As we all know, the technology landscape doesn't pause. The conversations we're having with customers right now suggest the next twelve months will be one of the most consequential periods in IT Asset Management in recent memory.
We've been watching the market closely, as we always do, and what's emerging isn't just a shift in product features. It's a fundamental rethinking of what it means to manage technology spend and risk in an AI-first world. For our customers, that brings both challenges and real, meaningful opportunity.
Here's what we see on the horizon, and how you can get ahead of it.
AI Spend Management in ITAM: From Pilot Programme to Core Budget Line
If your organisation has moved beyond experimenting with AI and is actively deploying it, you're not alone. Across our customer base, we're seeing AI workloads move from innovation budgets into operational spend, fast. And with that shift comes a new problem: visibility.
AI spend behaves differently from traditional software licensing. Usage-based pricing, token consumption, model-specific costs, and data platform fees don't always fit neatly into the frameworks most ITAM and FinOps teams have spent years building. The result? A growing blind spot at the exact moment AI is becoming one of your largest and fastest-growing cost categories.
The good news is that the tools to address this are maturing. The platforms we work with are investing heavily in AI spend visibility, covering token usage, model-level costs, and data platform consumption (Databricks and Snowflake, for example) in ways that weren't possible even twelve months ago. That means the window to get ahead of this is open right now, before AI spend becomes unmanageable.
Where to start
Start by mapping where AI tools and services exist in your estate, sanctioned and unsanctioned alike. Shadow AI is the new shadow IT, and it carries the same compliance and cost risks. If you don't know what you're running, you can't manage it.
The Hidden Risk in AI Pricing: A Window, Not a Floor
There's something important that tends to get lost in the excitement around AI adoption: the pricing you're paying today almost certainly doesn't reflect the true cost of delivering these services. The AI arms race is being subsidised, and that subsidy will eventually end.
Every major AI provider is currently operating below the cost of delivery. They're doing it deliberately, with one goal in mind: capture enterprise market share before price discipline returns. The hyperscalers are collectively spending hundreds of billions on infrastructure in 2026 alone, significantly more than the year prior, with free cash flow being squeezed in the process. This isn't a sustainable business model. It's a land grab. And like all land grabs, it has a time limit.
For enterprises building AI into core operations, the implications are significant. Organisations that become deeply reliant on a single vendor's models or infrastructure are accumulating switching-cost risk at precisely the moment when pricing pressure is building. By the time price increases arrive, the cost of moving will feel prohibitive. That's not an accident… it's the strategy.
What you can do now
Where possible, explore multi-year agreements while vendors are still prioritising growth over margin. The negotiating window is open now, not later. Avoid building deep dependencies on a single AI provider; architectural choices that preserve flexibility will be worth considerably more in two or three years than they cost today. And when you're modelling the ROI of AI integration, build your scenarios at two to three times current API pricing. If the case still holds at that level, you're on solid ground. If it doesn't, that's important information to have before you're committed. The current pricing landscape is a window. Treat it like one.
How AI Is Making ITAM Platforms Significantly Smarter in 2026
The intelligent features landing in ITAM toolsets this year are genuinely exciting, and we don't say that lightly. We've seen plenty of "AI-powered" marketing that amounts to little more than a better search bar. What's different now is that the automation is doing real work.
Think about the time your team spends reviewing contracts and processing invoices. For many of our customers, that's hours every week. Skilled people doing manual, repetitive work that keeps them from higher-value analysis. AI-assisted contract and invoice ingestion is changing that equation materially, with customers reporting significant time savings per document. That's not a rounding error; that's capacity your team gets back.
Similarly, natural language querying of your ITAM data, the ability to ask your platform a plain English question and receive a structured, accurate report, is moving from a curiosity to a genuine productivity tool. It makes your ITAM data more accessible to stakeholders who've never logged into the platform, which in turn makes your programme more influential across the business.
What you can do today
Audit where your team's time actually goes. Identify the manual, high-frequency tasks that are prime candidates for AI-assisted automation. The platforms are ready. The question is whether your processes are configured to take advantage.
SaaS Sprawl and Governance: Closing the Visibility Gap in Your Organisation
SaaS spend continues to climb, and the governance gap between what's being purchased and what's being managed is widening at most organisations. New tools get adopted at the team or project level, often without IT visibility, and the compliance and cost risks compound...
The positive development here is that SaaS management capabilities are becoming more granular and more actionable. Usage-based cost management, consumption analytics, and automated optimisation recommendations are giving ITAM teams the leverage they need to have credible conversations with business stakeholders about rightsizing licences and eliminating waste.
Our customers who've acted on SaaS optimisation have consistently found savings that more than justify the effort. In some cases, those savings have funded broader ITAM programme improvements. That's a conversation worth having.
The practical next step
If you don't have a clear picture of your SaaS estate, including shadow SaaS, that's the first gap to close. Discovery is the foundation everything else is built on.
ITAM and FinOps Convergence: Why Connecting These Disciplines Reduces Technology Spend
For years, ITAM and FinOps teams have often operated in parallel, sharing goals but not always sharing data or processes. That separation is becoming increasingly difficult to justify, and increasingly costly to maintain.
Cloud spend, software-on-cloud licensing, AI infrastructure costs, and data platform fees don't respect the traditional boundary between software asset management and cloud financial management. The organisations that are navigating this well are the ones that have connected these disciplines, using unified data, shared reporting, and integrated workflows.
This isn't about reorganising your team. It's about ensuring that the insights from your ITAM programme inform your FinOps decisions, and vice versa. The platforms support this convergence; the question is whether your operating model does too.
Our advice
Identify the handover points between your ITAM and FinOps functions, or between the teams and tools that handle each. Where are the data gaps? Where are decisions being made with incomplete information? Those are the places to start.
ITAM Data Quality: Still the Foundation Every Effective Programme Is Built On
We've always believed this, and the AI era reinforces it: the intelligence you get out of any system is only as good as the data you put in. As AI-powered features become more central to how ITAM platforms operate, the quality of your underlying data becomes more consequential, not less.
Discovery, normalisation, and inventory accuracy aren't glamorous. But they're the reason some organisations can walk into a vendor audit or a board conversation with confidence, while others can't. Your data foundation determines the ceiling on everything you can achieve.
A critical step
Don't assume your data quality is where it needs to be. A structured data health review, looking at discovery coverage, normalisation rates, and integration accuracy, gives you a clear baseline and a prioritised improvement plan.
How TMG Helps You Navigate the 2026 ITAM Landscape
We've been doing this since 2006. We've seen the hype cycles, the tool consolidations, the vendor pivots, and the market shifts. What's happening right now is real, and the organisations that position themselves thoughtfully over the next twelve months will have a meaningful advantage.
At TMG, our role is to help you cut through the noise and focus on what actually matters for your organisation. We're vendor-agnostic. Our loyalty is to your outcomes, not to any particular toolset. And we bring the depth of experience to know which innovations are worth acting on now, and which are worth watching a little longer.
Whether you're looking to strengthen your data foundation, unlock AI-assisted automation in your ITAM workflows, bring SaaS spend under proper governance, or connect your ITAM and FinOps practices more effectively, we're here to help you work through it, practically and without the jargon.
We don't shout about what's coming. We sit down with you, understand where you are, and help you map a path forward that makes sense for your business.
Ready to talk through what the next year looks like for your organisation? Reach out to the team at info@tmg100.com. We'd love to have that conversation.
The Mastermind Group (TMG) is an independent ITAM and FinOps managed services provider, working with organisations across Australia and beyond to optimise technology spend, manage risk, and get the most from their IT investments. Learn more at tmgitam.com.