5 Predictions for 2026 That Should Make Finance Leaders Uncomfortable

According to a recent Forrester report, only 15% of AI decision makers reported any EBITDA lift from their AI investments in the past year. Fewer than one-third could tie AI value to any P&L changes.

That stat is wild. And I think it tells us something important about how we've been measuring AI's impact all wrong.

Anyone who's used ChatGPT or Claude for even five minutes knows AI is creating value. We feel it every day. So if it's not showing up on the P&L, where's it going?

Here's what I think happened in 2025: companies prioritized measuring top-line increases tied to AI. Will this investment lead to 20% more output and 20% more revenue growth? 

That was the question everyone asked. An AI investment posture focused on growth doesn't require headcount changes, you're betting on expansion, not efficiency.

The problem? Measuring ROI for efficiency gains has been genuinely hard. 

How do you know if employees are using AI to generate the same levels of productivity in less time, or whether the tools just aren't helping that much? 

Without tight measurement infrastructure, it's nearly impossible to tell whether your teams are doing more with less, or simply doing the same amount with extra tools you're paying for.

The value capture is happening. But without measurement systems designed to track it, CFOs can't see where it's actually landing.

1. 2026 Will Be the Year AI Gets Audited

This measurement gap is setting up one of the most consequential divergences in corporate performance we'll see in 2026. Companies that build the infrastructure to track AI productivity will capture organizational value. Those that don't will continue questioning their investments while competitors pull ahead.

In 2026, the measurement of efficiency gains will get much tighter. Companies will scratch and claw their way to justifying ROI on a bottom-line basis, not just top-line. I expect to see many more company re-orgs designed to support a more AI-driven posture. Teams restructured around what AI makes possible. Workflows rebuilt from the ground up.

Those that don't will be left behind, maybe for good.

2. Your Vendors Have Discovered the "AI Tax"

We're seeing something in our negotiation data that every finance leader should be aware of. Software suppliers are increasingly incorporating what I call an "AI tax" into renewal quotes. 

It used to be typical to see a 5-10% "innovation uplift" at renewal. Now we're seeing 20-30% uplifts, with new AI features as the justification.

Suppliers are feeling massive pressure to show AI revenue given the huge investments across the ecosystem. So they're bundling AI capabilities into offerings whether you asked for them or not. Slack AI is now standard with most tiers. Google is embedding Gemini everywhere. And they're all looking to recoup those R&D investments through your renewal.

The challenge is that the incremental value is often hard to reconcile against the incremental cost. Our data shows organizations are becoming less tolerant of price hikes from legacy tools unless clearly tied to real, measurable value.

The reality is, for many companies, they are in-deep with certain vendors and feel locked-in. You might feel like you have no choice but to pay the AI tax. You don't have time to evaluate alternatives, run migrations, or retrain teams. So you bite the bullet and pay the uplift.

But that dynamic is about to shift.

What used to be considered vendor lock-in — effectively a hostage situation where customers had no choice but to stick with their incumbent — will start to be put to the test in 2026. Customers are getting frustrated with what feels like unrealized value tied to higher-than-ever increases. And frustration eventually turns into action.

Vendors will be forced to confront a challenging dilemma: Do they continue pushing short-term AI revenue optimization and risk alienating their customer base? Or do they take some short-term losses to build toward a better long-term future?

I expect this AI tax to fade as vendors get punched in the mouth a few times by frustrated customers. The smart ones will shift focus from extracting AI revenue to creating long-term value in this new paradigm. The ones who don't will watch their "locked-in" customers finally find the motivation to leave.

3. M&A Is About to Get Weird

Look at what just happened with Grammarly. They just rebranded to Superhuman after acquiring Superhuman itself, plus Coda. That's a company with 15+ years of text data layering on application-focused tools.

This is a different type of M&A than we've seen historically. It’s beyond “traditional,” consolidation, it's the combination of application-layer tools supported by defensible, differentiated data assets.

The massive growth in SaaS fueled by the 2021-2022 bubble is going to merge. Those really well-designed applications with great UX but no underlying data to power AI? They're acquisition targets. Expect to see more bolt-on deals: grab the excellent application layer and sit it on top of a data moat.

4. The Interface You're Using Is About to Disappear

Two forces are colliding around point solutions, and the implications are significant.

1. The rise of MCPs (Model Context Protocols) is shifting us from screen-and-application-forward design to text-and-chat-forward experiences. The primary user interface is increasingly going to be where you already spend time – ChatGPT, Claude, Google, maybe Slack if they can get it right. ClickUp has been trying to do this for a while, and starting to see traction. Instead of juggling six tabs and remembering how each app works, MCPs bring everything together into one human-centric interface.
2. OpenAI is systematically eliminating SaaS categories. They launched their knowledge base solution recently. Guru, Confluence, similar tools? Commoditized overnight. This will continue as these AI giants target use cases that reinforce their data models.

I won't sugarcoat it: it's scary to be starting a company in an application space right now. You don't know when Google, OpenAI, Anthropic, or Microsoft will wipe out entire verticals with the click of a button.

5. The Case for a Chief AI Officer

As AI becomes part of everyday operations in virtually every industry, establishing a Chief AI Officer could be an effective tool to shine light and bring real attention to AI transformation within organizations. Most C-Suite members are already juggling multiple responsibilities – driving performance, answering to investors, making sure the trains run on time.

Having someone at the leadership table whose primary focus is identifying AI opportunities, securing budget and resources, and pushing forward the changes needed to realize productivity will become necessary for large organizations in 2026. Especially where culture tends to resist change, bringing in leadership designed to accelerate transformation and armed with resources to execute feels like a good investment.

What This Means for Your Team

Given the trend towards MCP centralization and the rising "AI tax" on renewals, finance and procurement teams should actually feel optimistic about what's ahead.

Consolidation is happening and underway. As technology becomes more automated and trustworthy, finance and procurement teams can look forward to a world where prompting, asking questions, and executing workflows happens in a more AI-forward way, and it actually works. Less manual effort, fewer clicks, less tab-juggling.

The companies that will thrive in 2026 are the ones bringing insights and actions to the table for stakeholders, serving them up ready to go, and requiring less effort to find the information yourself.

If I'm a procurement person or finance leader, I'm looking at solutions with a clear data advantage and a commitment to exposing insights through AI that help me action in a seamless way. The winners won’t give me data, they'll tell me what to do with it.