Before You Start
How to Use This Assessment
This is a diagnostic tool, not a quiz. Work through it honestly — the value comes from the gaps you identify, not the score you achieve. Most African businesses score between 25 and 55 on their first pass. That is exactly where AI investment creates the most leverage.
1
Score Each Question
Circle or tick the answer that most accurately describes your business today — not your aspirations. Each answer carries a score (0, 1, 2, or 3).
2
Total Your Pillar Scores
Each pillar has 5 questions worth up to 3 points each (max 15 per pillar). Add up your total across all 5 pillars for your overall score out of 75.
3
Find Your Tier & Roadmap
Turn to page 12 to interpret your score and find the 90-day AI roadmap matched to your tier. Your lowest-scoring pillar is your highest-leverage starting point.
The 5 pillars — assessed in this workbook
P1
Data Readiness
Do you have data AI can actually use?
P2
Process Readiness
Are your workflows AI-automatable?
P3
Team & Skills
Can your team adopt and operate AI tools?
P4
Infrastructure
Does your tech stack support AI integration?
P5
Strategy & Leadership
Is there strategic commitment and vision driving AI adoption?
Africa-specific context
This assessment is calibrated for African business realities — inconsistent data infrastructure, limited bandwidth, mixed digital literacy across teams, and the specific AI tools that perform in low-data environments. The scoring reflects what's achievable here, not Silicon Valley benchmarks.
01
Pillar One
Data Readiness
AI is only as good as the data that feeds it. Before any tool, you need to know what data you have, where it lives, and whether it's clean enough to use.
Question 2.1 — Process Documentation
How well-documented are your core business processes?
Mostly in people's heads, not written down 0
Some SOPs exist but incomplete 1
Key processes documented and followed 2
Full SOP library, versioned, and enforced 3
Question 2.2 — Repetitive Tasks
What proportion of your team's weekly time is spent on repetitive, rule-based tasks?
Less than 10% — mostly creative/judgement work 0
10–30% — some routine tasks 1
30–60% — significant repetitive workload 2
Over 60% — heavily task-driven operations 3
Question 2.3 — Current Automation
How much of your operational workflow is already automated?
No automation — fully manual 0
Basic automation (email autoresponders, simple tools) 1
Moderate automation (Zapier, scheduled reports, CRM flows) 2
Advanced automation — APIs, custom workflows, triggers 3
Question 2.4 — Decision Speed
How quickly can your team act on new data or market signals?
Days to weeks — decisions are slow and meeting-heavy 0
Same day — but requires manual data pull 1
Hours — dashboards exist but not real-time 2
Near real-time — data triggers automatic actions 3
Question 2.5 — AI Tool Experimentation
Has your team used any AI tools in operations in the past 6 months?
No — not yet explored 0
Individual experiments only (e.g., ChatGPT occasionally) 1
2–3 AI tools in regular use across teams 2
AI-first workflows — embedded across multiple functions 3
Pillar 2 Score: _____ / 15 | Highest-impact automation opportunity: _____________________
AI
Bonus Section
The Africa-Ready
AI Tool Stack
The 12 AI tools that actually work in African business contexts — tested for low-bandwidth, local language, and SME-scale operations.
AI Tool Stack
12 AI Tools That Work for African SMEs
Filtered for: low-bandwidth performance, no-credit-card-required tiers, local language support, and practical SME use cases. Tested across Nigeria, Kenya, Ghana, and South Africa contexts.
Africa connectivity note
Test every AI tool on a 3G connection before committing. Many enterprise AI tools assume 50Mbps+ broadband. Claude, Google Gemini, and WhatsApp-based tools consistently perform best in sub-10Mbps environments common across West and East Africa.
Q 3.1 — Digital Literacy
What is the overall digital literacy level of your team?
Basic smartphone use only 0
Comfortable with office tools and apps 1
Uses SaaS tools daily, some data skills 2
Technical team — APIs, data analysis, coding comfort 3
Q 3.2 — AI Awareness
How AI-aware is your leadership team?
No awareness or interest in AI 0
Aware of AI but haven't prioritised it 1
Leadership actively exploring AI use cases 2
Dedicated AI champion or role exists 3
Q 3.3 — Learning Culture
How does your team typically adopt new tools?
Resistant to change — tools often abandoned 0
Slow adoption, needs heavy training and support 1
Moderate adoption with onboarding and documentation 2
Fast adoption — team experiments and self-teaches 3
Q 3.4 — AI Budget Allocation
Has your business allocated any budget for AI tools or training in 2026?
No budget and not planned 0
Considering but not allocated yet 1
Under $500/month allocated for AI tools 2
$500+/month or a dedicated AI investment line 3
Q 3.5 — Hiring for AI
Has AI capability been a factor in recent or planned hiring?
Not considered in hiring 0
Nice-to-have but not a priority 1
Actively sought in at least one recent hire 2
AI skills are a requirement for key roles 3
Pillar 3 Score: _____ / 15
Pillar 4 Score: _____ / 15 | Biggest infrastructure gap: _______________________________
Pillar 5 Score: _____ / 15
TOTAL SCORE P1 ___ + P2 ___ + P3 ___ + P4 ___ + P5 ___ =
___ / 75
Score Interpretation
Your AI Readiness Tier
75–100
AI-Ready — Scale & Optimise
You have strong data foundations, automated workflows, and team buy-in. Focus: move from AI tools to AI products. Build proprietary data moats, fine-tune models on your own data, and explore AI as a revenue line — not just a cost reducer.
50–74
AI-Building — Accelerate Implementation
Good foundations, some quick wins already achieved. The gap is in consistency and scale. Focus: pick 2–3 functions to go fully AI-first, invest in team training, and connect your data sources to give AI tools enough signal to be useful.
25–49
AI-Aware — Build Before You Automate
You know AI matters but foundations are patchy. Focus: data cleanup and documentation first, then layer AI tools. Trying to AI-automate a chaotic process just creates a faster mess. Fix the process, then automate it.
0–24
AI-Starting — Foundation First
Most African SMEs start here — this is not a disadvantage. Focus: start with one AI tool that solves a real daily pain (WhatsApp automation, meeting transcription, or content drafting). Build the habit before building the strategy.
Your 90-Day AI Roadmap (All Tiers)
M1
Month 1 — Diagnose & Pick Your First Win
Identify your #1 time-drain — the task eating 5+ hours/week
Select one AI tool from the stack (page 7) that addresses it directly
Set up the tool with one team member as champion
Run a 2-week pilot — measure time saved vs. baseline
M2
Month 2 — Clean Data, Automate Workflows
Audit and centralise your customer data into one accessible location
Document 3 core operational processes that could be AI-assisted
Set up one automation (Zapier/Make) connecting your most-used tools
Deploy AI for customer communication (WhatsApp bot or email template AI)
M3
Month 3 — Expand & Measure ROI
Expand your first AI win to the full team — build an SOP around it
Add a second AI use case from a different pillar (e.g., if M1 was ops, try marketing)
Calculate your 90-day AI ROI: hours saved × hourly cost = cash equivalent saved
Book a strategy session to plan your next AI investment cycle
AI Strategy Session — 60 Minutes
You have your score.
Now let's build your plan.
In a 60-minute AI Strategy Session, we turn your assessment results into a concrete, prioritised AI implementation plan — specific tools, integration sequencing, team training map, and 90-day milestones — built for your business, your team size, and your connectivity reality.
Assessment results review + pillar deep dive
3 prioritised AI use cases for your business
Tool stack recommendations with cost breakdown
90-day implementation roadmap (written)
Team training sequence and resource list
ROI projection for your first 90-day AI sprint
Book Your AI Strategy Session →
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