For about as long as technology has existed, people have been using it to record and manage data in one way or another. Then as now, handling data effectively is important because of the limits of human memory and cognition. Having technology do the work of “remembering” became especially crucial as civilisations engaged in more complex practices. As data sets became larger, there came an increased need to handle them and interpret the abstractions they contained. Thus, organisations developed a need for effective data management that continues to this day.
In the present, the enterprise data collected by large enterprises and other organisations has become all but inseparable from serious decision-making processes. However, human fallibility still plays a role in the quality of major decisions, with undesirable outcomes still commonplace despite the impressive amount of technology that is now leveraged to minimise risk.
Things are already set to change. Recent developments in artificial intelligence (AI) are set to completely transform how businesses handle their data. Though some forms of AI have been used in decision-making in the past, the sheer depth and sophistication of current AI models are proving to be a boon for businesses and other organisations. Here are some ways that next-generation AI is changing enterprise data management as it is understood.
1. Better Analysis and Decision-Making
Traditional data analysis can be time-consuming and mentally exhausting, leading to potential oversight and errors. AI alleviates this burden by rapidly processing vast amounts of data, identifying trends, and generating insights that might be missed by human analysts. Human analysts can then take on a monitoring and oversight role, ensuring the AI remains aligned with business objectives.
Importantly, because AI algorithms aren’t constantly burdened by human biases, they also excel at recognising non-intuitive patterns within data sets. These algorithms can continuously learn and adapt, enhancing their effectiveness over time. By identifying subtle patterns and trends, AI can provide human decision-makers deeper insights as well as completely new perspectives that would never occur to most humans.
2. Accurate Predictive Analytics
Aside from providing basic analyses, some AI products offer sophisticated predictive analytics to forecast future trends based on both historical data and context. With proper data hygiene, AI can be configured to predict outcomes with a high degree of accuracy. This usage is already commonplace in sectors such as finance, healthcare, and retail since external trends tend to have a strong impact on these sectors.
3. User-Friendly Data Visualisation
Because not everyone can easily interpret the abstractions represented by raw numbers, good data visualisation remains essential when communicating with human stakeholders. However, creating visualisations is a complex skill in itself, which often limits the ability of users to effectively share the implications of a given data set.
With AI tools, anyone who needs to build a data-driven case can create sophisticated visual representations of data, including interactive dashboards and detailed charts. This enhances comprehension and makes it easier for stakeholders without a data management background to understand and act upon critical information.
4. Automated Data Entry and Management
AI-driven automation is already being used to facilitate routine tasks like data entry and validation. When coupled with human monitoring, AI automation can also ensure that entries within a database are accurate and up-to-date, improving the quality of decisions and arguments based on the data.
5. Proactive Data Security
Major government and financial institutions already use AI to identify and mitigate potential cyber threats in real time. Machine learning algorithms can detect unusual patterns of behaviour that may indicate a security breach, allowing organisations to respond swiftly and prevent data theft or loss. This proactive approach greatly reduces the workload of limited cybersecurity personnel and helps organisations maintain a credible security posture in the face of mounting cyber threats.
6. Optimised Supply Chain Management
AI is transforming supply chain management by providing managers with real-time visibility and insights into every stage of the process. From predicting demand and managing inventory to optimising delivery routes, AI helps businesses streamline their supply chains and stay relevant in today’s globalised economy.
7. Personalised Customer Experiences
For years, AI has been empowering businesses to deliver personalised experiences based on individual preferences and behaviours. This usage is especially notable on e-commerce sites, where AI is frequently leveraged for targeted marketing campaigns and better customer satisfaction. As a bonus, businesses that use AI in this way can also enjoy lower sales costs and stronger customer loyalty.
8. More Innovative Product Development
Finally, AI usage is already leading to an emphasis on data-driven innovation within organisations. By letting AI handle the minutiae of day-to-day business, human stakeholders are freed from doing busywork and can, instead, focus on creating meaningfully improved products, services, and business models. When guided by decision-makers who understand the limits of AI, businesses can effectively leverage the advantages offered by their human capital alongside their new AI investments.
How Will AI Shape Success in Your Organisation?
AI is transforming enterprise data management in profound ways, offering businesses and other organisations better ways to serve their stakeholders. As AI technology continues to evolve, its impact on enterprise data will only grow, opening up new opportunities for organisations worldwide. Soon, understanding how to wield AI effectively will become a key factor in driving success across all industries.
