Successful AI Commands Attentive arrangement
Organizations are trying to determine how to use the power of AI to benefit their businesses, many are still missing the foundational planning necessary to develop, deploy, and maintain successful AI programs. To ensure your AI initiative meets your business needs, build a good foundation that establishes clear goals and sets up a solid plan.
Construct Your AI substructure
Elucidate AI ?
Bluezeal AI recently led a workshop in which participants were asked what AI meant to them. We heard as many definitions of AI as there were people in the workshop. Several viewed AI as robotics, some viewed AI as math and some viewed it as science.
Meanings of AI, it is essential to establish how AI is defined at your organization. Document it and share it with all employees to give everyone a common understanding when they talk about AI and the organization’s AI initiatives and goals.
Why Use AI?
Hopefully your organization is not deploying AI just because it’s trendy. To have a successful AI program, you must determine how you expect AI to affect your business. I find that many organizations cannot articulate what they want to do with AI, which means they can’t explain the value that it can bring to them or their customers.
“Why AI?” is to identify how AI analytics can help reduce a pain point for your business and/or customers. Then you can align this goal with a strategic corporate initiative to provide a road map for AI.
This is the most critical question in the planning process. The last foundation block is clearly defining the business value expected from AI. Document the business value so leaders can easily determine the success or failure of the AI initiatives.
In addition, quantifying the expected return on investment will help justify the project. From the example above, Rogers’ Communication realized a 53 percent reduction in customer complaints, which qualifies and quantifies that their AI program was successful.
Create a Strategy
Once you’ve established your AI foundation, it’s time to move on to developing your data strategy for AI. This is not the same as identifying how to generate data. AI initiatives rarely suffer from too little data. Rather, organizations have trouble accessing and making sense of their data. A data strategy for AI solves that problem by providing a document that outlines needed data, access policies, the condition the data should be in, and the timeline for the needed data.
Understanding how the data is going to be used is imperative to ensure the correct data is wrangled, cleansed, and aligned to support the needs of AI. Your data strategy must establish, manage, and communicate to end users your policies, procedures, and mechanisms for effective data usage. Include a plan for storing the data so people across the organization can easily and quickly access what they need and, at the same time, clearly address the security around sensitive data, including access rights and how data will be protected.
Because data is a key element of AI, a good strategy built upon a solid foundation will ensure that the data for AI is properly stored, packaged, integrated, and governed. Having clear goals and success metrics for AI supported by reliable, trusted, and well-curated data will ensure that your AI projects are effective and meet your organization’s goals.