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AI Workload Check

Get your AI Workload Check with 3 quick wins.

The check makes visible whether M365 workload, manual process work, knowledge search, cloud cost or AI governance is currently your strongest lever.

For US and international leadership, operations and IT teams where AI already appears in daily Microsoft 365/Azure work.

Typical workload and risk signals
  • Copilot sees more than the business has clarified.
  • ChatGPT runs next to IT and touches unclear data classes.
  • M365 knowledge stays fragmented while AI is expected to answer.
  • Agents need approvals, owners and human review before access.
What the check makes visibleInstant result in the browser, personal interpretation after submission.
Top opportunities

Which automation and cloud levers make sense first.

Risk score

Where governance, security or cost control burns first.

3 quick wins

What can create relief without migration or tool lock-in.

Start / Stop / Wait

A clear recommendation: start, check further, wait or deliberately do not start.

Value first

Complete the 5-minute check and see the result instantly.

Answer 12 short questions. Then see whether M365 workload, process leakage, cloud waste or AI governance is currently your strongest lever.

0/12 questions answered
Step 1/4Context0/12 questions answered
01How large is the company?Company size helps classify governance and scaling pressure.
02How central are Microsoft 365/Azure today?The score is especially useful for M365, Azure and identity-related leverage.
03Which cloud situation fits best?Cloud waste often appears when platforms grow before ownership is clear.
04Roughly how high is monthly cloud/SaaS spend?A rough range is enough. This is about waste potential, not accounting.

100% free. No tool lock-in. No sensitive data in the check. Instant result plus personal 3-quick-win review.

How we score

The score shows how Tirion thinks: technical, commercial and without theatre.

Process leakage

Which manual routines tie experts to work that could be structured or automated?

Cloud waste

Where do cost, complexity or platform risks appear because guardrails and ownership are weak?

AI governance

Which shadow AI, data and approval risks would block later scaling?

Similar patterns

Which anonymized case patterns match your industry, size, tech stack and problem?

No automatic sales push.

The result intentionally leads into three possible outcomes. The score stays useful even when a call would be too early.

Use the guide first

If pressure, sponsor or Microsoft leverage is still weak, use the matching decision guide first.

Score review

If a lever looks reliable, Kevin reviews quick wins, risk and the next path with context.

Do not start

If the score is too early, it does not become a project. That is a valid outcome.

What happens next?

1
Answer 12 questions

You invest 5 minutes and recognize your own leakage profile.

2
See the instant result

Process Leakage, Cloud Waste, AI Governance Risk and Decision Readiness become visible immediately.

3
Get 3 quick wins interpreted

Tirion checks which levers are actually reliable in your situation.

4
Clarify the next step

If useful, AI Kickstart, Sprint or Advisory follows. If not, we say so clearly.

Risk reduced before you decide.

  • No tool lock-in
  • No migration in the first step
  • No data sharing in the check
  • GDPR-/security-oriented approach
  • Clear recommendation, even when "do not start" is the right answer

Technical depth, not just consulting language.

  • Azure OpenAI, Microsoft 365 and identity as a controllable architecture frame
  • FinOps KPIs for owners, tags, alerts and cost accountability
  • Data classes for SharePoint, customer data and sensitive process information
  • Human-in-the-loop review points for AI workflows with real impact