(photo by Martin Lissmyr)
I have seen numerous presentations on the successful implementation of artificial intelligence (AI) and how the business or organization received a significant benefit. The value is normally expressed in terms of increased revenue or bottom line cost savings. Calculating the value of a business benefit is always easier to determine than the value of a human benefit, such as reducing stress or improving communications. The justification for implementing AI tools is the business case. The initiation of a new AI project should include an analysis of costs compared to the value received by completing the project.
The business case for implementing AI tools for project processes or within a PMO looks straightforward but has some challenges. In general, any tool that improves the project schedule or reduces project cost will provide value to an organization. Calculating the cost for implementation will require more intense review. Most organizations will face two serious implementation issues that need to be considered when calculating the deployment cost: data and single focus.
Experience in AI deployment projects shows that 60% to 80% of the effort will be spent finding and cleaning data (Reference my previous blog). The business case needs to include this cost of data cleansing. Typical data issues include a one- time cost to clean existing data and then an ongoing cost to maintain clean data. It is possible that an organization will require a data architect to help define data standards and ongoing strategies to properly maintain the data.
Implementing an AI tool to perform a single activity in project management is problematic because projects are integrated across several knowledge areas. An AI tool that finds a way to reduce the schedule by 2 weeks also needs to consider the side effects on risk, quality, and other areas across the project. The first AI tools in project management will have a simple, single purpose so any unforeseen negative results and remediation must be considered for the business case.
For project managers, creating a good business case is a significant achievement. It ‘sells’ the project, motivates the team and provides a clear objective. A well constructed business case normally considers all costs and for an AI deployment some of those costs are less obvious.