Artificial Intelligence (AI) is the hottest buzzword in business right now, and it seems like everyone’s jumping on the AI bandwagon. But let’s be clear, don't adopt AI just because it’s trendy. That would be like buying a treadmill and using it to hang clothes—sure, it’s technically being used, but it’s not doing what it was designed to do. AI should be more than just a flashy tool in your tech stack. If it’s not actively solving problems and contributing to your bottom line, it’s just a very expensive (and very complicated) showpiece.
AI’s real power lies in its ability to solve actual business problems, remove bottlenecks, and increase overall efficiency. If your AI isn’t doing those things, you should absolutely be asking, "Why are we using this, again?"
AI Needs to Be Tied to Outcomes, Not Optics
Let’s start with the most important point: AI must be tied directly to measurable outcomes that contribute to your company’s success. This goes beyond vague improvements like “streamlining processes” or “enhancing innovation.” Those phrases sound great in meetings, but what do they actually mean? If AI isn’t directly boosting profitability, reducing manual labor, or enhancing customer engagement, it’s missing the mark.
For example, using AI to reduce customer service wait times by 30% is a measurable outcome that can improve customer satisfaction and reduce churn. Using AI to automate invoicing can save thousands of hours of manual work, which cuts costs and lets your team focus on higher-value tasks. These are the kinds of results you want to see—clear, tangible benefits that align with your business goals.
Focus on Solving Constraints to Boost Throughput
When getting started with the implementation of AI, you should ask: “What’s the biggest constraint in our process, and how can AI solve it?” AI should be used to unblock workflow bottlenecks that slow your business down. That could mean reducing manual data entry in finance, automating customer support queries, or even predicting supply chain disruptions before they occur.
AI can be the tool that greases the wheels of your workflow. Identify the biggest friction points in your process—those areas where productivity grinds to a halt—and use AI to address them. Is your sales team bogged down in manual CRM updates? Automate it. Are your IT resources tied up in repetitive troubleshooting tasks? Deploy AI-powered bots to take over. The goal is to free up your human talent for work that drives revenue and growth.
It’s About the Results, Not the Speed
A common mistake businesses make is tracking how fast their AI system works rather than measuring its real impact. Don’t get lost in the vanity metrics—like how quickly an AI tool processes data or completes a task—if those actions aren’t making a difference where it counts. What matters is whether AI is boosting profitability, increasing customer retention, or reducing operational costs.
Let’s say you implement an AI-powered chatbot to handle customer queries. Great, it responds to questions faster than a human, but if customers aren’t more satisfied or if the AI’s responses aren’t accurate, what’s the point? The metric that matters isn’t how fast the bot works; it’s whether the bot enhances the customer experience and, in turn, reduces churn. The ultimate question should always be: Is this AI system helping us achieve our core business goals?
Continuous Evaluation: AI Needs a Regular Performance Review
AI isn’t a set-it-and-forget-it solution. Just like any other business process, AI needs to be regularly evaluated to ensure it’s driving the expected results. If it isn’t, don’t just shrug and assume it’s doing something. Revisit your initial goals and figure out why it’s not hitting the mark. Maybe the problem lies in how the AI was trained, maybe the data sets are incomplete, or maybe the wrong problem is being solved. Whatever the reason, treat your AI with the same scrutiny you’d apply to any other investment.
Encourage teams to conduct regular reviews of AI performance metrics. This is not just about tweaking the system but understanding whether AI is evolving in step with your business needs. If the AI is working perfectly but business priorities shift, the AI needs to adapt accordingly. And sometimes, it’s okay to admit that a particular AI implementation isn’t working and needs to be adjusted or even scrapped altogether.
AI Shouldn’t Be a Shiny Object
At the end of the day, the biggest mistake a company can make is implementing AI just because “everyone else is doing it.” AI should never be about chasing trends. If it’s not solving a real business problem, it’s just another shiny object that consumes resources without delivering real value.
Before diving into any AI initiative, ask yourself:
What’s the business objective we’re trying to achieve?
How will AI help us reach that goal faster, cheaper, and/or more efficiently?
How will we measure the success of the initiative?
If you don’t have clear answers to these questions, hit pause. AI, for all its potential, is only as good as the strategy behind it. Without a clear, goal-oriented implementation, it risks becoming a costly distraction.
The Takeaway: AI Should Work for You, Not Just Impress You
AI is a powerful tool, but it should never be used to just check a box. Its real value lies in its ability to solve constraints, boost productivity, and contribute to your company’s core objectives. If you’re considering implementing AI, make sure it’s tied directly to measurable outcomes. Focus on solving bottlenecks and inefficiencies, and don’t get distracted by how fast it works—focus on how well it solves the problem.
And remember, if AI isn’t delivering the expected results, don’t be afraid to pivot. Like any other business process, AI should be continuously evaluated and adjusted to meet changing needs. So, go ahead—let AI do its job as a problem-solver, not a showpiece.