AI Readiness — Assessment, Vendor Selection, and Team Preparation
TL;DR
Most AI initiatives fail at one of three points: misreading organizational readiness, picking the wrong vendor, or under-preparing the team. Score your organization across six readiness dimensions before investing in tools or strategy. Use a vendor scorecard for any AI purchase over $10K/year. Hire AI champions embedded in each function rather than building a centralized AI team. Buying tools before finishing readiness leads to shelf-ware within 12 months.
Ce que couvre ce guide
The full readiness assessment + vendor selection + team preparation framework you should run before signing any major AI contract. You’ll get the 6-dimension scoring rubric, the 7-criterion vendor scorecard, the four parts of team preparation, and a 90-day plan for moving from “interested in AI” to “competent at AI.” Built for marketing leaders who want to avoid the shelf-ware trap.
Points clés à retenir
- AI readiness has six dimensions: data quality, data access, infrastructure, skills, governance, leadership.
- Vendor selection is about outcomes, data handling, and integration — not features or demos.
- Teams thrive with embedded champions, not centralized AI departments.
- Invest in senior judgment augmented by AI; don’t automate away the craft you need later.
- Buying tools before finishing readiness leads to shelf-ware within 12 months.
The 6-Dimension Readiness Assessment
Score each dimension 1 (not ready) to 5 (fully ready):
| Dimension | Level 1 (Not Ready) | Level 5 (Fully Ready) |
|---|---|---|
| Data Quality | Siloed, messy, inconsistent definitions | Unified, clean, documented, accessible |
| Data Access | Engineering ticket required for everything | Marketers self-serve via governed tools |
| Technical Infrastructure | Patchwork of disconnected tools, manual exports | Integrated stack with APIs and a clear data layer |
| Skills & Literacy | No one on the team has used AI seriously | Most of the team uses AI weekly; designated champions |
| Governance & Ethics | No AI policy, no review process | Documented policy, escalation paths, audit cadence |
| Leadership & Budget | Leadership skeptical, no dedicated budget | Leadership sponsor, protected pilot budget, clear OKRs |
Score totals — 6-14: foundational work needed before pilots. 15-22: ready for pilots in limited scope. 23-30: ready to scale with governance.
Vendor Selection Framework
- Job clarity — can you name the specific job in one sentence? If not, pass.
- Measurable outcome — does the vendor commit to a metric, not just features?
- Data handling — where does your data live? Is it used for training? Get it in writing.
- Integration reality — does it plug into your existing stack or create a new silo?
- Vendor staying power — funded, growing, likely to exist in 24 months?
- Exit cost — if you leave in 18 months, what do you lose?
- Proof, not demos — reference customer in your industry at your scale you can speak to?
The Vendor Evaluation Scorecard
Before any AI purchase over $10K/year, score each criterion 1–5. Weight by what matters most.
| Criterion | Weight | What 5/5 Looks Like |
|---|---|---|
| Job clarity and outcome metric | Haut | Vendor names a specific outcome metric they will improve |
| Data privacy and handling | Haut | Contractual guarantees; no training on your data; clear residency |
| Integration with existing stack | Haut | Native connectors to your top 3 tools; no new silo |
| Reference customer at your stage | Moyen | Reference call scheduled with comparable company |
| Total cost of ownership (3 years) | Moyen | Predictable pricing; no usage-based surprise spikes |
| Exit portability | Moyen | You own and can export all outputs and data |
| Team support and training | Faible | Onboarding program, documentation, human support |
Team Preparation
- Literacy baseline — every marketer should write a decent prompt, recognize hallucinations, and know when not to use AI. Set this minimum within 90 days.
- Champions, not departments — embed an AI champion in each marketing sub-function (content, growth, analytics, brand). Champions spread practice faster than centralized AI teams.
- New skill mix — marketers who thrive combine three skills: the old craft (writing, analytics, strategy), AI fluency (prompting, tool selection, output evaluation), and taste.
- Role evolution, not replacement — invest in senior judgment and leverage juniors into it, rather than replacing juniors with automation.
The 90-Day Readiness Plan
| Jours | Focus | Outcome |
|---|---|---|
| 1-30 | Baseline and literacy | Assessment completed; team tool access; baseline training |
| 31-60 | First two pilots | Two contained pilots running with measurable targets |
| 61-90 | Evaluate and plan scale | Pilots reviewed; keep/kill decisions; Q2 roadmap |
Erreurs courantes à éviter
- Buying tools before finishing readiness assessment. Low-readiness orgs end up with shelf-ware within 12 months.
- Hiring a data scientist first. Hire an AI power user inside marketing first.
- Centralizing AI in one team. Embedded champions spread practice faster.
- Trusting demos over references. Demos are theater; references are evidence.
Mesures à prendre cette semaine
- Run the 6-dimension readiness assessment with your leadership team.
- Score honestly.
- Dimensions where you score below 3 are next quarter’s priorities — before any new tool purchase.
Foire aux questions
How long does AI readiness take to build?
Foundational work: 1–2 quarters. Mature scale: 12–18 months from cold start.
Should I hire an AI consultant?
Helpful for assessment and pilot design. Avoid long-term reliance — your team needs to own AI capability internally.
What’s the most important readiness dimension?
Leadership sponsorship and data quality are tied — both block everything downstream.
How big should an AI champion network be?
One per function (content, growth, analytics, brand). Meet weekly for 30 minutes.
What qualifies as a good AI vendor reference?
Comparable company, comparable scale, willing to take a 30-minute call. If they can’t produce one, that’s the answer.
Sources et lectures complémentaires
- Riman, T. (2026). Introduction au marketing et à l'IA 2e édition.
À propos de l'agence Riman : We run AI readiness assessments and vendor selection. Book a readiness review.
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