How to Get Started With AI in Your Organisation
A practical guide to moving from pressure to progress
The pressure to "do AI"
You're hearing about AI everywhere. Your board asks about your AI strategy. Your competitors are "doing AI." Vendors are pitching AI solutions. Your team is experimenting with ChatGPT.
The pressure is real. But pressure without clarity leads to scattered experiments, vendor lock-in, and wasted resources.
Why most AI projects stall
Most organisations start with tools, not tasks. They buy AI platforms, sign up for vendor demos, or experiment with ChatGPT, hoping something will stick.
This approach fails because:
- You don't know what problem you're solving
- You can't assess whether the tool actually fits your context
- You have no clear ROI or success metrics
- You haven't considered governance, risks, or compliance
- You lack buy-in because the value isn't clear
Projects stall because they lack foundation. They start with solutions, not problems.
Start with tasks, not tools
The right way to start is with tasks—the work your team actually does, the problems they face, the bottlenecks that slow them down.
Ask: What tasks are manual, slow, or error-prone? What decisions require expertise that's scarce? What processes create risk or compliance issues?
Starting with tasks gives you:
- Clear problem definition
- Obvious value if solved
- Natural success metrics
- Team buy-in (they experience the pain)
Focus on operational drag
Operational drag is the friction in your day-to-day work: manual data entry, repetitive decision-making, error-prone processes, information silos, compliance bottlenecks.
These are often the best AI opportunities because:
- They're well-defined problems with clear success metrics
- They impact productivity and risk immediately
- They're often solvable with today's AI capabilities
- They build confidence and momentum
Start with operational drag. Build from there.
Use cases → business case → adoption
The journey from idea to adoption follows a clear path:
1. Use cases
Start with structured use cases. Define what the AI would do, who owns it, what's feasible, and what value it would create. Structure enables comparison and prioritisation.
2. Business case
Build a business case with ROI framing, risk assessment, and implementation planning. This gives you confidence and stakeholder buy-in.
3. Adoption
Plan for adoption: pilot, validate, scale. Start small, prove value, then expand.
This path works because it builds confidence at each step. You validate feasibility before committing. You prove value before scaling.
Why validation matters
Validation is the difference between confident decisions and costly mistakes. Before committing resources, validate:
- Feasibility: Can AI actually do this given your data, systems, and constraints?
- Value: Is the value worth the effort, cost, and risk?
- Fit: Does this fit your governance, risk appetite, and strategic goals?
- Readiness: Do you have the data, systems, and team capability needed?
Validation doesn't mean perfection. It means honest assessment of what's possible, what's valuable, and what's ready.
The role of governance & readiness
Governance and readiness aren't afterthoughts. They're foundations. Consider them early:
Governance
What are your risk appetite, approval processes, and compliance requirements? What guardrails do you need? Governance shapes what's feasible and how you implement.
Readiness
Do you have the data, systems, and team capability needed? What prerequisites must be in place? Readiness determines timing and feasibility.
Consider governance and readiness early. They shape everything else.
How an Organisation Profile keeps everything aligned
An Organisation Profile is a structured view of your goals, risks, constraints, governance, data context, and team capabilities. It ensures every AI recommendation fits your organisation.
When you start with an Organisation Profile:
- Recommendations align with your strategic goals
- Feasibility assessments reflect your actual constraints
- Risk assessments match your risk appetite and governance
- Tool recommendations fit your data context and systems
- Implementation plans consider your team capabilities
An Organisation Profile is your compass. It keeps everything aligned.
Frequently Asked Questions
How long does it take to get started?
You can start exploring AI opportunities immediately. Building your Organisation Profile takes about 15-20 minutes. Generating your first use case takes about the same. The key is to start, validate, and iterate.
Do I need technical expertise?
No. Clairable is designed for non-technical leaders. The questions are in plain language, and the outputs are structured for business decision-making, not technical implementation.
What if I don't have good data?
Many AI use cases don't require perfect data. Some start with structured documents, process automation, or decision support. Clairable assesses data requirements as part of feasibility, helping you identify what's possible with what you have.
How do I prioritize use cases?
Prioritize based on value (time saved, risk reduced, revenue opportunity), feasibility (what you can do now), and strategic alignment (what fits your goals). Clairable helps you compare use cases across these dimensions.
Do I need to commit to a vendor?
No. Clairable recommends types of tools and approaches, not specific vendors. You can use the briefs to evaluate vendors, pilot off-the-shelf tools, or guide internal discussions.
Ready to get started?
Explore Clairable to start your AI journey with structure, context, and confidence.