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4.2 min to readAsset ManagementData and AI

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

Jonas Jasinskas
Jonas JasinskasGlobal Service Design Lead, Software Sourcing & Portfolio Management
Cubes, data & AI

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.

10 core evaluation considerations

  • Assess current ITAM processes

    Understand your existing ITAM processes, tools, and systems. Evaluate the strengths, weaknesses, and pain points of your current practices. This assessment will help identify where AI can be most beneficial.

  • Data readiness

    AI relies heavily on data. Ensure that your data is accurate, complete, and well-organised. Data quality is crucial for AI to deliver meaningful insights and predictions.

  • Data security and privacy

    Consider the security and privacy implications of AI in ITAM. Implement measures to protect sensitive data, especially if AI systems will have access to sensitive information.

  • Integration with existing systems

    Ensure that AI solutions seamlessly integrate with your existing ITAM tools and systems. A smooth integration will help in the adoption and transition process.

    Ensure that AI solutions seamlessly integrate with your existing ITAM tools and systems. A smooth integration will help in the adoption and transition process.

  • Skill and knowledge development

    Invest in training and upskilling your ITAM and IT teams. AI technologies require expertise in data science, machine learning, and AI model development. Ensure that your personnel have the necessary skills to manage and interpret AI-driven insights.

  • Change management

    Prepare your team for the changes AI will bring to ITAM processes. Communicate the benefits of AI, provide training, and ensure that employees are comfortable with new AI-driven workflows.

  • Define KPIs

    Establish Key Performance Indicators (KPIs) and metrics to measure the success of your AI-driven ITAM initiatives. These could include improved accuracy of asset data, cost savings, reduced security vulnerabilities, and more.

  • Define your objectives

    Clearly define what you want to achieve with AI in ITAM. Whether it's improving asset discovery, optimising resource utilisation, enhancing security, or reducing costs, having clear objectives will guide your AI implementation.

  • Compliance and ethics

    Be mindful of data ethics and regulatory compliance. Ensure that your AI practices adhere to privacy regulations and ethical considerations. Transparently communicate your AI usage to stakeholders.

  • Monitoring and governance

    Implement robust monitoring and governance practices for AI in ITAM. Regularly audit AI processes to maintain transparency and accountability.

There is always someone you can rely on

The good news is that a great deal of the preparation outlined above can be tackled with solutions offered by trusted advisors in the market today.

An assessment of your IT Asset Management (ITAM) maturity can play a crucial role in the successful implementation of generative AI solutions by providing a solid foundation for managing the technology landscape.

By leveraging ITAM consultation through managed services, organisations can enhance their overall IT management practices and tools, ensuring that the implementation of generative AI solutions is well-planned, efficient, and aligned with business goals. This expertise contributes to a smoother deployment, optimised resource usage, and reduced risks associated with AI implementations.

Software portfolio consolidation services can play a vital role in facilitating the implementation and speed of generative AI solutions by reducing complexity, streamlining the software environment, optimising resources, and enhancing overall efficiency. The capabilities in generative AI will certainly have an impact on the world of ITAM, however it is the health and maturity of your environment today that will dictate the business outcomes and speeds at which these new tools can realise value.

Talk to us about the expert support SoftwareOne can provide you with to ensure your organisation benefits from AI-driven ITAM practices.

A colorful neon ring on a black background.

Get ready for AI driven ITAM

Develop a strategic approach that will allow you to derive real positive impact to the business from AI driven ITAM.

Get ready for AI driven ITAM

Develop a strategic approach that will allow you to derive real positive impact to the business from AI driven ITAM.


Jonas Jasinskas

Jonas Jasinskas
Global Service Design Lead, Software Sourcing & Portfolio Management