Top trends
- Support deflection and sales automation remain the fastest wins.
- Agent-style workflows are rising, but only with strong approvals and evals.
- Budgets are shifting from experiments to owned programs with SLAs.
- Security and data residency questions happen before any build.
What’s working
Scoped workflows. Single owner, single metric, guardrails.
Retrieval + refusals. Policy prompts, redaction, and QA.
Instrumentation. Cost, latency, accuracy, and feedback loops.
Enablement. Training and change management to drive adoption.
What slows teams down
- Poor data readiness and access controls.
- No measurement—can’t prove ROI or safety.
- Unclear ownership; projects stall post-pilot.
- Compliance uncertainty delaying approvals.
How to accelerate safely
- Start with 1–2 workflows with clear owners and metrics.
- Deploy guardrails: redaction, approvals, logging, evals, and rollbacks.
- Instrument everything; review weekly.
- Expand via a 60–90 day roadmap tied to budget and risk.
AI adoption succeeds when governance and measurement ship with the first workflow—not after.
FAQ
Which industries lead?
SaaS, services, healthcare, and fintech are ahead due to clear ROI and process volume.
Biggest governance ask?
Logging, audit trails, and redaction for regulated data.
How do budgets look?
Commonly 4–8% of ops/IT budgets earmarked for AI programs with measurable milestones.
What about agents?
They’re growing, but only succeed with approvals, evals, and clear kill-switches.