iscover Cutting through the AI hype: How to choose tools that truly deliver
TechnologyMany AI-powered tools can transform the way businesses work. While it is great to have choices, sometimes the sheer volume on offer can feel overwhelming, writes Yonatan Bley.
For many, the variety of AI tools available to them presents both opportunity and risk. The promise of AI is compelling: smarter customer service, faster admin, more time for growth. But without a clear strategy, many businesses risk spending resources on technology that adds layers of complexity instead of delivering efficiency. The result? Frustrated team members, fragmented processes across multiple platforms and a creeping sense that the “productivity revolution” has somehow made things harder.
This isn’t a reason to ignore AI. It’s a reason to approach it with discipline. Businesses don’t need every shiny new tool – they need a framework for deciding what’s worth their time and money.
1. Start with the problem, not the tool
The first question every business should ask is: What manual task do we want to eliminate? Too often, businesses purchase technology because it’s trending, not because it addresses a bottleneck. Whether it’s reconciling invoices, managing customer queries, or scheduling staff rosters, the problem should define the solution – not the other way around.
2. Pilot one tool at a time
AI tools need to be tested in real-world conditions. That means giving yourself the time and space to pilot one tool at a time and setting clear criteria for success. Is it saving staff hours? Is it reducing errors? Is it improving customer response times? By isolating trials, you create clear data to measure impact. Piloting multiple tools simultaneously may muddy results and overwhelm staff, reducing the likelihood of meaningful adoption.
3. Train staff to embed, not to abandon
A tool is only as effective as the training given to those using it. Many promising AI solutions fail, not because the technology is flawed, but because employees need more training to use them properly. Businesses need to incorporate training, not just in the initial rollout, but as part of ongoing professional development. Embedding AI into everyday processes ensures it becomes a natural part of the workflow rather than a forgotten icon on the desktop.
4. Measure and move on if it doesn’t deliver
Return on investment is a critical indicator of a tool’s value. If an AI tool doesn’t reduce workload or improve customer experience within three to six months, it’s time to move on. The beauty of today’s software-as-a-service model is that switching costs are lower than ever. Businesses should treat AI adoption as a cycle of experimentation – test, measure, refine, or replace. Businesses can measure AI effectiveness by linking tools to clear business goals (e.g., efficiency, cost savings, revenue growth, customer satisfaction) and tracking both quantitative KPIs (like error reduction, faster processing, financial outcomes) and qualitative feedback from staff and customers.
5. The bottom line
AI has the potential to supercharge businesses, but only if approached with discipline. By focusing on real problems, piloting carefully, investing in staff training, and setting clear timeframes for results, businesses can separate the tools that add genuine value from those that simply add noise. In an environment where every dollar and hour counts, this framework can help small businesses harness AI as an engine of efficiency, not complexity.
Yonatan Bley is the general manager of AI Customer Products & SME at MYOB.
