Digital business leaders must overcome the challenge of identifying and quantifying the benefits offered by AI projects to ensure a maximum return on investment.
Determining the benefits for artificial intelligence (AI) projects is difficult and confusing, but increasingly important. By 2024, 50% of AI investments will be quantified and linked to specific key performance indicators to measure return on investment. Success in AI depends on considering both its tangible and intangible benefits and determining how to meaningfully quantify them.
The following three benefits of AI projects and how they are measured are largely consistent with the top sources of business value for AI through 2030: cost reduction and customer experience.
- Risk: Measurements include risk reduction, mitigation, deduction and a range of other ways to leverage risk information.
- Speed: Measurements include process, call answer, worker, operational efficiency, accuracy, customer satisfaction and response time.
- Sales: Measurements include churn, revenue, leads, abandons, web traffic, orders, user experience and interactions.
While AI investments that reduce risk are clearly valuable, they are hard to quantify. When defining benefits, leaders should ensure a clear link between each benefit and the relevant business KPIs. A critical element in understanding benefits is defining how they will be measured. KPIs need to be defined before the AI project is deployed (as a baseline) and again after project completion to determine the resulting benefit compared to the baseline.
Identify the sources and types of benefits for each AI project by classifying the best methods for measuring success, noting that many projects have multiple benefits. This then enables more-effective project prioritization and justification.
Bern Elliot is a Vice President and Distinguished Analyst with Gartner Research.