As businesses rush to harness the power of modern AI and ML technologies to drive growth, innovation, and productivity, Workday has released a list of 38 “Future of Work” use cases for those powerhouse technologies.
The Workday vision for ML and AI cuts across its two core product lines — HCM and Financials —and also touches on opportunities to create better and more effective experiences for users of its applications. These use cases were shown at the Workday AI/ML Innovation Summit this week, and are displayed in the slide below.
With business executives across every industry making ML and AI top priorities, I wanted to share Workday’s view of how customers are using, or will soon be using, ML and AI to:
- Simplify and accelerate daily work
- Automate wherever possible to eliminate drudge work and expense
- Drive greater employee engagement
- Push new insights into and across the organization
- Generate better business outcomes for every customer
Since the slide is a bit dense, let me unpack it by listing the “Future of Work with ML and AI” use cases across the four broad segments used by Workday in that slide: HCM, Experience, Finance, and Future examples.
1. HCM
- Skills Cloud
- Skills Graph
- Career Hub
- Candidates skills match for recruiters
- Learning recommendations
- Skills miner
- Suggested skills for worker
- Compensation survey management
- Suggested jobs
- Learning recommendations personalization
- Talent marketplace
- Gig recommendations
- Suggested skills for job requisitions
- Job-match analysis enhancements
- Job recommendations
- Time-tracking anomalies
- Suggested skills for learning admins
- Ongoing Skills Cloud enhancements
2. Finance
- Expense Protect
- Customer-payment matching
- Journal insights
- Plan anomaly detection
- Expense-receipts scanning
- Supplier-invoice automation: OCR
- Supplier-invoice automation: Worktag recommendations
- Anomaly detection
- Spend category recommendation: Purchase requisitions
3. Experience
- Suggested search
- Related search
- ML prompts
- Task recommendations
- Related actions
4. Future Examples
- Supplier discovery
- Tax-attribute recommendations
- Content insights
- Automatic text generation
Final Thought
No doubt Workday’s got plenty of other ML and AI projects underway, but these are the ones the company felt able to share at this time.
I’m hoping these lists will give business leaders some ideas for where new insights will emerge, and also a better sense of the massive potential of ML and AI when they’re perceived not as some black-box magic trick but rather as enablers of innovation, acceleration, simplification, automation, and opportunity.
To hear more data modernization, AI/hyperautomation, cybersecurity, and growth strategies from CIO practitioners, tune into Acceleration Economy’s Digital CIO Summit, which takes place April 4-6. Register for the free event here.
