Amid the buzz surrounding artificial intelligence, many business owners remain understandably cautious, questioning whether AI is more hype than help. It’s unsurprising—we’ve all seen technologies come and go, promising transformation but delivering little value. AI, for many, feels like another such promise: costly, complex, and often irrelevant to their specific industry. However, a practical approach focused on small-scale experimentation can yield significant benefits without overwhelming investments.
The Case for Small-Scale Experimentation
The key to unlocking AI’s potential lies in starting small. Large-scale deployments can be intimidating and fraught with risk, but smaller initiatives can deliver significant returns at minimal cost. The beauty of AI today is that it’s more accessible than ever, offering entry points for businesses of all sizes. A small investment can lead to automation that saves hours of work or provide insights that reshape a business process.
Small-scale experimentation doesn’t mean a slow approach either. Tools like ChatGPT allow businesses to test and iterate quickly, and can be the first step to larger implementations. Companies should encourage their staff to use ChatGPT in their day-to-day roles. As employees experiment with ChatGPT, they will start finding efficiencies in their work— drafting customer responses faster, automating routine calculations, or generating reports more efficiently. Companies should then closely monitor how staff use ChatGPT to identify further opportunities for automating these tasks. Once a valuable use case is identified, it can be transformed from a manual process into a fully automated AI-assisted business process, thus beginning their first steps into AI integration.
Moving from Experimentation to Implementation
Once a process has been identified as a candidate for automation, the next step is to implement it in a more integrated and scalable way. Low-code platforms like Microsoft Power Platform provide an excellent solution for quickly transforming a manually executed ChatGPT workflow into a semi or fully-automated system. These platforms are designed to be user-friendly and enable businesses to create internal applications without needing expensive, time-consuming software development projects.
With low-code solutions becoming increasingly common, even in larger corporations like hospitals, banks, and major companies, businesses can take an identified manual task and automate it rapidly. For example, after using ChatGPT to detect anomalies in customer orders, a company could use Power Automate to create an automated workflow that automatically checks customer orders as they come in. This approach allows for rapid deployment, testing, and refinement—all while avoiding the high costs and extended timelines associated with traditional software development.
This approach allows you to focus on incremental improvements. Start with automating one small, manual process, and once the benefits are clear, expand gradually. This step-by-step approach minimizes risk while continuously building AI-assisted efficiencies. Businesses that adopt this pragmatic approach are well-positioned to harness AI’s value effectively without the chaos and disruption that larger implementations can bring.