To derive tangible business benefits from AI projects, data and analytics leaders must implement five best practices. Gartner analyst Leinar Ramos shares more SiliconANGLE. GartnerIT GartnerSYM
for organizations, but AI teams often find it challenging to realize and communicate these benefits. In fact, Gartner research has found that difficulty measuring AI value and a lack of understanding around AI benefits and uses are top barriers to its implementation.
Benefits do not happen by themselves. They need to be actively managed and monitored before, during and after AI model deployment. Thus, to derive tangible business benefits from AI projects,Before they begin, AI projects must obtain funding from the business. To sell the value of AI initiatives, data and analytics leaders must build a value story. Value stories essential to secure financing, drive adoption and create momentum for AI projects to scale.
The business KPI does not necessarily need to be financial. Solely focusing on financial metrics can make organizations miss critical investments in important projects that have longer-term, but strategic, impacts. Indirect metrics that can influence customer success, cost efficiency and business growth can also be impactful.Capturing AI benefits will not happen automatically.
However, A/B tests are not always possible or economically feasible. Many organizations that have been successful with AI have used attribution models — such as first-touch/last-touch attribution or latency models — to assign credit to actions taken because of the AI project.
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