How AI is Changing Enterprise Tech Strategy (And What You Need to Do)

Why traditional SaaS is losing ground

Generative AI isn’t just a new tool; it requires a fundamental rewrite of your organisation’s technology strategy. Today’s organisations are at significant risk of disruption due to the transformational impact that AI is having on traditional enterprise software. For decades now, organisations have relied upon the stability of Software-as-a-Service (SaaS) across all functions. Today, Agentic AI is changing how we work and develop software, challenging traditional SaaS and consequently driving many organisations to reconsider their technology strategies. Because if your core CRM system is at risk of facing their Kodak moment, you want to be prepared.

By 2026, global AI investment is projected to exceed US$2.2 trillion surpassing Australia’s annual GDP. This capital influx signals a predatory shift in the ecosystem, as AI-native solutions begin to cannibalise the market share of traditional software vendors, signaling a new era of disrupting the disruptors. (source)

In the meantime, almost US$2 trillion in market cap has evaporated from SaaS vendors with over US$1 trillion in 2026 alone (source). Revenue multiples dropped from their 2021 peak of 41x to 6x. The market seems to be repricing the structural defensibility of being a system of record in an agentic AI world. Customer demand is shifting the pricing model from seats to outcomes and leading SaaS are moving toward usage based or outcome based pricing. Currently, 41% of the market has adopted these models, up from 15% in previous years [Bessemer]. This ensures that software spend remains aligned with actual customer business value. However, it’s eroding the unit economics of deterministic software and code (build once, sell infinitely). This erosion is putting the feature roadmaps of these software vendors at risk to be able to keep up with the evolving needs of its customer base. For customers, this means the longevity of their core platform stack could be eroding requiring reconsideration.

Simultaneously, the world is going through a turbulent geopolitical period introducing uncertainty in terms of economic and cultural value alignment. It’s sparked organisations and governments around the world to re-evaluate platform decisions in this light. Examples include the International Criminal Court moving away from Microsoft to reduce the dependency on technologies that are vulnerable to US sanctioning posing a significant risk on operational business continuity (source).

So what are the strategic questions to ask in regards to your platform ecosystem? The real questions can be found by taking a leaf out of the investor handbook:

This reframing changes everything. Further, it shines a direct spotlight on whether enterprise platforms are acting as an enabler or an impediment to your business growth objectives. It turns tech stack rationalisation and technology operations from the typical cost optimisation exercise into a strategic derisking activity from both an offensive and defensive angle. One that has the power to trigger a complete reshuffling of the enterprise platform landscape and the fundamental requirement for executing business strategy.

In this context, every organisation will have to consider its AI investment given it’s the most significant external trend influencing the market. It shifts the conversation away from the latest AI model benchmarking towards strategic decisions about a build, buy and partner ecosystem. It’s about really understanding the opportunities and risks in making these decisions, as well as ensuring long term capability building to be able to effectively serve your customers’ needs in this rapidly evolving market. For most organisations that means forging the right partnerships is critical. However, the hardest part is to understand how these technology trends change which questions to ask to solve for the strategic direction to begin with.

To understand what this means, let’s draw the analogy to the digital transformation. Over 25 years ago, digital brought a similar paradigm shift by introducing SaaS, digital customer experiences, and cross-functional teams working on iterative delivery. Technology firms rapidly started dominating Fortune 500, ‘Platform’ became the winning playbook, and legacy enterprises had to reinvent and rebuild quickly to survive. Digital transformation became the strategic centerpiece of nearly every organisation. Many organisations struggled to understand the trend, the risks and opportunities and consequently how to timely prepare for the future. What followed was a US$27 trillion value migration from digital laggards to digital leaders (source).

Now, AI is bringing the largest organisational paradigm shift since the digital transformation uniting human and AI agents both virtual and physical to work side by side at scale at lower marginal cost. Agentic AI and in particular Agentic Software Development, is now opening the opportunity for organisations to reconsider what to build inhouse versus what to keep outsourced through buy / partner.

Agentic coding and software delivery in general is now revisiting this exact ‘buy vs. build’ trade-off. With switching costs collapsing as Amazon, Google, Microsoft, Anthropic, OpenAI, Snowflake and Databricks are all launching AI code generation tools that help businesses migrate massive datasets between platforms. Mantel’s recent technology migration work is demonstrating that software switching costs are falling rapidly. The cost of data migration was once the single greatest barrier to platform switching, but is now becoming rapidly less of a problem as AI tools including Mantel’s own migration accelerator (ORCA) are significantly enhancing efficiency and accuracy of migrations, thus reducing risk for migration projects. Workflow embedding is being abstracted. Agentic AI doesn’t need a large UI surface. Agents interface with systems via API, MCP, direct database access, and other new interaction mechanisms becoming available at lightning speed.

Digital-native organisations are already internalising functions previously outsourced to SaaS.

What happens when we reframe the enterprise’s technology stack as an investment position? Every organisation should consider technological stagnation as a critical red flag. The warning signs are outdated IT systems, resistance to technological change from management, and a lack of data collection or analysis capabilities. These factors suggest companies may struggle to adapt as AI capabilities advance.

When baselining technology platform and ecosystem maturity, we can use five alternative questions to reframe the strategic mindset:

The wrong platform does more than waste money. It caps revenue growth. If your CRM can’t support AI-driven personalisation at the speed your competitors deliver it, you have bigger problems than the technology itself: you have a market share problem. Any technology that slows your cycle time from information to action becomes a drag on revenue velocity.

If your tech stack forces you into consumption-based pricing with a vendor whose costs scale nonlinearly in excess of your revenue unit economics, your margins erode with every increment of AI adoption. This makes the platform choice a margin decision. On the other hand, if your stack forces you into long-term commitments, you increase partnership dependency. This makes the platform choice a partnership decision. Either way, it moves the conversation away from the dreaded static platform feature comparison that so many organisations rely on too heavily for making their strategic decisions.

The emerging competitive differentiator is decision velocity: how quickly smaller decision chains and processes can be automated at scale. A tech stack built around human-in-the-loop workflows at every step physically cannot compete with one designed for delegated autonomy on high-frequency, low-risk decisions. A legacy stack enforces an organisational speed limit. The ability to scale AI efficiently, responsibly and sustainably is the key here.

Data sovereignty requirements and the evolving Consumer Data Right (CDR) in Australia make data portability a critical, non-negotiable strategic requirement. Enterprise data tolls and API economics are becoming a major pain point. Connector fees are looking like the new cloud egress charges. This is particularly problematic for organisations with federated technology strategies and vast platform ecosystems. They are a tax on your own data that increases the cost of doing anything new with it. If your vendor treats your data as leverage rather than infrastructure, every AI initiative faces a hidden tax.

Every white collar worker in Australia must have a profound hate-love relationship with AI by now. It’s the most existential threat for most in terms of job safety and income stability whilst simultaneously the largest opportunity to increase their individual productivity and value add to the Australian economy. Organisations that have instilled fear in their workforce by making bold market moves to replace employees by AI have taken a significant risk by focusing on trying to capture value from operational efficiencies, rather than focusing on organisational wide AI capability and adoption that is going to be critical for capturing the real value opportunities that AI is presenting.

Designing future proof technology infrastructure will become one of the most critical decisions most organisations need to make. The wrong platform creates risk across every business dimension that matters, from revenue growth to margin expansion, decision velocity, operational efficiency, talent acquisition, and the ability to meet rapidly evolving customer expectations.

Financial investors treat technological stagnation as a red flag on par with customer engagement, financial performance or management quality issues. However, most organisations are still playing catch up in balancing these priorities on a strategic level internally. 

The message for organisations is clear: The time for ‘wait and see’ is over. Your competitive differentiation in the next few years will be determined by your platform decisions today. Optimise your stack while you still hold the leverage.