K
Kathleen Martin
Guest
On-demand, scalable, and economic cloud storage and computation has enabled the efficient processing of huge data sets to draw critical insights using Artificial Intelligence (AI). Launching multiple AI initiatives is par for the course today. After all, some will not succeed. But how do you choose where to devote your resources?
"With so many options, the most difficult part can be deciding where to invest first."
“It is near impossible to name an industry that isn’t implementing AI solutions nowadays given its breadth of applications,” says Jim Radzicki, CTO of Telus International. “But, with so many options, the most difficult part can be deciding where to invest first.” There are so many areas where AI can be applied and demand for intelligent capabilities in the enterprise continues to grow, says Peter A. High, author of Getting to Nimble: How to Transform your Company into a Digital Leader and president of the technology and business advisory firm Metis Strategy.
AI project prioritization is critical. “It ensures that AI is connected to the business’ agenda and priorities,” says Goutham Belliappa, vice president of AI engineering at Capgemini North America. “Through tight governance and monitoring, companies can identify which projects are performing better than others and adjust the prioritization and resources accordingly in an agile manner.”
AI project prioritization: 6 strategies
Prioritization provides a framework wherein leaders can review all the options and available resources to determine the order in which AI projects will be implemented. “This type of big picture approach helps businesses achieve long-term success by taking all factors into consideration and making thoughtful decisions as opposed to executing them on an ad hoc basis,” Radzicki says. “Understanding the potential missed opportunities foregone by choosing one project implementation over another allows for better decision-making.”
Consider these six tips for AI project prioritization:
1. Focus on business significance
Buy-in from the board and C-suite is paramount. “If projects are tied to high-priority, tangible business outcomes, then they are more likely to succeed,” says Belliappa. Tie all AI initiatives into the business strategy of the enterprise and divisions of the company.
This “helps ensure that you do not develop AI for AI’s sake,” says High, “which can be another pathway to problems.”
Continue reading: https://enterprisersproject.com/article/2021/8/how-prioritize-artificial-intelligence-ai-projects-6-tips
"With so many options, the most difficult part can be deciding where to invest first."
“It is near impossible to name an industry that isn’t implementing AI solutions nowadays given its breadth of applications,” says Jim Radzicki, CTO of Telus International. “But, with so many options, the most difficult part can be deciding where to invest first.” There are so many areas where AI can be applied and demand for intelligent capabilities in the enterprise continues to grow, says Peter A. High, author of Getting to Nimble: How to Transform your Company into a Digital Leader and president of the technology and business advisory firm Metis Strategy.
AI project prioritization is critical. “It ensures that AI is connected to the business’ agenda and priorities,” says Goutham Belliappa, vice president of AI engineering at Capgemini North America. “Through tight governance and monitoring, companies can identify which projects are performing better than others and adjust the prioritization and resources accordingly in an agile manner.”
AI project prioritization: 6 strategies
Prioritization provides a framework wherein leaders can review all the options and available resources to determine the order in which AI projects will be implemented. “This type of big picture approach helps businesses achieve long-term success by taking all factors into consideration and making thoughtful decisions as opposed to executing them on an ad hoc basis,” Radzicki says. “Understanding the potential missed opportunities foregone by choosing one project implementation over another allows for better decision-making.”
Consider these six tips for AI project prioritization:
1. Focus on business significance
Buy-in from the board and C-suite is paramount. “If projects are tied to high-priority, tangible business outcomes, then they are more likely to succeed,” says Belliappa. Tie all AI initiatives into the business strategy of the enterprise and divisions of the company.
This “helps ensure that you do not develop AI for AI’s sake,” says High, “which can be another pathway to problems.”
Continue reading: https://enterprisersproject.com/article/2021/8/how-prioritize-artificial-intelligence-ai-projects-6-tips
