Watch How These 5 AI Data Management Features Will Automate Workflows by 2025

Working on Cieden's AI design projects got us immersed in the topic of digital innovations. The main question was, 'How can AI transform the industry in the coming years?'. Lots of discussions and coffee brought us to start a series of videos and posts about AI concepts in software development. 

In my first post, I focus on the top six AI features to revolutionize online meeting tools. Now, I  want to share my predictions on the future of data management with its immersive AI potential.

Here is a short list of five AI data management features to lead the way by 2025.

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Two main forces drive a technology change - a technology push, driven by advancements in technology, and a demand pull, driven by consumer demand. In your approach to integrating AI into your product, bridge these forces and ensure that AI, as a technological advancement, will add value to the product (technology push) and effectively meet and anticipate user needs (demand pull).

Autofill of data

Imagine a once labor-intensive task simplified to a few clicks, all thanks to AI. A single automatic function will substitute dozens of processes. But more importantly, it will give a great speed boost to workflows.

AI autofill will be a must-have feature for any industry striving for CMS or CRM automation due to data extraction and cleansing. For more precise analysis, AI will be able to read diverse formats like text, PDFs, or images. Finally, it will learn to fix inconsistencies between sources to avoid potential autofill errors.

Additionally, AI in data management will help users reduce the costs of cutting poor-quality data. Currently, it can save organizations up to $13 million annually. Beyond making money, autofill will be crucial in industries that focus on people. By 2025, it will guarantee perfect accuracy in diagnosing and treating patients.

Descriptions generation

In the next two years, AI will get better at writing product and service descriptions. It will use data to make the language fit specific audiences keeping descriptions more human-like and diverse.

The driving force behind this concept is more advanced generative patterns. They tap more into emotional-resonant content based on the needs of your target audience. One more success parameter is a sophisticated AI algorithm. It has to do with Enterprise Data Catalogs (EDCs) and smart data modeling. Both stand for the reliability, accuracy, and relevance of information. It also ensures the data environment is well-prepared and optimized for AI applications. 

An advanced AI system helps save hours on extensive brainstorming and manual writing. Meanwhile, AI descriptions get even more tailored and impactful.

AI-assisted calculations

Embracing data management automation minimizes the chance of human error. 

For this reason, I enjoy working with AI-assisted calculations. They can alter user perception of financial operations within your CRM. Instead of manual input, a user describes what they need to do as a text. Then, an algorithm generates and solves this formula on its own.

AI calculations can solve complex patterns hard to handle by the smartest human brain. What you’ll see is a user-friendly tool equipped with advanced algorithms. Meanwhile, the math part will stay behind the scenes.

Data unification

The fourth trend to automate data management with AI is unification. The prime goal of unification is to standardize data types, be it measurements, dates, or phone numbers. Yet, from what I see, the real value of data unification lies in personalizing user experience.

Model adaptivity made AI assistants like GPT-4 the most talkable phenomenon in 2023. They can dive into the context of a text to uncover its deeper meanings, something that AI couldn’t do before. Soon, every advanced software system will learn to do the same. Unification will help recognize and adapt to new formats, user behaviors, and market trends.

Beyond that, automated unification will act as a data guardian in complying with regulatory standards and policies. Consider it an investment in a more healthy and robust digital landscape.

Data visualization and explanation

AI data visualization makes it easy for users to perceive the deepest insights of software data. It shows a pivotal trend applicable across various industries. 

In a couple of years, users will be able to visualize data from easy text instructions. This implies a few essential steps:

• pulling the necessary info;
• designing a user-friendly layout;
• giving clear insights and next steps;
• picking the best way to visualize your insights;
• suggesting extra widgets to expand the dashboard.

Smart algorithms will be able to visualize deeper insights while promoting better business decisions. They will recognize trending patterns and promote data-driven decisions.

The AI’s impact on UX/UI shapes a future with new standards of data management. The leading positions will go to autonomous, and self-optimized solutions with automated management approaches. For this reason, investing in AI data management today is a strategic bet for tomorrow's UX success.

To delve deeper into these transformative trends, subscribe to Cieden's YouTube channel. There, we share our videos on AI concepts, offering insights that can guide your strategic decisions in AI investments.