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Before you jump on the artificial intelligence (AI) bandwagon, take a step back and think about your organization’s data. Is it squeaky clean, well-organized, and ready to fuel the AI engine? Just like a top chef needs the best ingredients to whip up a Michelin-star meal, AI needs high-quality, structured data to work its magic. So, let’s get real: Is your business data up to scratch? Is it consistently formatted, error-free, and easily accessible across your organization? Or is it a hot mess of inconsistencies and missing pieces?
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Many organizations are struggling with data that’s nowhere near ready for AI. We’re talking data silos, ancient legacy systems, sloppy data entry, and a serious lack of data governance. It’s no wonder that data ends up isolated, hard to find, and a nightmare to work with. In fact, Keypoint Intelligence’s Multi-Client Study on automation found that 25% of respondents hit roadblocks with their infrastructure when implementing robotic process automation (RPA). If that doesn’t scream “data management issues,” I don’t know what does.
For organizations looking to adopt AI, the state of their data can be a major headache. You’re excited about the possibilities, but then you realize your data is all over the place. Suddenly, you’re faced with the daunting task of cleaning, integrating, and maintaining your data. Using our metaphor above, it’s like trying to cook a gourmet meal with ingredients scattered across different kitchens—not exactly a recipe for success.
The Solution Provider’s Perspective
As a solution provider, you play a crucial role in helping organizations embark on their AI journey. However, the reality is that it’s not always a straightforward process. You often encounter clients whose data is inconsistent, incomplete, or poorly organized. It falls on your shoulders to take on the challenge of whipping their data into shape and educating them on the significance of maintaining high-quality data. It’s a demanding task, but it's essential for the success of any AI implementation.
There are ways to tackle these challenges head-on:
- Get your data governance game on-point
- Invest in some slick data integration tools and platforms
- Automate the heck out of your data entry and processing tasks
- Keep a watchful eye on your data quality and keep improving it
- Find an experienced solution provider to help you out (if you’re a buyer) or be that qualified provider
The same study reveals some stunning statistics that underscore the magnitude of the data challenge. Over 80% of respondents reported that at least a quarter of their business data is unstructured, while more than 40% acknowledged that over half of their data lacks proper organization. These findings serve as a powerful reminder of the urgent need to prioritize data management and tackle the issues posed by unstructured data head-on.
Keypoint Intelligence Opinion
Clean, organized data is the foundation of successful AI implementations. Without it, even the most advanced AI technologies will struggle to deliver meaningful results. The significant amount of unstructured data in organizations, as highlighted by our research, emphasizes the critical importance of addressing data management practices and getting your data in order.
To conquer these obstacles, organizations need to invest in the right strategies and partnerships. Take a long, hard look at your current data situation; figure out where you can improve; and make a game plan. And don’t be afraid to call in the big guns—experienced solution providers who know their stuff and have the tools to get the job done.
Prioritizing data management is no longer a nice-to-have—it’s a must-have. By understanding the challenges, investing in the right strategies, and teaming up with top-notch providers, organizations can unlock the full potential of AI and drive some serious business wins. The clock is ticking and the future of your success in AI is on the line. It’s time to act now!
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