AI fluency is the new baseline

Contents

📌Introduction 

📌What does "AI fluency" mean?

📌From competitive advantage to expected standard

📌How to prepare for this new standard

📌At SWL, we help you close the gap

Is implementing AI enough to unlock its full business value? Recent studies says otherwise. Even with the right tools, resources, and enthusiasm, most organizations still fall short. But why? ‘Cause they lack one key ingredient: AI fluency. It makes all the difference. According to Gartner, the belief that AI alone can solve business problems is still widespread. Without the skills and AI mindset to apply it responsibly and effectively, even the best tech won't deliver.

What does "AI fluency" mean?

AI fluency refers to the ability to understand, work with, and make strategic decisions involving artificial intelligence. It’s a mindset that combines basic AI knowledge with the confidence to use AI tools responsibly, creatively, and effectively in a business context. So, you need to understand what AI can do, when to apply it and how you can use it to solve real problems in your projects.

For example, imagine a customer service manager automating first-level support with a chatbot. AI fluency means they understand that the bot should handle FAQs, but escalate complex issues to a human. This helps to make the process more efficient.

From competitive advantage to expected standard

Until recently, knowing how to use AI tools, or even understanding their potential, was an unparalleled competitive advantage. How did it work back then? Forward-thinking teams that adopted AI early were able to reduce costs, work faster, and make more data-driven decisions than their peers. But all of this has changed again.

AI proficiency is no longer a desirable skill, but a basic requirement for tackling any project (and you should keep this in mind when thinking about your company and selecting and hiring talent). Just as digital literacy or basic data skills became essential over the last years, understanding how to work with AI is now part of the job description across all roles and industries (no longer exclusive to IT).

Why? Let's look at the main reasons:

• AI is part of virtually every tool used daily within a team: platforms and tools like Google Workspace, Microsoft 365, Notion and even CRM systems are up-to-date and include AI-based features by default. If your team isn't proficient in AI, you're not leveraging these tools to be more productive.
• Speed and automation are the norm: if your competitors are using AI to automate reports, generate content, or analyze data in real time, and you're not, your company will be left behind.
• AI drives strategic thinking: with the right fluency, your workforce can go beyond task automation and use this advanced technology for idea generation, risk analysis, market forecasting, and much more. This isn't just about doing things faster; it's about doing them smarter and more creatively.
• Customers and investors are asking questions: stakeholders want to know how your company is preparing for the future. AI readiness isn't just operational, it's also reputational. Being behind can affect trust and credibility.

So, the question you need to ask yourself is no longer "Should we use AI?". Instead, you should ask yourself: "Is our team ready to take advantage of everything AI has to offer?".

How to prepare for this new standard

If AI fluency is the new standard, how do you ensure your team is ready? If you don't have the answer, don't worry. We've got you covered. First, it's not about turning all your employees into machine learning engineers. No, it's about something else. The important thing is that you can create a culture where your team understands what AI can (and can't) do for your projects, and that everyone feels confident using it in their daily work.

Here are some tips on how to start building that AI-powered culture:

• Assess your current level of AI fluency: ask yourself what your teams already know about it and where they're lacking. To find out, you can conduct internal surveys, organize informal demos, or implement rapid use-case audits to identify areas for improvement.
• Invest in practical training and tools: is theory important? Yes, but your employees also need practice (and lots of it). To achieve this, offer access to practical workshops, real-world use cases, and AI-based tools. Let your teams test, fail, learn, and improve along the way. It's part of the process.
• Encourage responsible use of AI: make sure your team understands data privacy, biases, and the importance of human oversight when implementing this technology.
• Create feedback loops: allow people on your team to share what works, what doesn't, and what they'd like to try. This will allow them to improve their skills and refine internal processes.

At SWL, we help you close the gap

What you need is the ideal team to achieve AI fluency: one that's fluent, adaptable, and ready to lead with support in this technology (and future ones). At Software League, we connect companies like yours with highly qualified IT talent throughout Latin America—professionals who not only understand AI, but also know how to apply it to solve real-world business problems.

Here's how we help you bridge the gap:

• Create agile, AI-savvy teams from day one
• Save time and money by outsourcing to experts
• Access flexible talent solutions for short- or long-term projects

Don't let the AI learning curve hold your business and projects back. Schedule a call today, and let's build the best team ready for the future.