Where to start with AI for your business

AI is everywhere. From headlines to boardrooms, it’s fast becoming the go-to buzzword for innovation, efficiency and growth. But for many businesses, the hype creates pressure to “do something with AI”, often without a clear idea of what that actually means or how it will add value.

The result? Rushed experiments, wasted time, and tools that solve problems nobody actually has.

Flip the script: start with the problem, not the tech

Rather than jumping in and trying to retrofit AI into your business, a better approach is to take a step back and ask: what are the challenges we’re facing? Where are we wasting time, losing revenue or struggling to scale?

AI isn’t a magic fix, but it can be a powerful solution when applied with purpose. The most successful AI implementations don’t start with “let’s use AI”, they start with “we need to solve this”.

For example:

• Are your customer support queries overwhelming the team?
• Do you spend hours each week writing reports, replying to similar emails, or processing the same type of data?
• Do you have valuable information spread across spreadsheets, emails and systems?

These are all real-world pain points AI can help solve.

Identify the bottlenecks

Once you’ve pinpointed a few core problems, ask yourself:

• Can this process be automated?
• Is this task repetitive or rules-based?
• Would faster access to data or insights help?
• Could a smarter recommendation or prediction engine support decision-making?

AI isn’t only about robots and deep learning models, sometimes it’s as simple as using natural language processing to summarise documents or machine learning to spot patterns in sales data.

Don’t overlook the small wins

There’s a misconception that AI needs to be big and bold to be worthwhile. But often, the best returns come from the small, unglamorous wins:

• Auto-generating email responses to common queries
• Improving data entry accuracy with smart validation
• Using chatbots to triage requests before a human steps in

Start small. Prove the value. Then scale.

This doesn’t mean you can’t do more in the future, but the above is where to start.

Create a strategy – or get help doing it

If you’re unsure where to begin, or you do want to go more in-depth with AI, consider speaking with someone who specialises in AI strategy. A good expert won’t pitch you a tool, they’ll help you:

• Audit your existing workflows
• Prioritise use cases based on impact and effort
• Understand what’s possible with your data
• Plan the build or integration in phases

This makes the process less about chasing trends and more about solving problems with the right tools.

AI isn’t always the answer

It’s also worth saying: AI won’t always be the solution. Sometimes better processes, clearer roles or simpler tools can make a bigger difference.

But when AI is the right fit, it can change the game.

Final thoughts

Instead of asking “how do we use AI?”, start asking “where do we need help?”. Ground your AI adoption in real business needs, not hype, and you’ll avoid wasted effort, while unlocking real value.

If you’re not sure where to begin, talk to someone who can help you cut through the noise and build an AI approach that works for your business.