There’s no escaping it: AI is everywhere. Every boardroom conversation, vendor pitch and LinkedIn post seems to promise a future transformed by artificial intelligence. Everyone wants to harness its power, but the path to making it work is rarely clear. As our CTO, Jake Blough, says, “AI is easy to conceptualize but very difficult to operationalize.”
The hype is real, but so is the confusion. If you’re wondering how to turn AI’s potential into practical business value, you’re not alone.
To cut through the noise, I’ll explain what you need to consider before jumping in so you can simplify your ROI calculations and ensure AI delivers meaningful results for your business. Here are my five tips for creating a strong AI strategy.
1. Define a clear business objective
First things first: start with a clear business objective. AI is not a silver bullet; it’s a tool, and like any tool, its effectiveness depends on the problem you choose to solve.
Before considering algorithms or models, ask yourself, “What do I want to achieve?” Are you looking to improve customer service, automate repetitive tasks, boost sales or uncover new business insights? A well-defined objective keeps your AI project focused.
From there, define your use cases. While pursuing the shiniest, most ambitious AI applications is tempting, the most successful projects start small and specific. Whether it’s automating invoice processing, predicting equipment failures or personalising marketing campaigns, a targeted use case makes it easier to measure success and demonstrate value.
2. Pick the right AI
Once you’ve defined your use case, it’s important to understand the different types of AI available. The approach you choose will shape both your implementation and your potential ROI.
At one end of the spectrum, you have fully custom-trained models, which require building and training an AI from the ground up using your data. Although very powerful, they’re often resource-intensive, costly and best suited for highly specialised needs.
Fine-tuning is simpler, allowing you to adapt an existing model to your requirements with less effort. Retrieval Augmented Generation (RAG) combines large language models with your data sources, enabling AI to provide intelligent and contextually relevant answers. There are also in-app AI features, where AI integrates with software you already use, along with API-based AI services and prompts (think ChatGPT). These allow you to connect your systems to powerful AI capabilities through simple integrations, focusing on crafting the right inputs to get the best results from existing generative AI tools.
Many organisations seeking quick wins often find that the fastest ROI comes from three approaches: in-app AI features, API-driven AI with prompt engineering and RAG. Take ChatGPT as an example. You’re leveraging an API to access a powerful language model, and the real magic comes from crafting the right prompts to get the answers you need. It’s a blend of integration and creativity that can be rapidly deployed to support everything from customer service to content creation.
Meanwhile, RAG is increasingly popular among businesses that want AI to access their knowledge bases. Think of a support chatbot that not only understands language but also uses your company’s documentation to give accurate, up-to-date responses. These approaches save time and unlock new ways to engage customers and empower teams, often with minimal setup.
3. Use the right data
Of course, AI runs on data, and not just any data. The adage holds: good data in, good data out. If your data is incomplete, inconsistent or riddled with errors, your AI outcomes will be, too.
Invest time in understanding your data landscape, cleaning up what you have and establishing robust data governance. The quality of your data will determine the success of your AI initiative.
4. Be security conscious
Security is another non-negotiable. AI systems often require access to sensitive business information and protecting that data in transit and at rest is critical.
Think about who has access, how data is stored and what safeguards are in place to prevent leaks or misuse. Don’t let a security oversight compromise your investment.
5. Use AI ethically
Ethical use is equally important. AI can amplify biases, make questionable decisions or unexpectedly affect people’s lives. Incorporate transparency, fairness and accountability from the start. Consider the societal impact of your AI applications and ensure you’re using the technology responsibly.
Remember that AI should augment your people, not replace them. The best results happen when AI automates the mundane and empowers your teams to focus on higher-value work. Think of AI as a digital colleague that makes your workforce smarter, faster and more effective, rather than one that replaces human judgment and creativity.
AI tends to give superpowers to those who are already skilled at their jobs, helping them achieve even more. For those who aren’t, AI won’t magically transform performance. It’s a force multiplier for talent, not a substitute for it.
Next steps in your AI journey
Regarding ROI, align your expectations with your use case. Are you seeking cost savings through automation, increased productivity, revenue growth from smarter recommendations, higher customer satisfaction, new business insights or the ability to scale operations more efficiently? Be realistic about what success looks like and set measurable targets so you can track progress and course correct as needed.
Don’t lose sight of the future either. AI is evolving rapidly, as are the regulations that govern its use. Build with scalability in mind so your solutions can grow with your business. Stay alert to legislative and regulatory changes and be prepared to adapt your approach as the landscape shifts.
In summary, implementing AI isn’t about chasing the latest trend; it’s about making deliberate, strategic choices that drive real business value. Start with a clear objective, focus on quality data, prioritise security and ethics and use AI to empower your people. Measure what matters and keep an eye on the road ahead.
If you’re ready to move beyond the AI hype and start building something that works for your business, let’s talk. The right strategy today will set you up for success tomorrow.
