The Impact on Valuation When AI Is Part of the Tech Stack

Artificial intelligence is no longer a futuristic concept—it’s rapidly becoming a baseline expectation across industries. For technology companies, especially those seeking to raise capital or position themselves for acquisition, AI is not just a tool for efficiency; it’s increasingly a driver of enterprise value.

The question investors are asking isn’t simply “Do you use AI?”—it’s “How does AI create sustainable advantage in your product, your business model, and your growth trajectory?” Companies that cannot answer this convincingly may be leaving real money on the table.

Why AI Matters for Valuation

Valuation in the technology sector is fundamentally tied to growth potential, defensibility, and efficiency. AI directly influences all three:

• Growth Potential: AI-powered features—such as personalization, predictive analytics, or workflow automation—expand addressable markets and open new revenue streams. That’s why companies with clear AI narratives are pricing at significantly higher multiples. For example, AI-focused IPOs like Astera Labs went public at nearly 40.7× revenue, compared to ~11× for non-AI peers such as Rubrik .

• Defensibility: Proprietary AI models or unique datasets create moats that are hard for competitors to replicate. Investors pay up for this: PitchBook data shows AI-heavy public comps trading well above broader software averages, with private AI deals reaching a median EV/Revenue multiple of 25.8× versus a SaaS median of ~7× .

• Efficiency & Margins: AI-driven automation reduces costs and improves scalability. PwC research shows AI-intensive sectors saw 4.3% productivity growth between 2018–2022, compared to just 0.9% in less AI-exposed sectors . These efficiency gains translate into stronger margin profiles, which directly support higher valuation multiples.

In practice, the difference is real: a company with $50M ARR valued at the SaaS median (7× ARR = $350M EV) might command 9× with clear AI leverage ($450M EV). For firms that prove AI leadership comparable to top-tier peers, the uplift can push valuations into the $1B+ range .

The Risk of “AI Blind Spots”

Despite the hype, many companies still underestimate how AI could enhance their products. Some hesitate to revisit roadmaps, worried about cost or complexity. Others assume investors won’t value AI unless it is transformational. But evidence suggests even incremental applications—like smarter customer support, AI-assisted lead scoring, or productivity features—are influencing multiples.

With nearly 50% of US VC mega-deals ($500M+) in 2024 going to AI companies, and 46% of total startup funding flowing into AI, investors are signaling that they actively seek AI exposure . Companies without an AI story risk being benchmarked against peers who are—and being penalized.

Revisiting the Product Roadmap

The question executives should ask is not “Can we afford to add AI?” but “Can we afford not to?”

Revisiting the product roadmap with an AI lens is now a strategic imperative. This means:

• Assessing Core Workflows: Where can AI drive measurable productivity or customer value?

• Leveraging Proprietary Data: How can internal data fuel differentiated models that create moats?

• Future-Proofing the Business: Which AI-driven innovations will position the company to lead the next cycle, not lag it?

With AI adoption now at ~72% of enterprises worldwide (McKinsey, 2024), the expectation has shifted: AI is table stakes .

The Bottom Line: AI as a Valuation Catalyst

In today’s deal environment, AI isn’t just a buzzword—it’s a valuation catalyst. Companies that integrate AI meaningfully into their tech stacks are rewarded with:

• Higher growth projections (via expanded TAM and faster adoption)

• Stronger competitive moats (via proprietary data and defensible AI features)

• Richer valuation multiples (a “turn or two higher,” translating to tens or even hundreds of millions in enterprise value)

Those who ignore AI risk being priced as laggards in a market where capital is disproportionately flowing to AI-driven businesses.

The message is clear: revisit your product roadmap through the lens of AI. The upside in valuation is real, and the cost of inaction may be far greater than you think.

Sources: McKinsey & Company (Quantum Black), Pitchbook, Bloomberg, Goldman Sachs Research, Bain and Company, Aventis Advisors, PwC