"SaaS is dead, long live SaaS" — enterprise software isn't dying, it's being replatformed with AI orchestration layers
Dallas Dolan (PWC tech practice leader) coined the phrase "SaaS is dead, long live SaaS" to describe the transformation underway. Enterprise clients aren't abandoning Salesforce, Office 365, or Google Workspace — they're augmenting them with AI orchestration tools (LLMs, GitHub, visual design tools) to extract more value from existing platforms. The shift is from "how many seats do we need?" to "how do we use AI to get more value per seat?" This is a reconsideration of platform dynamics, not a wholesale replacement.
"SaaS is dead, long live SaaS. We're seeing a quantum shift in how corporations think about their tech budgets — not spending less on software, but recontemplating where the money is spent."
PWC's M&A teams have shifted from PowerPoint screens to coding screens — using visual design, GitHub, and LLMs to build workflows
Dolan's on-the-ground observation: walking through PWC's M&A offices, screens have changed from research pages and slide decks to "black coding screens" — employees using low-code tools (Vertex AI, visual design platforms) and GitHub to build custom workflows and data pipelines. These aren't professional coders; they're bankers and consultants who've adopted AI-native workflows. They're still using Office 365 and traditional tools, but they've added a new layer of AI-assisted automation.
"You see a lot of different screens now. It used to be research pages and PowerPoints. Now you see black coding screens — people using visual design, Vertex, GitHub to create workflows that ingest content and interact with LLMs."
In 10 years, the new form of capital may be "how much compute do you own" rather than "how much software revenue do you generate"
Dolan's most provocative claim: enterprise software cost savings aren't flowing to shareholders — they're being rotated into capital infrastructure (GPUs, TPUs, power, data centers). Companies are using AI-driven productivity gains to vertically integrate their compute stack. In a decade, the balance sheet asset that matters may not be software licenses or SaaS subscriptions, but owned compute capacity. This is a structural rotation from software margins (80%+) to hardware margins (20-40%) at scale.
"If you look out 10 years, perhaps the new form of capital is not software license income, but how much compute do you own and how much runs through your infrastructure."
Enterprise clients won't abandon Salesforce or ServiceNow for startups — trust and auditability matter more than features for regulated industries
Dolan's point: financial services, healthcare, and public sector companies operate in highly regulated environments where auditability and platform reliability are non-negotiable. A new AI-native CRM might have better features, but it doesn't have a decade of compliance certifications, audit trails, and proven uptime. The mandate for regulated businesses is "high degree of auditability and reliability" — which favors incumbents with trust, not startups with features.
"I don't see a complete divergence from enterprise software companies we've always trusted. Especially in regulated businesses, the mandate is a high degree of auditability and reliability."
Cost savings from AI aren't going to shareholders — they're being reinvested in infrastructure, demand generation, and global expansion
The conventional take: if AI makes workers 20% more productive, companies fire 20% of workers and pay the savings to shareholders. Dolan's reporting: cost savings are rotating into (1) capital infrastructure (GPUs, data centers), (2) demand generation (finding new customers globally), and (3) product development (building AI-native features). Private equity benefits from margin improvement, but public enterprises are reinvesting, not distributing. The rotation is from labor costs to capital expenditures.
"Savings are not going away and going straight to shareholders. They're being reinvested — into capital infrastructure, demand generation, and new products."
A bank CEO told PWC: "AI gives us more deployable capital to do more investing — and we can spend more time with founders"
Dolan's conversation with a Texas bank: AI efficiency gains don't just save money, they free up capacity to evaluate more deals and spend more time with portfolio companies. If investment bankers can analyze 2x as many deals with the same headcount, the constraint shifts from analyst capacity to relationship bandwidth. This is the positive-sum version of the AI narrative: productivity gains enable more activity, not just cost cuts.
Private equity is seeing the biggest mindset shift around AI — using it to platform portfolio companies and create operational leverage
PWC is publishing research on AI's impact on private equity. The thesis: PE firms are using AI to accelerate value creation in portfolio companies (operations, customer acquisition, unit economics), not just cost-cutting. The platformization dynamic — where PE firms build centralized AI capabilities that all portfolio companies can leverage — creates a new source of alpha. This mirrors the "PwC internal AI tools rolling out across offices" playbook but applied to PE portfolio construction.
Consumption-based pricing is replacing seat-based SaaS licensing — Adobe did it 10 years ago, now it's permeating the ecosystem
Dolan's historical note: Adobe transitioned to consumption-based Creative Cloud pricing over a decade ago, enduring a painful multi-year financial transition. That model is now standard for AI-era SaaS: charge based on usage (API calls, compute, storage) rather than seats. This changes everything — how sales teams sell, how products are built, how marketing positions value, and how partnerships are structured. The companies that transition successfully will survive; those that can't will die.