Identifying the right processes for AI

Before anything else, decide on the specific domain or area of your business where AI can make the most significant impact. Whether it’s finance, claims, underwriting, customer service, supply chain, payroll or HR, selecting the right domain is crucial. Consider where the most pressing challenges or the greatest opportunities lie. This will set the stage for a focused and effective AI strategy. Think about areas where there are high volumes of data, repetitive tasks, or where decision-making could benefit from AI’s predictive power. By narrowing your focus to a particular domain, you ensure that your AI efforts are targeted and manageable.

Once you’ve chosen the domain, take a good, hard look at your existing workflows within that area. Are they efficient? Are they standardised across the board? And most importantly, is your data in good shape? AI thrives on high-quality, structured data, so if your processes are a mess, AI isn’t going to save the day—it might even make things worse. Start by reviewing your workflows and identifying any bottlenecks or inefficiencies that need fixing before you even think about bringing AI into the mix.

Not every process within your selected domain is suitable for AI integration, and that’s okay. The best candidates are those that align with the stages of your own AI journey:

• basic automation: start with repetitive, rule-based tasks that can be easily automated using tools like Robotic Process Automation (RPA)
• enhanced data processing: next, consider processes where machine learning can add value, such as predicting outcomes or identifying anomalies
• advanced decision support: look for opportunities where cognitive computing can support complex decision-making, helping you move beyond simple automation to strategic insights
• process optimisation: identify workflows that could benefit from AI-driven process mining and optimisation algorithms to streamline operations
• strategic transformation: finally, consider processes that, when integrated with AI, could transform your business strategy in real-time.

AI can bring tremendous value, but it’s not without its risks. Before you go all in, conduct a risk and benefit analysis. What are the potential gains in efficiency, accuracy, and cost savings? And what about the risks—like data privacy concerns, compliance issues, or the potential for introducing bias? This step corresponds with the guardrails in your AI journey, ensuring that as you move forward, you’re mitigating risks and maintaining alignment with your business goals.

AI is powerful, but it’s still only as good as the people who use it - human judgement is still required in many sectors. As you identify processes for AI integration, think about the human element. How will this change impact your team? Will they need new skills or training? This reflects the importance of people in the AI journey—ensuring that your team is ready and able to work with AI tools, and that they’re part of the transformation process from the start.

Once you’ve identified a few processes that are prime candidates for AI, it’s time to prioritise. Start with the processes that offer the most significant potential impact for the least effort. This might align with the early stages of your AI journey—like basic automation or enhanced data processing—where quick wins can build momentum for more complex AI implementations down the road.

As you embark on your AI journey, it’s crucial to establish guardrails to keep everything on track. These include setting clear objectives, defining success criteria, and implementing oversight mechanisms to monitor AI’s performance. Guardrails are critical in every step of your AI journey, ensuring that your AI initiatives are ethical, compliant, and aligned with your strategic goals.

Sometimes the best way to understand AI’s potential is by looking at how others have done it. Consider case studies where businesses have successfully integrated AI into their processes. These examples can help you see how AI, at various stages of its journey, has been applied to real-world challenges—offering insights and inspiration for your own AI roadmap.