AI is coming to the world of ITAM – Are you ready?

We've all heard it, AI is coming. In the last months, nearly every publisher presentation, partner update, product launch or technology roundtable mentions the wonders of generative artificial intelligence in some permutation.

Marketing buzz aside, we all have witnessed some of the astounding things that generative AI can produce for both personal and professional applications, everything from recipe creation, storytelling and image generation to in-depth analysis of complicated documents and large datasets.

Utilising the tools and large language models available online today, it’s also obvious that AI is capable of producing errors and miscalculations if it’s not fed optimised data from your organisation’s systems and/or designed without prescribing accurate required outcomes.

There is little doubt that the future of our productivity will be largely shaped by how we implement, adopt, and utilise these new tools and technologies. However, it’s important to remember that these new AI models- trained by people and consumed by people- will rely on the same foundations and trustworthy data that underpin the practices that we follow today.

As companies begin to explore the possibilities of integrating AI into IT Asset Management (ITAM), organisations will be required to develop strategic approaches regarding processes, tools, and systems. This will not only ensure that the data that is consumed by AI is accurate and trustworthy, but that the assistance that we want from artificial intelligence and large language models produces results that have real impact to the business.

Before delving into the specific steps organisations need to take to adopt generative AI, let's first examine the pivotal role it will play in advancing ITAM practices.

5 reasons why AI powers effective ITAM

Integrating artificial intelligence (AI) into IT asset management (ITAM) offers a plethora of benefits that can streamline operations, enhance efficiency, and optimise resource utilisation. Here are some compelling reasons to embrace AI in ITAM:

• Improved asset discovery and tracking: AI algorithms can automatically scan networks, identify assets, and collect comprehensive data about their configurations, software installations, and usage patterns. This real-time visibility into the IT landscape enables organisations to maintain accurate asset inventories, track asset lifecycle, and ensure compliance with licensing agreements.
• Enhanced predictive maintenance: AI-powered predictive analytics can analyse historical asset data, identify patterns, and predict potential hardware failures before they occur. This proactive approach to maintenance reduces downtime, minimises disruptions, and extends the lifespan of IT assets.
• Optimised resource utilisation: AI can analyse asset usage patterns and identify opportunities to optimise resource allocation. It can recommend strategies for consolidating underutilised assets, repurposing hardware, and rightsizing software licenses. This leads to reduced costs, improved performance, and more efficient resource utilisation.
• Strengthened security posture: AI can analyse network traffic, identify anomalies, and detect potential security threats. It can also automate vulnerability assessments, patch management, and incident response procedures. This proactive approach to cybersecurity enhances protection against data breaches and unauthorised access.
• Automated reporting and compliance: AI can automate the generation of ITAM reports, providing insights into asset utilisation, software licenses, and compliance status. This automation saves time, reduces manual effort, and ensures that organisations stay compliant with regulatory requirements.

Integrating AI into ITAM is not without its challenges, such as data quality issues, ethical considerations, and the need for skilled personnel. However, the potential benefits of AI far outweigh these challenges, making it a transformative force in the ITAM landscape.

What can you do today to be prepared for tomorrow

Evaluation and readiness will be crucial steps for organisations looking to adopt generative AI. This includes assessing your organisation’s data quality, data governance, and technical infrastructure. While AI offers significant benefits for ITAM, it also presents challenges.

These include concerns about data privacy, security, the need for skilled personnel to manage AI systems, and potential biases in AI algorithms. Organisations must carefully plan and implement AI solutions in ITAM to ensure they derive maximum benefit while addressing these challenges.

Some of the things you should keep in mind are listed below. This is not an exhaustive list but covers the main topics you need to consider when it comes to integrating AI solutions into your ITAM practice.