Start simple with a structured approach

Whether working with an internal team or a consulting agency like ours, we recommend these steps:

AI Introduction and Its Potential

Start the session with what AI is, its benefits, and examples of successful AI implementations. This helps create a shared understanding of AI and serves to inspire the team on the possibilities.

Idea Generation

Discuss the problems that are inhibiting growth or efficiency in the business and brainstorm potential AI solutions to these problems. We like to focus on the customer lifecycle because of the direct tie to outcomes like revenue, customer loyalty, and customer service.

Prioritization

Next, stack rank project ideas based on the potential costs and expected ROI of each viable AI idea. Decide on one or a few AI initiatives to start. Keep the scope SMART – specific, measurable, achievable, relevant, and time-bound.

Assessment

Now it’s time to assess whether the AI ideas are technically possible with your current or attainable resources. This includes whether you have the necessary data to train AI models and consider data privacy and ethical implications.

Prototype Development

Create a step-by-step plan for the chosen AI project, including timelines, milestones, and responsibilities. Determine the resources you will need like budget, personnel, and technology for each stage of the project. Identify any skill gaps in your team and how to fill them with training, hiring, or with a partner.

Post-Workshop Actions

Document the workshop outcomes and communicate the plan. Start prototype planning by setting clear, achievable goals. Don’t overlook the importance of change management: AI projects often require changes in workflow, roles, and decision-making processes.

Wrap Up

Explore the possibilities by visiting Magnetiz, our AI consulting service that works alongside your team to make the business run better. Ready to start? Schedule a strategy call

You can explore our newsletter archive here.