Transformation: AI

Technology

Technology

Finally, we arrive at technology. There are so many options for organizations to choose from it can become quite overwhelming. Luckily, organizations like Mosaic have seen incredibly successful AI implementations, and AI that falls flat on its’ face because of faulty supporting tech. The technology should be pliable enough to meet the organizations transformation, not forcing the transformation to follow itself. Technology is the foundation upon which all the changes to people, process and culture rest. By developing the right technology solution supported by surrounding enablers, organizations can make massive strategic gains.

data science coe assessment meeting image _ transformation AI technology

A prominent energy generation and transmission firm wanted to focus on utilizing internal data for improved business decision making, optimizing their data analytics Center of Excellence (CoE) team structure, matching analytics technology with organizational fit, and convincing business stakeholders of the value and possibilities of advanced analytics. Mosaic was contracted to deliver an in-depth assessment, including a comprehensive AI technology assessment.

Due to our vast experience in designing and deploying AI/ML tech, Mosaic is very comfortable in mapping the goals, use cases, internal skill sets with tools that can actually help instead of hinder them.

Data Architecture & Infrastructure Needs

Data Integration

ID and manage data sources, map needs with existing/prospective technology

Data Quality & Governance

Manage standardization & enrichment tasks with the goal of unified metadata

Data Repository Management

Manage backups, replication, and recovery, plan and manage repository lifecycle, including scaling & performance tuning

Data Analytics

Manage and support self-service analytics toolsets, design standards/strategic reports/dashboards with an eye towards usability

AI Applications

Automate data pipelines to feed into advanced machine learning models to improve stakeholder experience, including algorithm performance and monitoring model drift.

Explore the Other Components of Transformation: AI