measure AI’s business impact. These metrics help ensure accountability, optimize investments, and align AI initiatives with corporate goals.
Hillogy partners with enterprises to design, implement, and scale AI solutions that deliver measurable value. We invite senior executives to engage with us for an AI readiness assessment and pilot planning session. Together, we can turn AI from a technology experiment into a strategic business advantage.
Contact us today to start your AI transformation journey with confidence!
