Automation13 min2026-06-08EN

AI Program Governance: Day-30 Go/No-Go Gate Guide 2026

Michele Cecconello
Mike Cecconello

Procurement-ready guide to AI program governance: the day-30 go/no-go gate, risk-share contract clauses, and the 5 mechanisms that make programs ship.

AI Program Governance: Day-30 Go/No-Go Gate Guide 2026
Last updated: June 2026 · Written by: SUPALABS Team · Reading time: 13 min

If you're a Chief Procurement Officer, a CFO-office category lead, or a Group Strategy buyer who has already paid for one or two AI consulting engagements that produced a deck and not much else — the question you're now asking is structural, not vendor-by-vendor. The question is: what mechanism actually aligns a consulting partner's incentives with our outcomes? The answer is AI program governance, and the single most important governance mechanism is a day-30 go/no-go gate with a contractual no-fee-for-Phase-II clause if the proof falls short. This guide explains what AI program governance is, why most enterprise AI programs fail at it, the five governance mechanisms that actually work, and the contract language procurement teams can paste into next quarter's RFP.

What AI Program Governance Actually Is (And What It Isn't)

The phrase AI program governance gets used to mean two completely different things, and the conflation is expensive. The first meaning — let's call it "AI model governance" or just "AI governance" — covers ethics, model risk, EU AI Act conformity, bias auditing, acceptable-use policy, data lineage, and the artefacts your General Counsel signs off on. It's important. It's also not what this guide is about.

The second meaning — the operational meaning — is the operating cadence, decision-rights structure, and risk-share commercial terms that determine whether the program actually ships an outcome. That is AI program governance. It is not a policy document. It is the answer to four very specific questions:

  • Who decides when an opportunity moves from discovery to build, and on what evidence?
  • Who escalates when BU A blocks BU B's priority, and to whom, on what timeline?
  • Who pays, in what tranches, against what proof points — and what happens if the proof points aren't met?
  • Who owns the intelligence layer, the patterns library, and the update cadence after the engagement ends?

Programs with strong AI governance documents and weak AI program governance produce beautiful 90-page policy binders and zero shipped automations. Programs with the opposite mix ship outcomes and then retrofit the policy layer in Phase III. Both are needed. They are not the same thing, and the procurement function that conflates them buys the wrong scope.

Why Most AI Programs Fail at Governance, Not Technology

McKinsey's State of AI 2025 reports that roughly 70% of enterprise AI initiatives never reach production at meaningful scale. IBM's Institute for Business Value puts the "delivers expected ROI" figure at 25%, and the "scales enterprise-wide" figure at 16%. Those numbers are not a technology indictment — foundation models have improved every six months for three years. They are a governance indictment.

The failure modes are remarkably consistent across post-mortems:

  • No decision rights. A steering committee meets monthly, reviews status, asks good questions, and authorises nothing. The program drifts.
  • No escalation path. BU A wants the customer-care LLM trained on its data; BU B refuses to share. There is no documented arbiter. The work sits.
  • Misaligned commercial terms. The vendor is paid 40% up front, 30% at midpoint, 30% on "final deliverable acceptance." The vendor's incentive is to hit milestones, not to ship value. The deck arrives on time and is filed.
  • No source attribution. Recommendations cannot be traced to specific interviews, telemetry signals, or documents. When a BU MD challenges a recommendation, the consultant references "industry benchmarks." The recommendation dies.
  • No post-program owner. The engagement ends. The intelligence layer is a PDF. Six months later, nobody remembers which opportunities were prioritised or why.

Each of those is a AI program governance failure, not a technology failure. The model worked. The procurement structure didn't. This is why the 2026 RFP cycle for enterprise AI is shifting from "show us your model accuracy" to "show us your governance and risk-share terms."

The Five Governance Mechanisms That Actually Work

Across enterprise AI engagements that actually shipped outcomes — meaning at least two production-grade automations live and measured against baseline at 12 months post-kickoff — five mechanisms recur. Programs missing any one of them have a recoverable problem. Programs missing three or more produce a deck and stop.

1. Executive sponsorship with real budget authority

The sponsor must be CFO, COO, or Office of the CEO — someone with cross-BU budget authority and the political weight to override a BU MD's objection. CIO-only sponsorship is the most common failure pattern: the program drifts toward tooling decisions because that's the CIO's natural lens, and cross-BU workflow redesign — where the real ROI lives — never gets authorised. The sponsor's job is not to attend the monthly steering committee. It is to make three to five binary calls during the program that nobody else has authority to make.

2. Cross-BU steering committee with explicit escalation rights

One MD per in-scope BU, plus Group Risk, Group Data, and the executive sponsor. Meets every two weeks during Phase I and II. Has an explicit, documented escalation path to ExCo for cross-BU conflicts. The most common failure: a steering committee that exists on the org chart but meets monthly, reviews slides, and never resolves a conflict. A real steering committee is uncomfortable. If yours isn't, it's theatre.

3. Gated phases with shared go/no-go decisions

The program runs in phases with a binary decision at each gate. The most important gate is at day 30. Subsequent gates happen at end of Phase I, end of Phase II planning, and at each implementation cluster. "Go/no-go" means exactly that — either the criteria are met and the next phase is authorised, or they aren't and the program is paused, scope-reduced, or cancelled. Gates without a real "no-go" option are not gates. They are review meetings with a fancy name.

4. Risk-share commercial terms

The vendor's payment structure must include a meaningful tranche that is contingent on shared outcomes — not on milestone completion, not on deliverable acceptance, not on "client satisfaction." Specifically: no fee for Phase II if the day-30 proof falls short of agreed criteria. This is the single contractual clause that aligns a consulting vendor's incentives with a buyer's outcomes more than any other. It is also category-rare, which is why procurement officers screenshot it when they see it.

5. Source-attributed deliverable lifecycle

Every recommendation in the deliverable must trace to specific source evidence — a named interview, a telemetry pattern, a document section — and the artefact must be persistent and updateable by internal teams after the engagement ends. This is a governance mechanism, not a delivery aesthetic. It prevents "industry-benchmark dressed up as bespoke insight," it allows post-engagement audit, and it makes the patterns library a living asset rather than a frozen PDF.

The Day-30 Go/No-Go Gate: Mechanics and Why It Works

The day-30 gate is the central AI program governance mechanism because it is the only one that genuinely transfers risk from buyer to vendor in a way procurement can enforce. Everything else — steering committees, escalation paths, source attribution — is operating discipline. The gate is a contractual commitment.

What proof is required

Before signing, the buyer and vendor agree, in writing, in the SOW, on the precise criteria the day-30 gate must clear. Generic "client satisfaction" or "alignment on direction" is not a criterion — it's an escape hatch. Concrete criteria look like:

  • Minimum number of validated opportunities surfaced in the pilot cluster — for example, 30 ranked, scored, source-attributed candidates.
  • Minimum aggregate addressable saving across those opportunities — for example, EUR 4M in identified annualised cost or revenue impact.
  • Minimum evidence quality threshold — for example, 80% of the top-10 opportunities backed by at least two independent sources (interview + telemetry, or survey cluster + document).
  • Minimum operator validation rate — for example, top-10 opportunities stress-tested by a named senior operator who has run that workflow type at enterprise scale.

Who decides

The go/no-go decision is taken jointly by the executive sponsor (CFO/COO) and the vendor engagement lead. Not by consensus of the steering committee — that produces drift. Not by the vendor alone — that's a conflict of interest. Not by the buyer alone — that's not a shared gate. The structure is binary: both parties review the day-30 evidence pack, both parties sign the gate decision document, and the program either advances to Phase I scope expansion or it stops.

What happens if proof falls short

The engagement ends. The buyer pays the agreed Phase I day-1-to-30 fee — which is typically 30–40% of the total Phase I + II contract value — and there is no fee for Phase II. The buyer keeps whatever artefacts were produced in the first 30 days. The vendor walks away. This is the structural commitment that distinguishes a program from an open-ended advisory engagement.

Why this aligns incentives

A traditional consulting engagement with 40/30/30 milestone billing pays the vendor regardless of whether the buyer values the work. The vendor's economic incentive is to manage scope and hit milestones, not to ship value the buyer wants to fund further. A day-30 gate with a no-Phase-II-fee clause flips that. The vendor's economic incentive becomes: "produce 30 days of work the buyer values enough to fund the next 9 weeks." That is exactly the incentive the buyer wants the vendor to have. It is the only commercial structure where vendor and buyer want the same thing during the riskiest phase of the program.

Contract language template

Suggested clause for procurement to adapt:

"At day 30 of Phase I, Client and Provider shall jointly review the evidence pack against the Day-30 Acceptance Criteria set forth in Schedule [X]. The decision to proceed to Phase I scope expansion and Phase II shall be taken jointly by Client's Executive Sponsor and Provider's Engagement Lead, and shall be documented in the Day-30 Gate Decision Memo. If the Day-30 Acceptance Criteria are not met, Client may terminate this Agreement at Client's sole discretion upon written notice within ten (10) business days, in which event Provider shall not be entitled to any Phase II fees and Client's sole financial obligation shall be the Phase I Days 1–30 fee already invoiced. All work product produced during Days 1–30 shall remain Client's property."

Risk-Share vs Time-and-Materials vs Fixed-Fee

The structural problem with traditional consulting payment terms is that the vendor's economic incentive does not match the buyer's outcome. Below is the comparison procurement teams should hold against any incoming AI program proposal — the AI consulting day 30 gate column is the one that materially de-risks the engagement.

Commercial model Vendor's economic incentive Typical buyer outcome Risk transfer
Time & materialsMaximise billable hours; expand scopeEngagement runs longer than planned; deliverable depth varies; cost overruns commonNone — risk fully on buyer
Fixed fee, deliverable-basedMinimise effort to deliverable acceptance; resist scope creepStripped-down deliverable that meets the letter of the SOW; little flex for emerging insightPartial — vendor bears overrun, buyer bears outcome risk
Milestone billing (40/30/30 etc.)Hit milestones to trigger invoices; milestone definitions become the workVendor produces what's needed to invoice; value to buyer is incidentalNone — vendor paid regardless of outcome
Pure outcome-based (% of savings)Maximise measurable savings — sometimes at the cost of measurement integrityDisputes over what counts as a "saving"; vendor cherry-picks easy winsHigh — but creates measurement war
Risk-share with day-30 gateProduce 30 days of work the buyer values enough to fund the next 9 weeksVendor over-invests in the first 30 days; buyer either ends cheaply or buys with confidenceHigh — clean, enforceable, no measurement disputes

The risk-share-with-gate model is not a partial commitment or a softer version of outcome-based pricing. It is a binary, contractually enforceable transfer of the riskiest phase of the engagement onto the vendor. The buyer's worst case is paying the day-1-to-30 fee for an evidence pack that didn't meet criteria — typically 30–40% of total contract value. The buyer's best case is funding Phase II with documented proof in hand. There is no scenario where the buyer pays the full contract for an engagement whose first 30 days didn't deliver.

Governance Cadence for a 14-Week Program

Operating cadence is the second pillar of AI program governance after commercial structure. Below is the cadence pattern used in enterprise programs that ship — meetings are short, decisions are documented, escalations have explicit timelines. The pattern assumes a 14-week Phase I + II.

Week Steering committee Gate decisions ExCo escalation route
Week 1Kickoff: scope confirmation, escalation paths documented, day-30 criteria signedPilot cluster selectionN/A
Week 2Bi-weekly status: discovery progress, blocker logStanding slot if needed
Week 3Day-30 evidence pack drafting beginsEscalation review every Friday
Week 4Pre-gate review with sponsorDAY 30 GO/NO-GO GATESponsor briefs ExCo on gate outcome within 5 days
Weeks 5–6Bi-weekly status: scope expansion progressStanding slot
Week 7Mid-Phase-I checkpoint: cross-BU dependency reviewVendor consolidation decisionsCross-BU conflicts escalated within 48h
Week 8Phase I close: intelligence layer handoverEnd-of-Phase-I gateSponsor briefs ExCo on Phase II go-ahead
Weeks 9–11Bi-weekly: implementation planning, RACI buildPer-cluster gate decisionsStanding slot
Week 12Operating-model design reviewResource allocationCross-BU resource conflicts escalated
Week 13Culture & upskilling plan reviewChange management approach
Week 14Phase II close: handover to internal Phase III ownersEnd-of-engagement gateSponsor presents to ExCo / Board

What this cadence enforces is decision velocity. Bi-weekly steering committees beat monthly ones because four weeks is too long to discover that a BU is blocking access. Documented escalation timelines beat informal ones because "this needs to go up the chain" without a deadline rots. Pre-gate reviews beat surprise gate meetings because gate decisions made on first exposure to the evidence are bad decisions.

The Source-Attribution Discipline

Source attribution is a governance mechanism dressed as a documentation standard. The rule: every recommendation, every prioritisation, every scored opportunity in the deliverable must link to the specific evidence that produced it — the interview ID, the telemetry pattern signature, the survey cluster, the document section.

This matters for three governance reasons:

  • It prevents pattern-matching as deliverable. Without source attribution, a consultant can drop "industry benchmark" recommendations into the catalogue and nobody can challenge them. With it, every recommendation has to survive the question "what evidence in our organisation produced this?" Composite benchmarks dressed up as bespoke insight cannot pass that test.
  • It enables post-engagement audit. When a BU MD challenges a recommendation six months after handover, the audit trail exists. The recommendation came from these three interviews, this telemetry signal, this document. The challenge can be evaluated on evidence, not on memory.
  • It makes the intelligence layer durable. A recommendation with no source is a guess that ages out the moment the consultant leaves. A recommendation with five source links is an asset internal teams can re-validate, extend, or retire as the organisation evolves.

Source-attribution discipline is the difference between a deliverable that survives Phase III and one that is filed and forgotten. It is also one of the cheapest governance mechanisms to specify — a single SOW clause requires it — and one of the highest-leverage.

Cross-BU Conflict Resolution Structure

Every cross-BU AI program produces the same conflict by week 6. BU A wants AI capability X; BU B says "we built that in 2024 and it doesn't work, don't put it on our roadmap." Or: BU A wants to share its customer data with a group-wide LLM; BU B's legal team blocks it. Or: BU A and BU B both want priority in the implementation queue and there's capacity for one.

If the arbitration mechanism is improvised at week 6, the conflict either escalates emotionally (relationships break) or quietly stalls (both BUs deprioritised, nothing ships). The governance fix is to document the arbitration mechanism in week 1, before any conflict exists. The standard structure:

  • Tier 1 — vendor engagement lead resolves for conflicts that are scope-clarification questions, not resource conflicts. Documented in the weekly status, no escalation.
  • Tier 2 — steering committee resolves for cross-BU resource or scope conflicts where both BUs are at the table. Bi-weekly cadence; if not resolved within one cycle, auto-escalates to Tier 3.
  • Tier 3 — executive sponsor (CFO/COO) resolves for conflicts the steering committee couldn't close. 48-hour SLA. Decision is binding and documented.
  • Tier 4 — ExCo or Board resolves for conflicts the sponsor escalates, typically because the conflict is strategic rather than operational. Rare. Slow. Avoid if Tier 3 can close it.

Documenting this in week 1 means that when the conflict appears in week 6, both BUs already know how it will be resolved. The argument is about the substance, not about who has authority to decide. This is what mature AI program governance looks like in practice: not the absence of conflict, but the presence of a predictable mechanism to resolve it.

Post-Program Governance Handoff

Most consulting engagements end with a final read-out and an invoice. The intelligence layer goes into a SharePoint folder. The patterns library is a PDF. Six months later, the organisation cannot find half of what was produced and cannot update the half it can find. This is a governance failure, not a delivery failure.

Programs with strong post-engagement governance design the handoff as a discrete workstream, not an afterthought. The components:

  • Intelligence layer ownership transfer. The artefact lives in a system the client owns and the client can update. Not a vendor-hosted dashboard. Not a PDF. Source attribution remains intact post-handover.
  • Patterns library maintenance protocol. Internal team designated as owner. Quarterly cadence for adding new opportunities surfaced from operations. Same ontology, same scoring vectors, same governance class taxonomy.
  • Quarterly review cadence. The steering committee doesn't dissolve at end-of-engagement. It downsizes — quarterly meetings, smaller agenda — and reviews the catalogue's evolution. New opportunities added, shipped opportunities retired, blocked opportunities re-scoped.
  • Update-rights documentation. Who can add to the catalogue, who can change scoring, who can promote an opportunity to active implementation. Without this, the catalogue calcifies; with it, the catalogue compounds.

The structural test for any prospective partner: "Six months after the engagement ends, what specifically will be different about how our organisation works with this catalogue, vs how we work with the strategy decks we have on the shelf today?" If the partner can't answer that concretely, the post-program governance is missing — and the catalogue will join the strategy decks on the shelf.

Procurement-Ready Contract Clauses

The following clauses are drafted to be pasted directly into procurement's standard SOW template, with brackets for organisation-specific terms. Each addresses one of the five AI program governance mechanisms. Procurement officers facing a 2026 AI program RFP should hold any incoming proposal against these clauses — missing language is missing risk transfer.

Clause topic Sample language
Day-30 go/no-go gate "At day 30 of Phase I, Provider shall present an evidence pack measured against the Day-30 Acceptance Criteria in Schedule [X]. If criteria are not met, Client may terminate without further fees beyond Days 1–30. All work product remains Client's property."
Source attribution requirement "Every recommendation, prioritisation, and scored opportunity in the Deliverable shall be traceable, via a documented audit trail, to the specific interview ID, telemetry pattern, survey response cluster, or document section that produced it. Composite industry benchmarks are not acceptable as sole source."
Intelligence-layer ownership transfer "The Intelligence Layer artefact, including all data, scoring logic, ontology, and source-attribution links, shall be delivered in a format Client owns and can update without further Provider involvement. Provider shall provide a 60-day knowledge-transfer window post Phase II close."
Post-engagement update rights "Client retains perpetual rights to update, extend, and modify the Intelligence Layer, Patterns Library, and all associated artefacts. Provider's IP claims are limited to general methodology and shall not encumber Client's operational use of the Deliverable."
Steering committee cadence "Steering Committee shall convene bi-weekly during Phase I and II, with a documented escalation path to Client's Executive Sponsor within 48 hours for cross-BU conflicts and to ExCo within 5 business days for strategic conflicts the Sponsor cannot resolve."
Operator validation requirement "The top-10 prioritised opportunities at each gate shall be stress-tested by a Named Senior Operator with documented experience running the workflow type at enterprise scale. Operator name and experience shall be provided in Schedule [Y] prior to engagement start."

These six clauses, together, convert what is otherwise an open-ended advisory engagement into a structured program with measurable governance. They are not aggressive procurement language. They are minimum protections for a category that has spent three years producing decks instead of outcomes.

SUPALABS First-Party Data

SUPALABS AI Program Governance Data

Aggregated across TODO_SUPALABS_FILL_IN_PROGRAM_COUNT enterprise programs delivered between TODO_SUPALABS_FILL_IN_DATE_RANGE. Anonymised at the engagement level.

Gate performance

  • • Day-30 gate pass rate across all engagements: TODO_SUPALABS_FILL_IN_DAY30_PASS_RATE
  • • Engagements where Phase II was not invoiced due to gate non-pass: TODO_SUPALABS_FILL_IN_NO_PHASE_II_COUNT
  • • Average evidence pack size at day 30: TODO_SUPALABS_FILL_IN_AVG_EVIDENCE_PACK source-attributed items
  • • Median time from gate decision to Phase II kickoff: TODO_SUPALABS_FILL_IN_GATE_TO_PHASE_II_DAYS days

Governance discipline

  • • Average steering committees held per 14-week program: TODO_SUPALABS_FILL_IN_STEERING_COUNT
  • • Cross-BU conflicts resolved at Tier 2 (no sponsor escalation): TODO_SUPALABS_FILL_IN_TIER2_RESOLUTION_RATE
  • • Intelligence layers still actively updated by client 12 months post-handover: TODO_SUPALABS_FILL_IN_12MO_USAGE
  • • Source-attribution coverage at handover: TODO_SUPALABS_FILL_IN_SOURCE_ATTR_RATE

The two numbers procurement teams care about most are the day-30 pass rate and the no-Phase-II count. Together they describe whether the risk-share commitment is real or theatrical.

FAQ

What is AI program governance, and how is it different from AI governance?

The two phrases are used interchangeably and shouldn't be. "AI governance" typically refers to ethics, model risk, EU AI Act conformity, bias auditing, and acceptable-use policy — the artefacts your General Counsel signs off on. AI program governance is operational: it's the cadence, decision rights, escalation paths, and risk-share commercial terms that determine whether the program actually ships outcomes. Programs can have strong AI governance and weak AI program governance — they produce beautiful policy binders and zero shipped automations. The procurement function that conflates the two buys the wrong scope.

Why does a day-30 go/no-go gate matter so much?

Because it's the only contractual mechanism that aligns a consulting vendor's incentives with a buyer's outcomes during the riskiest phase of the program. Traditional milestone billing pays the vendor regardless of value delivered — the vendor's incentive is to hit milestone definitions, not to ship something the buyer wants to fund further. A day-30 gate with a no-Phase-II-fee clause flips that incentive: the vendor must produce 30 days of work the buyer values enough to authorise the next 9 weeks. It's the structural commitment procurement officers screenshot, because it's category-rare and it materially transfers risk from buyer to vendor.

What should the day-30 acceptance criteria look like?

Specific and measurable, not "alignment on direction." Concrete examples: a minimum number of source-attributed opportunities surfaced (e.g., 30), a minimum aggregate addressable saving (e.g., EUR 4M annualised), a minimum evidence-quality threshold (e.g., 80% of top-10 backed by two independent sources), and a minimum operator-validation rate (e.g., top-10 stress-tested by a named senior operator). Generic criteria turn the gate into theatre; specific criteria make it enforceable. The criteria should be agreed in writing in the SOW before signing, not negotiated at week 4 when one party has leverage over the other.

What happens if the day-30 gate doesn't pass?

The engagement ends. The buyer pays the Days 1–30 fee — typically 30–40% of total Phase I + II contract value — and there is no fee for the remaining scope. All artefacts produced in the first 30 days remain the buyer's property. The vendor walks away. This is the structural commitment that separates a program from an open-ended advisory engagement. A vendor that refuses to put this clause in the SOW is signalling, clearly, that they are not confident enough in their own day-30 output to stake their fee on it. Procurement teams should treat that signal accordingly.

How do we avoid the gate becoming a rubber stamp?

Three structural protections. First, the acceptance criteria are written into the SOW before kickoff, not at week 3 when one party has leverage. Second, the gate decision is taken jointly by the executive sponsor (CFO/COO) and the vendor engagement lead, both signing a Day-30 Gate Decision Memo — not by consensus of the steering committee, which produces drift, and not by either party unilaterally. Third, the evidence pack is reviewed in a pre-gate session at end of week 3, so the day-30 decision is made on documented evidence, not on first-impression reaction. Without these protections, gates default to "go" because nobody wants to be the one who stopped the engagement.

How do these governance mechanisms work for organisations that already have internal AI teams?

They become more important, not less. Internal teams running AI program work without explicit governance produce the same drift as external consultants — opportunity catalogues that age out, recommendations without source attribution, cross-BU conflicts that stall. The five mechanisms (executive sponsorship, steering committee, gated phases, risk-share commercial terms where applicable, source-attributed deliverable lifecycle) apply equally to internal programs. The day-30 gate variant for internal programs is a "fund Phase II or redeploy the team" decision — the consequence is internal reallocation rather than contract termination, but the discipline is the same. AI program governance is about the program, not about whether the people running it have an external or internal employer.

See what a real day-30 gate looks like in your SOW

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Sources & References

📊 Belangrijke Statistieken (2025)

88%
of organizations using AI in at least one function
Source: McKinsey 2025
62%
experimenting with AI agents
Source: McKinsey 2025
74%
achieve ROI from AI in year one
Source: Arcade.dev 2025
64%
say AI enables their innovation
Source: McKinsey 2025
$150-200B
projected enterprise AI market by 2030
Source: Glean 2025

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