Comprehensive AI Strategy
Archive clear roadmap for AI adoption
Discussing AI adoption requires a robust strategy. We must evaluate every aspect of the organizational structure to identify where AI can streamline existing processes and boost growth. A comprehensive AI strategy provides a clear roadmap for integrating the necessary components for a successful AI journey.
How to develop a strong AI strategy?
Here’s our approach to developing an AI strategy:
Identify Your Challenges
- Outcome: A Ranked List of Challenges Based on Potential Impact
Assess AI Solutions
Your AI expert will undertake the following:
- Build versus Buy : Determine whether to develop custom AI solutions or purchase from a provider. Your expert will guide this decision based on the nature of the challenge.
- Technology Selection : Identify the appropriate AI/ML models/solutions based on the build-versus-buy decision, assessing technology availability and the effort required to tackle each challenge.
- Data Set Availability : Identify if the data necessary for training and testing AI/ML models is available within the organization.
- Investment : Estimate the investment required based on the decided approach, chosen technology and data set availability.
- Outcome: The List of Challenges, Prioritized by AI Feasibility and Investment Needs
Set Goals and KPIs
With a feasibility-ranked list from your AI expert, conduct a baseline data analysis and market research to set realistic standards. Compare these against industry norms and competitors. Define clear goals and establish Key Performance Indicators (KPIs) that allow for consistent assessment of your AI solution’s effectiveness.
- Outcome: A list of challenges ranked by investment requirements and value proposition with specific and measurable outcomes
At the end of your strategy sessions, you will have a very clear idea to convert this list of challenges into actual projects. These projects may be added to your roadmap for detailed planning and execution.
