AI Strategy & Consulting: AI Professional Services

 By analyzing your company's data sources for quality, volume, and accessibility, while also evaluating if your current IT infrastructure can support demanding AI computations and storage needs. Its also important to assess the existing AI/data science skills within your teams (like the Marketing, Engineering, and Dev teams you've interacted with) to pinpoint expertise gaps and training requirements needed for successful AI implementation.

Our teams will work together to explore potential ways AI could specifically help different parts of your business, like streamlining tasks for the Marketing, Engineering, or Dev teams you've previously coordinated with using JIRA, or creating entirely new capabilities. These potential AI applications are then carefully evaluated based on factors like their expected impact (e.g., cost savings, revenue growth), technical feasibility, data availability, and alignment with overall business goals, allowing the company to rank them and focus on the most promising projects first.

The process of creating a detailed, strategic plan that lays out the sequence and timing for implementing specific AI initiatives across the business. This plan identifies key milestones, required resources, dependencies between projects, and assigns responsibilities, providing a clear path for teams like Marketing, Engineering, and Development (which you've coordinated previously) to follow for successful AI adoption over time. 

Involves assessing and recommending the most appropriate AI software, specific algorithms or pre-built models, and major cloud platforms like AWS SageMaker, Google Vertex AI, or Azure ML for a company's needs. This guidance ensures the chosen technical infrastructure aligns with the business's AI objectives, budget, existing systems, and the specific requirements of the planned AI applications. 

 Establishes the crucial framework detailing how your business will effectively collect relevant data (perhaps from systems used by Marketing, Engineering, or Dev teams you've worked with), securely store it, and apply governance rules for quality, access, and compliance. It ensures data is properly prepared and readily available in the right format to successfully fuel your AI models and initiatives.

We will define the essential rules and principles to ensure that artificial intelligence systems, including those potentially used by the Marketing, Engineering, or Dev teams you've worked with, are developed and deployed responsibly, fairly, and transparently. These guidelines address critical concerns like bias mitigation, data privacy, accountability, and maintaining human oversight to build trust and manage potential risks.