One definite shift has happened over the past couple of years: AI news has turned into a constant firehose of hype. Every month, there’s a new buzzword that dominates social media. We’ve gone from LLMs to fine-tuning, co-pilots, knowledge graphs, agents, vertical AI and then back to agents (again). Last month, it was DeepSeek. Next month, it’ll be something else.

And every time, the conversation follows a familiar pattern — Twitter, LinkedIn and news outlets light up with dramatic takes. Some claim that AI is on the verge of conquering humanity, while others declare that “it’s all over”, as if AI has already reached its peak and everything is decided.

For people with actual jobs, this non-stop cycle creates unnecessary pressure. We already know AI is transforming both personal and professional life. But here’s the thing — despite all the noise, most of us haven’t even started using AI meaningfully yet.

AI is Moving Fast, But Not That Fast

AI development is clearly faster than past technological shifts, but it’s not happening overnight. It’s been a little over two years since AI breakthroughs became mainstream, and yet, in many industries, companies are still figuring out where to begin.

Meanwhile, every new AI model release sparks another “this changes everything” moment. Take DeepSeek — when it launched, social media exploded with “it’s over” posts, some stock prices took a hit, and people rushed to make predictions. But when you look closely, even though it’s an exciting advancement, it hasn’t fundamentally changed AI applications yet.

AI Headlines Create More Noise Than Clarity

I’ve spoken to CFOs, finance VPs, and other business leaders who feel overwhelmed by all of this. They don’t know where we actually stand with AI or where things are headed. And the reality is, reading every new AI headline isn’t helping — it’s making things worse.

That’s why the best thing you can do is stop reading every AI headline. I’m not saying you should ignore AI completely. But instead of getting caught up in the hype, focus on what actually impacts your work.

If you’re in finance, pay attention to AI breakthroughs in accounting and financial automation. If you’re in healthcare, look at AI innovations in medical research. But don’t waste your time on every new model release from OpenAI, Google or whoever else unless it directly affects your industry.

Consider exploring AI-powered tools already used in FP&A, such as predictive forecasting models that improve accuracy in revenue planning, or anomaly detection systems that flag unusual spending patterns in real time. These solutions directly reduce manual effort and support faster, data-driven decision-making.

How to Focus on What Matters (Actionable Next Steps)

If you’re wondering how to cut through the hype and move toward real impact, here are a few practical ways to start:

1. Try AI tools made for finance, not general-purpose demos. Test products that automate workflows, audit trails or forecasting — anything that reduces time spent on repetitive tasks.

2. Think beyond your job title. With AI, roles are blurring. An analytics tool for the controller’s office might benefit FP&A too. Explore tech that supports broader finance functions, not just your corner of it.

3. Ignore flashy model releases unless they solve your problem. DeepSeek might be a leap for researchers, but it’s nearly useless for most finance professionals unless someone builds a real-world tool on top of it.

Less Hype, More Action

Filtering out the noise helps you think clearly. It shifts your focus beyond the headlines and into action. Instead of just reading about AI, start using it. Look for tools that can increase productivity, automate tedious tasks and improve decision-making.

As someone building AI products, I don’t have the luxury of ignoring industry developments. But even I’ve made a choice — to limit what I consume and only focus on breakthroughs that improve our products and, in general, finance.

So, do yourself a favor — choose one area where AI can reduce repetitive tasks or enhance decision-making in your Controller and FP&A process, and test a tool or approach this month.