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Plan and Implement Your AI Project
Now that you’ve identified your first AI project, it’s time to start preparing for a successful project launch.
These steps provide the basic framework for planning an AI project. For a more detailed and example-driven explanation of the process, review the AI + Data: Project Planning module on Trailhead.
Identify Project Stakeholders and Goals
Project stakeholders are people who have an interest, influence, or impact on the project. Keep in mind that your project stakeholders are typically different from strategic, company-wide stakeholders for AI, although there might be a little overlap. Project stakeholders are dedicated to the implementation of that specific AI project, while strategic stakeholders manage the company-wide AI strategy.
Additionally, define the project success metrics. Aim to define a SMART goal: specific, measurable, achievable, relevant, and time-bound. For example, the objective for a customer service project might be to reduce the average case handling time by 20%, and the objective for a sales project might be to increase upsell conversion rates by 10%.
Consider the Technical Requirements
When you’re getting started on an AI initiative, it’s essential to assess the technical requirements of the project. Here are some of the questions to ask.
- What type of AI does the project require? Predictive, generative, or both?
- Does this solution need to integrate with other systems?
- Are there any out-of-the-box solutions you can use and customize, or do you need to build it yourself?
- If you choose to build it yourself, does your organization have the right in-house skills?
- What models, programming languages, frameworks, libraries, and tools will you use?
- How will you balance the trade-offs between accuracy and speed, complexity and simplicity, and innovation and cost?
If you’re building your project in Salesforce, you must have Data 360 and Einstein Generative AI enabled in your org.
Identify the AI Solution
Identify which AI features can help move your project toward its goals. Then review the feature documentation to see whether the solution needs some customization in order to complete your goals. Examples of customization include:
- Updating prompt templates to include specific data fields
- Updating a flow to link into your Salesforce org’s processes
Use your best effort in this exercise, but keep in mind that, to achieve the business results you want, many AI solutions require some iterative refinement after the implementation. Include extra time for these refinements in the testing phase of development.
After you have your expected implementation steps, build out the project timeline. Include time for testing, and designate a pilot stage.
