Get AI out of the pilot stage and into the decisions and work your people do every day.
Focus investment
Prioritize use cases by decision value, feasibility, data readiness, risk and adoption.
Work with your software
Plug AI into the data and applications you already run.
Change the work
Change roles and workflows so people use AI as part of the job.
5 parts of putting AI to work.
AI opportunity and portfolio design
Pick the decisions and workflows where AI pays off most, and the order to tackle them.
Enterprise AI architecture
Set up what AI needs to run in production, security included.
AI agents and intelligent applications
Build assistants and agents for specific roles, with clear limits and a person to hand off to.
Governance and responsible operation
Establish controls for access, privacy, evaluation, auditability, model change and operational risk.
Adoption and operating-model change
Train the people who use it, then improve it from how they use it day to day.
From one valuable workflow to an enterprise capability.
- 01
Select
Choose 1 decision or workflow where AI will change a result.
- 02
Ground
Give it the data and permissions it needs, and nothing more.
- 03
Deploy
Put it inside the tools people already use, with a person deciding what it may do.
- 04
Extend
Measure adoption and operating impact, then widen from evidence.
Built through connected expertise.
Intelligence builds the AI, and Technology wires it into the software you run. When the AI reaches customers, Marketing joins; when it opens a new product, so does Innovation.
- Intelligence
- Technology
- Innovation
- Products & IP
Where AI replaced the wait for manual reports.
From TenEleven.ai.
