AI Consulting for CIOs
AIDOLS helps CIOs ship enterprise AI in 90 days inside the platform stack they already own — ServiceNow, Microsoft, ITIL, ITSM/ITOM, AIOps — without proprietary lock-in or vendor sprawl. Every engagement carries a written security review, integrates with existing IAM and SSO, and ships with the governance documentation the audit committee and the regulator both ask for.
What CIOs get from AIDOLS
Specific outcomes scoped against the metrics the CIO office already tracks — not generic value props.
AI inside your existing enterprise platforms
AIDOLS deploys inside the platforms you already own — ServiceNow, Microsoft 365 Copilot, Salesforce Einstein, SAP, Oracle, ITSM/ITOM stacks — rather than asking IT to support another vendor. CIOs avoid the operational tax of running parallel platforms and the procurement overhead of net-new vendor contracts.
Vendor consolidation, not vendor sprawl
Enterprise AI programs tend to accumulate point-solution vendors quickly. AIDOLS runs a vendor-rationalization pass at Sprint scope, identifies overlap, and consolidates against your existing platform commitments. CIOs end the year with fewer vendor contracts, not more.
Governance documentation aligned to your audit framework
Every Build ships with model risk management documentation aligned to the framework your auditor cares about — SR 26-2 (the US interagency model-risk guidance that replaced SR 11-7 in April 2026), OSFI E-23, PRA SS1/23, the ECB guide to internal models — plus SOC 2 control mapping, data residency documentation, and right-to-explanation outputs. Internal audit and the regulator get the same artifact set.
AIOps that improves the on-call quality of life
AIDOLS AIOps Build engagements ship inside your existing observability and ITSM stack (Datadog, Splunk, Dynatrace, ServiceNow, PagerDuty), surface root cause faster, and cut alert fatigue measurably. The system reduces the on-call burden, not adds another dashboard.
The 4 problems we solve for CIOs
Your AI vendor list keeps growing. Much of it overlaps.
Enterprise AI procurement typically explodes once individual business units start signing AI vendor contracts independently. The CIO discovers the inventory at audit time: dozens of AI vendors, overlapping capability, uneven security posture, and a procurement spend the finance team cannot reconcile to outcomes. Rationalizing the portfolio after the fact can take a year or more and a separate consulting engagement.
AIDOLS runs vendor rationalization as part of a Sprint or as a standalone diagnostic. The output is a consolidated vendor map against your existing platform commitments, a recommended decommissioning sequence, and a written savings projection.
Your SaaS vendors are turning into AI vendors. Your security posture cannot keep up.
Every major SaaS platform — ServiceNow, Salesforce, Microsoft, SAP, Oracle, Workday — has shipped AI features, with sub-processor disclosures, data-handling changes, and inference-spend models that did not exist at the original contract signing. CIOs face dozens of contract amendments and security-review re-assessments at once, with security teams already stretched.
AIDOLS Sprints scope a vendor-AI-feature posture review across your top 10–20 SaaS contracts: what AI features are enabled by default, what data flows to which sub-processor, what governance controls exist, and what contract amendments are required to align with your governance posture. CIOs get a defensible posture review the security team can act on without standing up a new program.
AIOps promised to cut alert fatigue. Most deployments added another dashboard.
Most AIOps deployments fail because they bolt onto an existing observability stack (Datadog, Splunk, Dynatrace) without changing the underlying alert taxonomy or the on-call routing. The result is another dashboard for the SRE team to ignore, with no measurable reduction in alert volume or MTTR. CIOs see a vendor invoice without a corresponding improvement in operational metrics.
AIDOLS AIOps Build engagements scope explicitly against alert volume, MTTR, and false-positive rate. The Build replaces or rationalizes existing alerting rules, integrates with your ITSM (ServiceNow, Jira) for ticket routing, and ships with a written 30-day post-launch metrics report. For a Build, if the deployed system does not generate ROI exceeding its fee within 90 days, the fee is refunded in full; the Sprint, an assessment, carries no refund, and Scale's refund is prorated.
The audit committee asks who owns AI governance. The honest answer is "no one full-time."
In most enterprises, AI governance lives across security, legal, risk, and architecture without a single accountable owner. The audit committee asks for an AI governance posture review, the CIO produces a slide, and 12 months later the same question returns with more urgency. Standing up the function in-house can take a year or more and a senior hire.
AIDOLS Sprint engagements scope an AI governance posture review with deliverables aligned to your existing audit framework: a model inventory, a risk-tier classification, a governance RACI, and a 90-day remediation roadmap. CIOs get a defensible artifact set the audit committee can accept without committing to a permanent hire on day one.
Get your AI Readiness Score in 5 minutes
See where production AI fits in your operations: a 0–100 score across strategy, data, tooling, team and governance, with three next steps.
Start the Assessment →How a CIO engagement typically works
Four steps from kickoff to production cutover. Fixed fee at every step.
CIO + IT leadership kickoff
Joint workshop with the CIO, enterprise architect, security lead, and the platform owner of the affected SaaS stack. Agree the scope (single Build, vendor rationalization Sprint, AIOps deployment, or governance posture review) and lock the SOW.
Architecture + security review
AIDOLS engineers integrate with your enterprise architecture team, your security team (SOC 2, data-handling, IAM/SSO, secrets), and your procurement gates. Architecture decision records produced for your reference architecture.
Build + platform integration
Build inside your existing platforms (ServiceNow, Microsoft, SAP, Salesforce). Weekly architecture review with your enterprise architect. Governance documentation drafted in parallel with engineering work.
Production cutover + governance handover
Production deployment inside your platform. Governance artifact suite handed over: model card, risk-tier classification, decision-log specification, drift monitoring plan, audit-framework alignment write-up. Optional Scale retainer for ongoing operations.
Pricing model that fits a CIO's budget cycle
Three transparent fixed-fee tiers — no time-and-materials drift, no partner-pyramid markup, no surprise change orders.
Best for: CIOs scoping a vendor-rationalization, AI governance posture review, or AIOps thesis. Produces an artifact set the audit committee and the security team can act on.
- •Data + infrastructure audit
- •Prioritized opportunity map with ROI estimates per use case
- •Target-state reference architecture
- •90-day implementation roadmap with named owners
- •Executive readout deck
Best for: CIOs ready to ship one production AI system in 90 days inside their existing enterprise platform. Includes governance documentation aligned to your audit framework.
- •Production AI system shipped end-to-end
- •Data engineering, model development, MLOps deployment
- •Integration into existing systems
- •Post-launch evaluation harness + monitoring
- •For a Build, if the deployed system does not generate ROI exceeding its fee within 90 days, the fee is refunded in full; the Sprint, an assessment, carries no refund, and Scale's refund is prorated.
Best for: CIOs operating production AI systems who want ongoing model monitoring and governance updates inside their platform stack.
- •Ongoing engineering retainer post-deployment
- •Model retraining, monitoring, drift detection
- •Incident response + evaluation harness updates
- •One new feature release per month
- •An alternative to a full-time senior MLOps hire
AIDOLS vs Big Four for a CIO
| Dimension | AIDOLS | Big Four |
|---|---|---|
| Pricing model | Fixed fee per tier; written, no T&M drift | Time-and-materials retainer; partner-pyramid markup |
| Platform posture | Inside your existing platforms; no parallel stack | Often a recommendation to add net-new platform vendors |
| Vendor consolidation | Sprint-scope rationalization against your existing platform commitments | Vendor recommendations add to procurement burden |
| Governance documentation | Aligned to SR 26-2 / OSFI E-23 / PRA SS1/23 / the ECB guide to internal models in Build fee | Typically a separate governance engagement |
| Time to production | 90 days; 30-day post-launch verification | Multiple phased SOWs before production |
| Security review integration | Runs in parallel with Weeks 1–4; SOC 2 mapping documented up front | Security review handled separately, often slows engagement |
| Audit + regulator readiness | Same artifact set for internal audit, external audit, regulator | Separate engagements per audience |
| Exit clarity | Scale: 60-day notice after a 12-month minimum; clean handover to enterprise IT | Long retainers; proprietary platforms can create lock-in |
What a CIO should ask before hiring an AI consulting firm
Seven questions to put on every shortlist call. Firms that cannot answer crisply on all seven are not engineering-first.
- 1.Which of our existing platforms (ServiceNow, Microsoft, Salesforce, SAP, Oracle) does the firm integrate against natively, and which require net-new vendor commitments?
- 2.What governance documentation is included in the Build fee, and against which audit framework?
- 3.How does the security review process work, and does it run in parallel with engineering work?
- 4.What is the vendor-rationalization output, and what is the typical AI spend recovery in the first 12 months?
- 5.How is AIOps measured against alert volume, MTTR, and false-positive rate?
- 6.What proprietary components, if any, will we be locked into post-deployment?
- 7.Who personally is on the engagement, and do they stay on after the SOW is signed?
Calculate your AI ROI before you sign anything
Plug your numbers in. See projected annual savings, first-year ROI and months to payback in minutes.
Run the ROI Calculator →Common objections from CIOs — and our honest answers
"My architecture team will not accept another reference architecture."
AIDOLS does not impose a reference architecture. We deploy inside your existing one and produce architecture decision records your enterprise architect keeps. There is no AIDOLS target-state platform to migrate to.
"Our security review takes 12 weeks. The 90-day clock will not start."
AIDOLS runs security review in parallel with Weeks 1–4 architecture work. SOC 2 control mapping, data-handling agreements, and IAM/SSO integration are documented up front. Where your process explicitly requires security approval before any code, the 90-day clock starts at approval.
"We have already committed to Microsoft Copilot / ServiceNow Now Assist / Salesforce Einstein."
Good — AIDOLS deploys inside those platforms and extends the native platform AI with custom use cases, governance documentation, and integration into other systems the native AI does not cover.
"We have an internal AI Center of Excellence already."
AIDOLS works alongside an internal CoE rather than replacing it. Engagements are scoped jointly with the CoE — AIDOLS ships the first 1–3 production systems while the CoE matures, then transitions operations to the CoE under a Scale retainer wind-down.
"Our procurement requires 3 vendor responses to RFP."
AIDOLS responds to RFPs. A fixed fee, with a refund clause on the Build, is easier to compare than a time-and-materials estimate: procurement can put total cost and time to value side by side.
FAQs from CIOs
Does AIDOLS deploy inside existing enterprise platforms like ServiceNow, Microsoft, or Salesforce?
Yes. AIDOLS deploys inside the platforms you already own — ServiceNow, Microsoft 365 Copilot, Salesforce Einstein, SAP, Oracle, ITSM/ITOM stacks — rather than adding parallel platforms. Architecture decision records are produced for your enterprise architect to keep.
How does AIDOLS handle vendor consolidation?
AIDOLS runs vendor rationalization as part of a Sprint engagement or as a standalone diagnostic. The output is a consolidated vendor map against your existing platform commitments, a decommissioning sequence, and a written savings projection.
What governance documentation is included in an AIDOLS Build?
Every Build ships with a model card, risk-tier classification, training data manifest, decision-log specification, drift monitoring plan, and a written governance write-up aligned to your audit framework — SR 26-2, OSFI E-23, PRA SS1/23, or the ECB guide to internal models. SOC 2 control mapping and data-residency documentation are included as standard.
How does AIDOLS handle security review and procurement gates?
AIDOLS runs security review in parallel with Weeks 1–4 architecture work. SOC 2 control mapping, IAM/SSO integration, secrets management, and data-handling documentation are produced up front. Where your process requires security approval before any code, the 90-day clock starts at approval.
Can AIDOLS work alongside our internal AI Center of Excellence?
Yes. AIDOLS works alongside an internal CoE rather than replacing it. Engagements are scoped jointly with the CoE — AIDOLS ships the first 1–3 production systems while the CoE matures, then transitions operations to the CoE under a Scale retainer wind-down.
How does AIDOLS measure AIOps engagements?
AIDOLS AIOps Build engagements scope explicitly against alert volume, MTTR, and false-positive rate, baselined at kickoff and verified 30 days post-launch.
What is included in an AIDOLS AI governance Sprint?
A governance Sprint produces an AI model inventory across the enterprise, a risk-tier classification per model, a governance RACI, a 90-day remediation roadmap, and an audit-framework alignment write-up. The deliverable set is designed for the audit committee and the security team to act on without further consulting work.
How does AIDOLS pricing compare to Big Four AI consulting for CIOs?
Big Four AI engagements are typically billed as time and materials at $400–$800/hr and often produce a strategy document plus a separate implementation SOW. AIDOLS prices Sprints at $15K–$25K, Builds at $75K–$150K, and Scale retainers at $25K/month, with a deployed system rather than a slide deck as the deliverable. For a Build, if the deployed system does not generate ROI exceeding its fee within 90 days, the fee is refunded in full; the Sprint, an assessment, carries no refund, and Scale's refund is prorated.
AI consulting for other roles
AIDOLS works across the full executive stack. If your engagement spans multiple functions, we scope it jointly.
Next steps
- What AI-native consulting is Engineers who build and deploy the system on a fixed fee, instead of a strategy deck billed by the hour.
- Course lesson: nothing gets lost Keep what you build in AI tools as plain text your organization owns, not inside a vendor account.
- The AI vendor security questionnaire What to ask an AI vendor before you sign: data residency, sub-processors, privacy law and contract terms.
Three ways to start, scoped to a CIO mandate
Pick the path that matches the next decision your office has to make.