AI Shouldn't Just Help Us Do More. It Should Help Us Lose Less

Lately, it seems like every company needs to talk about artificial intelligence. 

The question is: How are we using AI in our businesses? But I believe we are asking the wrong question. 

For me, the real question to ask is: What problems in our companies can we detect before it costs us money?

I run a performance marketing company, and one of the things I've learned over the years is that, in business, the problem often isn't making a mistake. The real problem is how long it takes for us to realize we are making one. 

A campaign's costs may start to rise, customer conversion rates may drop, a sales team might take too long to contact leads, a metric may begin to drift off course little by little, and so on. 

At first, maybe nobody will notice, then the reports arrive, and someone analyzes the results. Then a meeting is scheduled; there is a discussion about what happened, and decisions are made. And while all of this is happening, the company keeps losing money. For me, that's where one of the most interesting applications of artificial intelligence and automation can be used. 

At CleverClick 360, we operate under a shared-risk model. Our clients pay us for every lead we generate, but our work doesn’t stop there. We work towards a specific CPA target and get involved at various stages of the funnel to help ensure those leads actually convert into sales. This means that if something goes wrong, we also assume part of the risk. 

This is why, several years ago, we began developing technology, automation, and data analysis systems that would allow us to detect problems faster. Not because we wanted to claim the use of artificial intelligence, but because we were losing money. And I believe this distinction is important. 

Many companies are adopting AI because they feel they have to. They buy tools, sign up for platforms, and automate processes without being entirely clear on the problem they are trying to solve. So we did it the other way around; first, we had a problem, then we looked for a solution. 

For example, we manage campaigns across various platforms and countries. A person can constantly review the results, but there is a limit to the amount of information we can process. A system does not have that problem. 

That is why we developed bots capable of monitoring costs, detecting deviations, and generating alerts when something begins to fall outside the established parameters. It might seem simple, but let's think about the difference.

If a campaign starts spending abnormally in the middle of the night, we don't need to wait for someone to arrive the next day, open the platform, spot the issue, and decide. The system can detect it sooner and stop the loss. To me, that is one of the true values of automation. Not necessarily doing more, but losing less.

However, I do not believe in handing over all decisions to artificial intelligence, either. Technology can analyze millions of data points, identify patterns, and detect anomalies much faster than we can. But it still requires something fundamental: judgment. A system can tell you that something has changed. A person needs to understand why. 

That is why our understanding of technology is quite simple: technology detects, automation contains, and people decide. I believe this principle can be applied basically at any company. In finance, we can detect deviations in expenses or margins. In sales, changes in conversion rates or response times. In operations, processes are beginning to lose efficiency. In human resources, patterns related to turnover, performance, or training needs. The possibilities are enormous. 

But before thinking about artificial intelligence, I believe we business owners should ask ourselves much more fundamental questions: Which indicators really matter for my business? How long does it take me to detect a problem? Which errors keep recurring? Where am I losing money? Which decisions am I making too late? 

The answers to those questions are likely more valuable than any list of artificial intelligence tools. Because technology alone doesn't fix a company. If you have disorganized processes and automate them, you will simply end up with disorganized processes running faster. If you have bad data and use artificial intelligence to analyze it, you will reach wrong conclusions at a faster pace. 

And if you don't know what you want to measure, having more information will likely just create more noise. For me, one of the biggest lessons learned while developing technology at CleverClick 360 has been understanding that AI needs to have a deep understanding of the business. Our systems work because they are backed by years of experience running campaigns, analyzing results, making mistakes, and learning from them.  

Technology didn’t replace that knowledge; it turned it into systems, and I believe there is a giant opportunity there for companies. Every business accumulates knowledge; people know how to spot problems, teams develop ways of working, and leaders learn to recognize certain signals. 

The problem is that much of that knowledge lives only in people's heads. What if we started turning it into systems capable of observing, learning, and reacting? I think that's where a much more interesting conversation about artificial intelligence begins. Not about how many tasks we can eliminate, but about how much knowledge we can leverage. 

At CleverClick 360, we also work with Data Analytics, Machine Learning, and Business intelligence teams to cross-reference campaign information with client data. Because a low CPL doesn't necessarily mean a campaign is working.  You might generate many leads at a great cost, only to discover later that none of them are buying. 

If you only look at the advertising platform, you'll probably think you did a fantastic job. If you look at the business as a whole, the conclusion might be entirely different. 

That is why I believe one of the major changes artificial intelligence will bring is forcing us to connect information that we previously analyzed in isolation. 

• Marketing 
• Sales 
• Operations 
• Finance 
• Customers 

Everything is part of the same system. 

And the faster we can identify what is happening within that system, the better decisions we can make. I do not believe that artificial intelligence will replace entrepreneurs, leaders, or teams. However, I do believe that companies that learn to detect their problems faster will have a huge advantage over those that continue to manage their businesses by looking only at what has already happened. 

For many years, we ran companies by looking at past reports: what we sold, how much we spent, what worked, and what went wrong. Artificial intelligence gives us the opportunity to start looking in a different direction: what is changing, what is veering off course, what could go wrong, and where we should intervene sooner. To me, that is the real shift. It's not about having a company filled with artificial intelligence. It is about building a company that learns faster. 

Because, ultimately, the greatest competitive advantage probably won't be who has the most technology but will be whoever can realize first that something is changing and has the speed to do something about it.