Solution Atlas
EverydayUser storyConsultative playbook

Service desk volume is growing — we want a triage agent before more headcount

An IT operations leader is facing a 25% rise in service desk tickets year-on-year. Many are repeatable password resets, software requests, and "how do I" questions. The team wants to deploy a conversational agent before approving more contractor headcount.

Trigger
Cost pressure; repetitive ticket volume.
Good outcome
Copilot Studio agent in Teams, message volumes modelled, Managed Environments and DLP applied.
Diagnostic discovery

Signals this story fits

Observable cues that confirm the conversation belongs here.

  • ·Service-desk ticket volume rising year-on-year
  • ·Repetitive ticket categories (password resets, software requests, "how do I…")
  • ·IT operations under headcount pressure
  • ·Teams platform widely used as employee surface
  • ·No conversational AI in production

Questions to ask

Open-ended, SPIN-style — each one has a reason it matters.

  1. 1.What are your top five ticket categories today, and what fraction of volume do they represent?

    WhyConcentrated top-five volume is the deflection opportunity.

  2. 2.What's the average cost per ticket today?

    WhyAnchors the deflection business case.

  3. 3.Have you scoped a chatbot before? If so, what stopped it?

    WhySurfaces past failure modes — usually message-pack pricing surprise or weak integrations.

  4. 4.What integration points exist with ServiceNow, Entra ID, AD, SAP?

    WhyDetermines what the agent can actually do, not just say.

  5. 5.Are Managed Environments and DLP applied to Power Platform today?

    WhyWithout governance, the agent becomes shadow IT inside the tenant.

  6. 6.How do you measure 'time saved' beyond a ticket count?

    WhyBridges from cost reduction to employee experience metrics.

Baseline → target architecture

TOGAF-style gap framing — what we typically see today, and what the proposed end state looks like. The gap between them is the engagement.

Baseline architecture

Service desk human-only. Power Platform present but inconsistent governance. No agent. Conditional Access applied to end users but Power Platform environments not subject to Managed Environments policy.

Typical concerns

  • ·Repetitive low-value tickets consuming agent time
  • ·Headcount pressure with rising demand
  • ·Past chatbot attempts stalled at scale
  • ·Power Platform governance partial
  • ·No clear deflection metric

Capability gaps

  • ·Conversational agent with grounded responses
  • ·Action runtime (Power Automate) wired to backend systems
  • ·Managed Environments + DLP applied to agent surface
  • ·Message-volume forecasting and cost discipline
  • ·Deflection telemetry
Target architecture

Copilot Studio agent surfaced in Teams. Power Automate Premium executes actions against AD, ServiceNow, M365 admin. Dataverse stores conversation state. Managed Environments enforces DLP and governance on the agent. Telemetry surfaces deflection rate, escalation accuracy, and cost per message.

Key capabilities

  • Conversational agent in Teams
  • Action runtime via Power Automate Premium
  • Stateful conversation history in Dataverse
  • Managed Environments + DLP
  • Identity-gated access

Enabling SKUs

Resolved in the ‘Recommended cards’ section below.

Architecture decisions

Each decision is offered as explicit options with trade-offs — Hohpe's “selling options” principle. A safe default is noted where one exists.

  1. Decision 1.Agent scope — narrow (password reset only) vs broad (multi-intent)

    Narrow

    When it fitsFirst agent; high-confidence single intent.

    Trade-offsLow ceiling on deflection; second agent needed soon.

    Broad multi-intent

    When it fitsMature CoE; existing Power Platform governance.

    Trade-offsMessage volume rises faster; cost less predictable.

    Default recommendationNarrow for the first 8 weeks, broaden once message-volume forecast is reliable.

  2. Decision 2.Custom agent vs M365 Copilot extension

    Custom Copilot Studio agent

    When it fitsSpecific scenario; tight integration with backend systems.

    Trade-offsOperates outside M365 Copilot surface.

    M365 Copilot extension

    When it fitsWant the agent visible in the M365 Copilot surface; users already in Copilot.

    Trade-offsRequires M365 Copilot licensing first.

    Default recommendationCustom agent if M365 Copilot not deployed; extension once Copilot lands.

  3. Decision 3.Message-pack sizing — tenant pack vs per-user

    Tenant message pack

    When it fitsBroad use across many users; volume predictable.

    Trade-offsCost surprise if volume undershoots or overshoots.

    Per-user

    When it fitsNarrow rollout to specific cohorts.

    Trade-offsMore expensive per message at scale.

    Default recommendationTenant pack sized to 80% of forecast; expand as volume confirms.

Low-risk trial — proof of value

30-day Copilot Studio agent pilot for top 3 ticket categories

4 weeks

Agent built in Copilot Studio covering top three ticket categories. Power Automate flows for AD password reset and software-request approval. Dataverse for conversation history. Managed Environments + DLP applied. Deployed to one business unit in Teams. Deflection telemetry captured.

Success criteria

  • Top three ticket categories deflected at 30%+ rate
  • Escalation accuracy above 90%
  • Zero DLP policy violations during the pilot
  • Message volume modelled and within forecast band

InvestmentCopilot Studio tenant pack ~€185/month + Power Automate Premium per-user. Existing service-desk staff untouched during pilot.

Proof metrics

  • ·Deflection rate on top categories above 30%
  • ·Cost per deflected ticket below cost per human-handled ticket
  • ·Employee CSAT on the agent above 4/5
  • ·Service-desk staff redeploy to higher-value work

Recommended cards

The SKUs and capabilities most likely to be part of the solution, with the editorial rationale for each in the context of this story. Add the ones that fit your situation.

Why for this story

The low-code agent platform. Surfaces in Teams, integrates with Power Automate for actions, and includes governance via Managed Environments. Message-pack pricing is the cost surprise lever.

Why for this story

The action runtime. When the agent says "I will reset that password," Power Automate actually does the work via SAP, AD, or ServiceNow connectors.

Why for this story

State for conversation history and policy data. Capacity-priced storage.

Why for this story

Identity guardrail — Conditional Access governs who can use the agent; SSO into the agent flows from M365.

Back to Low-code agents with Copilot Studio