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Define Your AI Strategy
Bring an AI strategy to your company. Identify a vision, establish AI governance, define AI use cases, and develop your AI backlog.
These steps provide the basic framework for developing your organization’s AI strategy. For a more detailed and example-driven explanation of building an AI strategy, review the AI Strategy module on Trailhead.
Develop Your Company’s Vision for AI
An AI vision statement articulates overarching goals that help focus your company’s efforts. This vision statement can define broad business outcomes, such as improving sales productivity or reducing the open case time by a target percentage.
It’s helpful to identify key stakeholders across your company who can help you refine these goals. These individuals aren’t always directly involved in the specific projects, but they’re invested in AI success overall. Key stakeholder roles can include:
- Executive leadership
- Business department leads
- Technical teams such as IT, Data Science, or Business Intelligence
- Legal and Security
Stakeholders can help your business identify cross-team goals and innovate ways to expand upon project success, such as modifying a successful AI project to work with a new business unit. Each time you build upon the success of a previous project, you increase your organization’s ability and capacity to implement AI solutions successfully.
Establish AI Governance
A strong AI governance plan includes building a set of policies, processes, and best practices so that everyone uses and develops AI in a responsible and scalable manner. Collectively, these policies and guidelines align with your company’s vision and applies to the inventory of current AI solutions used in your business. In addition, AI governance helps your team identify potential risks, address them with mitigation strategies, and ultimately guide your business toward its stated goals.
Identify AI Use Cases
Now that your team has solidified the vision and governance, your team can define AI use cases and prioritize them according to business impact and value. Identify use cases through crowdsourcing, by conducting business process analyses, and by reviewing market trends.
After you’ve identified a list of use cases, analyze them based on potential business value and ease of implementation. As you prioritize your projects, it’s valuable to identify projects that build momentum. To multiply impact, consider projects that use the same dataset or that can be easily replicated into additional business units or geolocations.
After you’ve identified your first AI project, add the other projects into a backlog for future evaluation.
