AI Is Here—And It’s Your Best ITAM Ally, Not Your Replacement

ITAM News & Analysis

AI Is Here—And It’s Your Best ITAM Ally, Not Your Replacement

I’ve been asked several times over the last couple of years how AI will impact ITAM and how it will impact jobs. Well, who knows what will actually happen in the future, but my guestimate is that, unless you are in a very repetitive and low-skill part of ITAM, AI will bring a new wave of technology to augment your superpowers, rather than being a threat to your role. But as always, as a profession, we will need to evolve.

In this article, I’ll explain my rationale behind this optimistic opinion of AI using a recent job description and the Practical ITAM best practice framework. Lastly, I’ll share what skills we might need to focus on over the next 5 – 10 years.

Firstly, let’s look at this recent job description for a senior ITAM role in the US. It certainly looks like a challenging and interesting role for somebody.

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IT Asset Management-Vice President ($153,000.00 and $196,000.00)

“Your responsibilities will include working with (group) companies and entities to provide ITAM Program support and direction to ensure governance, including policies, controls, standards, and procedures, are in place to meet (group) regulatory, operational, audit and reporting requirements when it comes to hardware and software asset management. Responsible for assisting the team to maintain accurate inventory of all hardware and software assets, both physical and virtual, and to provide governance support for compliance in relation to standard hardware for both end user and data centre products with internal policies, controls, and third-party contracts. This includes the end-to-end asset lifecycle from planning, acquisition, deployment, management, and decommission/disposal of IT assets. The ITAM Process lead will also be responsible for support requirements for regulatory, internal/external audits, as needed. The role will report to the ITAM Governance Lead and is responsible for supporting the build-out and operations of the IT Asset Management practice.”

Role Objectives:

• Lead business process workshops with the various internal technology teams to identify risks and design future state improvements to increase data quality and drive process standardisation globally.
• Support lifecycle asset management tasks, projects, activities and engagements for the ITAM program.
• Extensive experience with process governance and data quality remediation
• Works with ITAM leadership to develop and enhance lifecycle asset management strategy, company policies and processes that align with the programs and customer’s business objectives.
• Analyses new and complex lifecycle asset management-related problems and creates innovative solutions that address schedule, technology, methodology, tools, solution components, and financial management.
• Manages the daily tracking of internal data quality dashboards overseeing acquisitions, deployments, asset utilisation, and disposition of IT assets.
• Contributes to the maturity of processes and procedures enhancing IT asset data quality and process compliance.
• Manage internal IT Asset Management dashboards, metrics, visualisations and reports and report updates to senior leadership.
• Assist in creation of compliance reports and analysis to review with asset and business application owners for support renewals, audits, or ad hoc requirements on a regular basis.
  Monitor hardware compliance and usage to identify, reallocate and remove unused IT assets.
  Maintains current knowledge of relevant technology as assigned.
• Coordinate with team members in the daily administration of all IT asset management related activities.
• Assist in coordinating requirements for asset validations, reconciliation and remediation in support of contract renewals by providing them an overview of what they currently have, what they use and what they should tune-up or renew.
• Participates in special projects as required.

A Needed Framework for SaaS Cost Control 

SaaS management is challenging. This challenge has seen the rapid growth of dedicated SaaS Management Platforms (SMPs) such as Zylo and Torii. Existing ITAM tools such as Flexera One and USU Software Management have also added SaaS management capabilities to their tools.  

Unlike Infrastructure-as-a-Service (IaaS) – where costs are closely monitored and optimised – SaaS procurement is often decentralised. This leads to duplicate licenses, unused subscriptions, and a lack of visibility into overall spend. The FinOps Foundation’s move to standardise SaaS cost and usage reporting through frameworks like FOCUS™ (FinOps Open Cost and Usage Specification) has the potential to bring much-needed clarity to a murky landscape. 

If done right, this initiative could enable organisations to:

• track SaaS expenditure more effectively
• compare costs across vendors
• integrate SaaS financial management into their broader cloud strategies.

Establishing a common language for SaaS financial operations could empower finance, IT, and procurement teams to collaborate better on cost optimisation. 

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Elements of this role most likely to still require a human touch within 5-10 years

Even as AI-driven tools streamline data analysis and automate routine tasks, there are pivotal facets of a VP-level ITAM role that still demand a human touch. Strategic oversight and governance hinge on interpreting broad business objectives and complex regulations, while leadership and stakeholder management require empathy, conflict resolution, and the ability to unify diverse teams. Winning over hearts and mind. Negotiating high-stakes contracts with vendors calls for emotional intelligence and real-time adaptability that AI hasn’t mastered, and making judgment calls on regulatory compliance—especially under frameworks like NIST—demands a nuanced, context-rich approach that pure algorithms can’t replicate.

That’s where forward-thinking leaders will excel; they’ll harness AI’s speed and precision while staying attuned to the subtleties of all things human in their organisation.

Despite the promise, the reality of managing SaaS spend presents unique challenges that could undermine FinOps’ success in this space. 

Elements of this role likely to be heavily augmented by AI within the next five to ten years

• Routine Data & Reconciliation – AI automates daily asset tracking, anomaly detection, and real-time usage alerts, slashing manual “true-up” work.
• Compliance & Reporting – Automated scans uncover non-compliance, compile audit artifacts, and send renewal prompts, streamlining regulatory oversight.
• Licenses & Contracts – Natural language processing flags key contract terms, renewal dates, and usage anomalies, pinpointing renegotiation opportunities.
• Dashboards & Decision Support – AI pulls data for on-demand dashboards and forecasts hardware/software needs, delivering actionable insights without manual effort.
• Administrative Workflows – Automated routing handles common approvals and notifications, escalating only exceptions so ITAM teams can focus on strategic tasks.

From a best practice perspective

We can also look at this from a best practice framework point of view. The ITAM Forum’s Practical ITAM framework includes twelve key competencies for an ITAM best practice.

In the next 5-10 years, areas with a high dependency on human intervention are likely to be:

• Authority, Team, Stakeholders and Communication – Despite AI’s growing capabilities, authority, team dynamics, stakeholder engagement, and communication still hinge on distinctly human qualities. Exercising authority requires judgment that balances organisational goals with ethics and culture, something AI alone cannot provide. Team leadership calls for empathy, motivation, and trust-building, attributes that rely heavily on interpersonal connection.

Stakeholder engagement and communication likewise demand strong emotional intelligence, adaptability, and an understanding of nuanced concerns. Negotiations, conflict resolution, and strategic alignment with diverse groups extend beyond what algorithms can interpret purely from data. As a result, while AI will continue to handle an expanding range of tasks, the critical elements of human authority, collaboration, and nuanced communication will remain central to successful leadership over the next five to ten years.

Medium Dependency

• Plan, Improve, Input, Operation, Output, and Tools all involve a mix of structured processes and human-driven judgment. AI can streamline data collection, provide predictive insights, and automate certain repetitive tasks within each phase. However, activities like goal setting (Plan), continuous refinement (Improve), context-aware data interpretation (Input), complex system orchestration (Operation), and tailored deliverables (Output) still depend on human oversight, creativity, and adaptability. Even with AI-driven analysis and automation, these stages benefit from people who can assess changing conditions, interpret nuanced feedback, and make strategic decisions that algorithms alone can’t fully address. As a result, they see a moderate impact—boosted by AI but remaining reliant on human intervention for critical thinking and contextual understanding.

Low Dependency – Most likely to be dominated by AI

• Tasks focused on accuracy and optimisation are highly data-intensive and algorithmic, making them prime candidates for AI-driven solutions. Machine learning and advanced analytics can process vast amounts of information faster and more reliably than humans, constantly refining performance through iterative improvements. As these functions hinge on pattern recognition, mathematical precision, and adaptive modelling—areas where AI excels—expect automation to increasingly outpace human capability over the next five to ten years.

How can existing ITAM professionals prepare for these transitions?

1. Soft Skills
   • Strategic, Advisory, & Influencing Skills: Build competence in stakeholder management, negotiation, and senior‐level communication. AI can crunch numbers, but you must persuade decision‐makers on next steps.
   • Change Leadership: Learn how to lead process improvements across organisational boundaries, including conflict resolution and cross‐departmental project management.
2. Augment Data & Technical Knowledge
   • AI & Analytics Familiarity: You don’t have to become a data scientist, but understanding the fundamentals of machine learning, data modelling, and basic analytics tools (e.g., Python, Power BI) will help you partner effectively with data teams.
   • Cloud & SaaS Asset Management: As usage patterns shift rapidly to cloud, building best practices for dynamic/elastic assets becomes vital.
3. Master the ITAM Tools Landscape
   • In many firms, these will be the core “engine” for automation and AI. Deep functional knowledge of key ITAM platforms remains a career differentiator. This too will evolve with AI – For example, a future role is the orchestrator of AI ITAM agents.
   • Integration & APIs: As more “smart” agents proliferate, integration across procurement, finance, HR, and DevOps pipelines will become essential. Understanding how APIs and system integrations work can help you shape robust ITAM solutions.
4. Focus on Governance & Continual Improvement
   • Automation Governance: Over time, you may have 50+ automated workflows or AI bots for ITAM. Professionals who can champion a coherent governance structure, track ROI, and maintain accountability will be indispensable.
   • Continual Upskilling & Networking: Stay connected to the ITAM community through conferences, webinars, and certifications to keep tabs on emergent AI use cases and best practices.

Will AI steal your job? No, I don’t think so, but as I mentioned at the start, we will have to evolve as a profession. What it will do is shave hours off repetitive tasks, giving you the bandwidth to shape strategy, influence stakeholders, and deliver genuine value. Think of AI as the rocket fuel for your ITAM career—it’s time to strap in, adapt, and drive AI value within your organisation.

 

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