5 myths and truths about AI for companies

May 31, 2024 Roberto Magalhães

Uncover the myths and truths surrounding AI for businesses. Explore the real-world impact, benefits, and challenges of implementing AI technologies.

In recent years, mentions of artificial intelligence (AI) on technology news portals have reached an all-time high. From new uses to its impact on the future of business, the number of articles about AI has multiplied to the point that it practically dominates the landscape. However, it is not surprising: AI has tremendous potential, and some of it is starting to crystallize.

Unfortunately, having so much information about AI also means there are a lot of myths and exaggerations out there. In fact, many companies are still studying their AI adoption plans due to misinformation they find online or stories of failure around AI plaguing the internet. This is why it is important to clarify certain aspects of AI. On the one hand, it allows companies to make more informed decisions. On the other hand, it encourages them to start their AI journey with greater optimism.

Here are five of the most widespread myths about AI – and the truths they hide behind them.

1. You need to adopt the most sophisticated AI

AI's capabilities grow with each passing month, so it's natural for companies to think the solution to all their problems lies in the latest, most sophisticated iteration. It makes sense: powerful AI must be able to handle large amounts of data from multiple sources, deliver fast and relevant insights, and adapt seamlessly to all systems. That's why companies want this sophistication.

The truth: While mature AI can do all of this (and more), the reality is that adopting sophisticated AI is not plug-and-play. You need to develop more basic AI solutions until you reach a level of maturity that can cover all this ground. Plus, you don't necessarily need the most sophisticated AI out there. Maybe your technological challenges are easily solved with a more basic AI algorithm, so you shouldn't always look for the fanciest alternative out there.

2. The AI algorithm needs to be customized

The benefits of using a customized solution are many, but mainly there is the certainty that it will be perfect for the challenges that the company is trying to solve with its implementation. This reasoning also applies to AI, which is why so many companies are thinking about investing in custom algorithms to ensure they get the most out of this technology.

3. Building the AI is the hardest part

Creating a working AI solution is a difficult task. This is because the team needs in-depth technical knowledge, a high level of creativity and considerable business experience to arrive at an application capable of meeting different needs. This is why people believe that once AI development is complete, you can sit back and relax while the AI starts to provide value on its own.

The truth: There is no “sit back and relax” phase when it comes to AI development. This is because AI needs constant attention to evolve and become a more sophisticated and valuable solution. Of course, you will encounter many challenges when building an initial AI solution, but you will quickly realize that there is no way to relax here, as AI development requires constant improvements and multiple iterations to provide real value. So building the AI isn't the hardest part, mainly because you'll never stop building it.

4. You only need a few experts to build an AI

When strategizing about AI development, many business owners close their eyes and think about hiring a few engineering rock stars who can handle the entire project with minimal input. Perhaps this engineering talent will only need input from a data scientist at some point in development, but using preexisting AI solutions and their own experience, a few senior AI developers could easily work on and deploy an AI solution.

The truth: It's strange that we have to clarify this, but developing an AI solution involves more than just the ability to assemble the algorithm through code. As with all development projects, creating an AI solution requires a combination of technological skills, business acumen, management capabilities, and vision. It's true that software engineers can have all of these things, but reality shows that you can only achieve all of this by working with a capable team that has multiple roles and a clear leader who can move the work forward.

5. Everyone needs to implement AI as much as possible

Some people say that we already live in the age of AI. Therefore, there is a growing push for companies to start adopting AI now or risk falling behind and reaching a point where they may never recover. The reasoning behind this is simple: when some companies start using AI, they start to enjoy new capabilities that put them well ahead of everyone else. Therefore, to stay in the race, you need to implement AI as much as possible or risk disappearing in the face of advances in AI-driven companies.

The truth: You don't necessarily need to reinvent your entire process to accommodate AI. Instead, try to start applying AI where it can immediately protect the bottom line, such as using a chatbot to help with customer support or integrating AI into your CRM to sort and filter incoming communications. Starting small and building incrementally is the best possible approach to making the most of AI, especially because it prevents you from investing too much in a solution that may not make a difference to you.

Planning for AI, beyond the myths

The first step to successfully implementing AI in your organization is to truly understand everything about this technology. This involves understanding the potential of AI, its limitations, and how it can truly benefit you in particular. There is a lot of excitement around AI, so this learning process is highly important for planning a valuable AI solution for your business challenges.

If you liked this, be sure to check out our other articles on AI.