Preparing IT Teams For The Next AI Wave

Uploaded on 2024-10-31 in TECHNOLOGY-Key Areas-Artificial Intelligence, TECHNOLOGY--Resilience, JOBS-Training, FREE TO VIEW

Artificial Intelligence (AI) is fast transforming modern businesses, they are now beginning to understand the importance of risk and compliance - not only as regulatory checkboxes but as critical components of successful AI integration.

Historically, these activities have been sidelined, as they often seem to lack direct value or innovation. However, AI’s growing role has changed the game, creating a compelling reason for IT departments to address risk and compliance with renewed focus and urgency.

Preparing for AI readiness requires a solid framework that can manage data integrity, security, and compliance, ensuring that organisations maintain control and mitigate risks effectively. Here are some critical steps to consider.

Defining Your Data Estate

AI’s effectiveness relies on well-organised, accessible data. The first step toward readiness is defining your data estate, a process that involves cataloguing all data sources, locations, and formats across the organisation.

With AI’s ability to process and analyse large datasets, an incomplete or poorly mapped data landscape could result in inaccurate insights or overlooked assets. Identifying all data points also reveals hidden risks, from compliance liabilities to potential vulnerabilities, allowing organisations to address these proactively.

Completing Cloud Migration

Cloud environments have become the standard for handling modern AI tools, given their superior data management capabilities compared to traditional on-premises systems. Migrating to the cloud enables organisations to leverage mature, built-in tools for data governance and policy management, as well as scalable computing power essential for AI applications.

This shift in infrastructure can be useefully supported by a specialist manged services provider, who can offer enhanced cloud support to support in-house IT teams with the complex task of cloud migration, from design and implementation to ongoing optimisation and support.

Garry Ackerman, Director, of cloud-migration firm Argantic comments on the advantage of providing tailored support to mid-market organisations that may lack extensive in-house resources. "Through this partnership, internal IT teams gain access to skills and support only as needed, ensuring they can focus on core activities without being sidetracked by ongoing AI management and compliance projects."

Ensuring Proper Data Access Controls

One of AI’s unique capabilities is to turn ordinary users into "super searchers," allowing them to uncover data they may not have previously accessed or known about. Consequently, establishing proper data access controls becomes vital. By limiting access to only the data each user needs, organisations reduce the risk of sensitive information being inadvertently exposed or misused.

This step not only safeguards proprietary data but also ensures compliance with data protection regulations, such as GDPR, as AI-driven searches can lead to unexpected privacy implications if unmanaged.

Defining Data Loss, Sharing & Retention Policies

AI’s integration into day-to-day operations brings increased attention to data handling policies. Data loss prevention, controlled data sharing, and retention policies must be well-defined and directly tied to data files, enabling these policies to persist as data moves within or outside the organisation.

Properly applied data policies help maintain data integrity, reduce the risk of leaks, and ensure that outdated or unnecessary data is systematically purged, avoiding clutter and compliance violations.

Addressing Shadow AI Usage

As companies test the waters with new AI tools, a common trend has emerged: senior staff experimenting with these tools outside of IT’s oversight. This 'shadow AI' activity, while innovative, raises serious concerns over unauthorised access to sensitive data and unmonitored data movement.

Empowering Internal IT Teams For The AI-driven Future

For internal IT teams tasked with managing these changes, the burden can be significant. AI adoption places extra demands on teams that may already be stretched thin, dealing with legacy systems that are costly and rigid.

AI adoption is a powerful tool for innovation, but it introduces risks that business leaders must be prepared to manage. Addressing these risks head-on with a comprehensive compliance and data governance framework will pave the way for successful AI integration.

Image: Ideogram

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