AI is everywhere right now. It’s the centerpiece of board slides, investor pitches, and product updates. Fair enough, some of these tools do help people work smarter. Things move quicker. Teams get more done.
But for all the talk about AI, the potential of this technology is often wasted because the output isn’t useful and businesses fail to harness its power the right way. After the big plans and bold promises, it’s all rather underwhelming.
The problem of bad data
One reason for this is because it’s working with bad data. Disjointed data that’s full of gaps. AI will only ever be as good as the data it ingests – it amplifies what it’s fed.
And there’s another common problem. Even if AI output is good, useful insights aren’t reaching the right people in time. That’s because you either need a PhD in data science to understand what it’s telling you – or wait for a business intelligence specialist to build graphs and widgets, and present the data in a readable way. And by that time, it’s too late.
So, if you’re chasing genuine, sustainable transformation, don’t skip the groundwork. There are two things that you must do. First, get your data foundation in order. Then, create an AI layer that gives teams real-time, actionable insights in a language they understand – and allows them to talk back.
Talking back
What does this look like? Imagine a workplace where every member of the team—regardless of technical knowledge—can explore data-backed insights, make smarter decisions, and drive real impact. That’s what democratizing your data can achieve and here’s how you do it.
Connected systems
Your data can’t live in isolation. Sales, marketing, finance, and operations feed into one another. You can’t expect alignment if your teams don’t have access to the same information because you’re just managing silos and creating bottlenecks. Get everything to talk to everything else. That’s step one.
Clean, reliable data
This is the unglamorous part, but it’s critical. Data has to be accurate, up-to-date, and consistent. That doesn’t happen by accident. It takes ownership, good processes, and yes — the occasional painful cleanup project. But once your people start trusting the numbers, everything else moves faster.
Accessible, understandable output
Data should be a tool for teams – not a challenge. Static dashboards and delayed reports stand in the way of actionable insights. But interactive, natural language interfaces make data accessible to all. Teams must be able to ask questions and get instant answers with clear data visualizations. AI has the potential to reshape traditional data analytics by moving beyond static dashboards and delayed reports to real-time, intuitive dialogue.
Scalable infrastructure
You’re not just solving for today. You’re building for next year, five years from now, ten. Your data stack needs to flex with your business. You should be able to plug in new tools, markets, and teams without tearing everything down.
Less empty talk, more productive chats
Once these fundamentals are in place, AI can do what it’s meant to: lift, accelerate, unlock. That’s when the magic starts to feel real — when reporting evolves from a slow, siloed task into a dynamic, business-wide conversation.
Experiment. Test tools. Move fast. That’s how innovation happens. But remember that it’s what’s under the surface that matters. AI is definitely a driver of transformation but, without a solid data foundation, it can only ever get you so far.
But also bear in mind that good output will be wasted if it’s opaque. It’s vital that teams can understand and interrogate the insights that AI surfaces. Getting the most from data and AI requires a two-way conversation.
Get this right and you will see the true potential of AI and the impact it can have on your business in building a data-driven culture.
This article was produced as part of TechRadarPro’s Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro
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