Find what is holding back AI adoption.
Arist shows talent teams where employees are stuck, why they are stuck, and what each role needs to use AI effectively.
Usage is not the same as capability.
A dashboard can count sessions. It cannot tell you whether employees trust the output, know how to apply the tool to their role, or stopped using it because policy, access, or workflow gets in the way.
Those are different gaps. They require different fixes.
Find and fix the gaps.
- 01
Interview
Hear from employees across roles, regions, and confidence levels. Separate knowledge and skill gaps from tool, policy, access, and process barriers.
- 02
Analyze
Connect employee insight to adoption, HRIS, and learning data. See the root causes by cohort and the value at stake.
- 03
Act
Give each cohort the right response—from role-specific practice and manager reinforcement to clearer policy or a redesigned workflow.
- 04
Prove
Connect capability change to tool adoption, then repeat the interviews to see what changed.
- 30,000 employees trained in 3 weeks
Arist makes it remarkably easy to build high-quality learning in a short amount of time, without sacrificing depth or impact. Their needs analysis agent has also been incredibly valuable, providing fast, clear insights that help us focus on our biggest knowledge, skill, and competency gaps.
What talent teams get
A role-based AI capability map
See where knowledge, confidence, application, and workflow break down.
Root-cause clarity
Know whether the answer is training, communication, policy, access, process change, or a combination.
Targeted AI upskilling
Give each cohort support tied to the work it actually does.
A defensible baseline
Track capability and adoption from a clear starting point.
Evidence of change
Show leaders where employee behavior and business use improved.
Start with what people need to do differently.
Bring us your AI adoption goal. We will show you what is getting in the way and how to fix it.