View a markdown version of this page

Workforce analytics use cases - Accenture Enterprise AI – Scaling Machine Learning and Deep Learning Models

This whitepaper is for historical reference only. Some content might be outdated and some links might not be available.

Workforce analytics use cases

Workforce analytics is an advanced set of data analysis tools and metrics for comprehensive workforce performance measurement and improvement. Workforce analytics are highly sensitive by nature and require trusted ML and DL algorithms to create scalable, productionized solutions for harnessing human potential.

To bring about a balance between responsible AI and computing at scale, Accenture created an advanced, reusable, AWS MLOps architecture for multiple workforce productivity use cases, including:

  • Solutions.AI for Talent and Skilling — An AI-powered solution that delivers intelligent insights to help close the skills gap in any organization. Through Solutions.AI, Accenture created enterprise-wide AI solutions that deliver game-changing results, fast.

  • FutureofU: Skills. Jobs. Growth — An AI-enabled platform solution created in collaboration with Accenture partners, who are committed to accelerating a smooth transition to help get diverse talent skilled and integrated into the AI workforce.

  • Intelligent Workforce Insights – Uses the power of cutting-edge AI/ML technologies to develop role maps that identify declining, stable, and emerging skills, both internally and in the market, and assess roles for upskilling.

The challenge with these use cases is that the backend needs massive amount of computing resources to infer and produce the ML score results. For optimal user experience, the scoring needs to happen fast enough, with near real-time intermediate scores. All three of these use cases have three common technical traits:

  • ML engineering at scale

  • AI/ML automation with responsible AI

  • End-to-end productionized large-scale resilient AI/ML systems