2024 Predictions for Data Management, Data Discovery and Cybersecurity

This year will be a pivotal one for data management, data discovery and cybersecurity. The industry faces new challenges and opportunities arising from the rapid development and adoption of artificial intelligence (AI) amid a difficult global economic climate affecting budgets and resources. Meanwhile, new laws and regulations governing privacy, data security and AI technologies are expected as clients and consumers place increasing demands on businesses for data privacy and security.

In this blog post, we share our predictions of the trends, technologies and practices that will shape these domains in the year ahead, based on our own opinions and insights.

Increasing Investment Amid Rising Regulatory Pressure

In 2024, inflation will become accepted as the norm in many countries forcing organizations to recalculate budgets based on prevailing costs of tools, services and resources. As a result, we expect to see increased investment in compliance and cybersecurity. This will be necessary as cyber-threats increase and organizations’ attack surfaces grow due to increasingly fragmented networks, expanding data generation and consumption, and the continued adoption of SaaS services as part of standard business technology portfolios.

In addition, the complexity of the data protection and privacy legislation landscape will continue to expand around the world, particularly in the Asia-Pacific region. In this region, several countries are adopting and enforcing new laws and regulations. Businesses operating under these rules will be obligated to comply with new requirements that diverge from those in more established markets. Legislation in this region typically has a stronger focus on data sovereignty and data localization compared to other equivalent regulation, such as the EU GDPR, with potential implications for the free flow of data in the global economy if strictly enforced.

AI-Driven Cybercrime Forcing Rapid Legislative Change

In 2024 we’ll see increasing focus on the risks and opportunities associated with artificial intelligence (AI). AI has become a ubiquitous and powerful tool for data analysis, decision-making and automation, but presents new challenges for data sovereignty and security. 

One of the main challenges in this area is the lack of regulation and oversight of AI systems and applications, especially in terms of their ethical, social and legal implications. Currently, there are no global frameworks for governing AI, and many AI systems and applications operate in a black box, without transparency or accountability. We’ll see cases emerge in which the use of AI by organizations harms consumers, resulting from bias, discrimination or manipulation, as well as cyber-attacks initiated using purpose-built AI systems.

However, we do expect to see governments accelerating their efforts to regulate and monitor AI, and to impose new rules and obligations on AI developers and users. For example, the EU’s Artificial Intelligence Act (AIA), which is expected to be adopted in 2024, will introduce a risk-based approach to AI regulation. Similar legislation will be enacted in the US and Canada, and across other global regions.

These regulations will have a significant impact on data management and cybersecurity, as they will require AI systems and applications to be more privacy-aware, secure and trustworthy. AI systems and applications will need to ensure that they collect, process and store data in a lawful, fair and transparent manner, and that they respect the rights and preferences of individuals. They will also need to ensure that they protect data from unauthorized or malicious access, use or modification, and that they prevent or mitigate any potential cyber-attacks or data breaches.

Automating Cybersecurity to Overcome Complexity

Another key trend that will affect data management and cybersecurity in 2024 is the increased automation of cybersecurity processes using software-based tooling. This will further increase the practice of data sampling versus full data audit. These trends are driven by the need to address the staff shortfalls and skills gaps in the cybersecurity industry, as well as the need to cope with a massive and complex data landscape.

Cybersecurity automation is the use of software tools to perform or assist with cybersecurity tasks, such as data identification and classification, data management, risk management, and threat detection, response and remediation. Cybersecurity automation can help improve the efficiency, effectiveness and scalability of cybersecurity operations, essential for cash-strapped organizations. 

In 2023, we’ve seen organizations taking steps to implement data management to help them meet regulatory, legislative and cybersecurity obligations. Data sampling uses a subset of data from a larger data set to draw conclusions or make decisions about the whole data set. It can help reduce the time, cost and complexity of data analysis; however, data sampling has its limitations — particularly for the purposes of privacy compliance and data security — since vast quantities of the wider dataset are not evaluated, meaning there is a very real potential for missing sensitive data that needs additional protection.

In 2024, we expect to see more organizations adopting cybersecurity automation and data sampling, as they seek to optimize their data management and cybersecurity processes and outcomes. However, it is important businesses are aware that these practices should not be considered as a substitute for full data audits for privacy compliance and data security, where the comprehensiveness of the discovery and data management process is essential.

Accelerating Data Proliferation and AI Data Mapping

We expect to see continued data proliferation through expansion to the cloud as businesses seek cost-savings and operational agility. While the cloud offers greater scalability, flexibility and accessibility of data storage and processing for organizations, it also introduces new risks and complexities for data management and cybersecurity, such as the loss of visibility, control and governance of data. 

The ease of access to cloud services also enables the creation of shadow stores and environments; data repositories or systems that are created or used without the knowledge or approval of the IT or security departments. These factors can leave businesses unknowingly exposed to cyber-attacks or data breaches. 

In 2024, we expect to see more organizations leveraging AI to support data mapping and data discovery, as they seek to address the challenge of data proliferation. Despite this trend, businesses should be aware of the shortcomings of AI-driven data discovery, instead investing in specialized data discovery solutions such as Enterprise Recon. This platform combines context-defined pattern matching, based on comprehensive pattern definitions, with AI to optimize discovery for more effective management and remediation.

It will be an exciting, but challenging, year ahead for cybersecurity teams. It is evident that 2024 will be a transformative and innovative period for data management, data discovery and cybersecurity, as organizations adapt to the evolving technological, economic and regulatory landscapes.