New research underscores the critical need for CIO-CRO alignment and emergence of ‘Revenue Architects’ to unlock AI’s full value
A new research report from Clari Labs reveals that although Artificial Intelligence (AI) is widely acknowledged as a transformative force for enterprise revenue growth, 78% of enterprises are still in the early stages of AI adoption, and a staggering 67% don’t trust the revenue data AI depends on. The report highlights a pressing need for organizations to fundamentally rethink how they run revenue operations if they are to unlock the full potential of AI and intelligent agents.
“Most CIOs lack the data and context to answer the fundamental question: who did what, when, and what was the outcome? Without Revenue Context, AI will fail them.” — Andy Byrne, CEO & Co-Founder, Clari
CIO + CRO: The New Revenue Dream Team
The study emphasizes that enterprise AI success now hinges on a strong alliance between the Chief Information Officer (CIO) and the Chief Revenue Officer (CRO). These two leaders must co-author a new operational model that blends data, guided workflows, AI, and ‘Revenue Context’—a detailed understanding of who did what, when, and with what outcome.
As CIOs become more involved in driving revenue outcomes, they are increasingly asking three key questions:
- What is the current state of AI adoption for revenue?
- Where are their peers succeeding—and failing?
- What foundational capabilities are truly required to scale AI effectively?
To answer these, Clari Labs surveyed 400 revenue leaders—CROs, CSOs, and RevOps heads—from enterprises with over 1,000 employees across North America.
The Rise of the Revenue Architect
The research finds enterprises are creating new roles and structures to scale AI effectively:
- 52% plan to hire sales consultants with AI expertise.
- 46% are expanding their Revenue Operations (RevOps) teams to include AI skills.
Enter the Revenue Architect: a strategic leader tasked with preparing the enterprise to scale AI for revenue. This role is responsible for data trust, system alignment, and ensuring execution consistency across all go-to-market teams. These architects are key to enabling AI agents to operate with confidence—arming them with the context needed to guide decisions and optimize outcomes.
The State of AI for Revenue
Despite early enthusiasm, the broader market still lacks the infrastructure required for AI to succeed at scale:
- 67% of leaders don’t trust their revenue data.
Revenue data remains scattered across CRMs, spreadsheets, emails, BI systems, and siloed tools. This fragmentation leads to blind spots, hinders visualization, and erodes confidence. - 49% discover revenue risks only after missing targets.
CRMs and spreadsheets offer incomplete pictures, while activity and conversational data sit unused in silos. Most teams lack the operational rigor to trace actions to outcomes. - 67% of North American enterprises missed their 2024 revenue goals.
Yet, 91% remain optimistic about 2025 — a confidence that hinges on fixing fundamental flaws in data trust and team execution. - 40% say reps are working on the wrong accounts, and
64% report up to 30% pipeline loss due to poor handoffs, missed signals, and siloed operations.
These gaps are precisely where AI can help—surfacing insights, guiding reviews, and driving consistent account planning. But AI adoption faces one major barrier: frontline seller distrust.
Winning Trust at the Frontline
The biggest blocker to AI success is a lack of trust from sales reps. Many AI tools today offer narrow, fragmented suggestions that miss the strategic bigger picture. Sellers feel overwhelmed by irrelevant prompts and disconnected insights.
Clari’s research argues that true guided selling isn’t just automation—it’s about equipping reps with the same strategic visibility as a CRO, helping them make smarter decisions, and enabling precise execution across the revenue cycle.
The Cost of Missing Targets
There are real consequences to missed revenue. 43% of leaders say failure to hit targets leads to job cuts. To avoid that, 30% of revenue leaders plan to increase AI investments in 2025. Their goal: deploy AI to drive structured, predictable growth through better pipeline reviews, forecasting, and team alignment.
Unlocking Revenue Context™
To tackle these systemic issues, Clari introduced Revenue Context™ — the industry’s first enterprise-scale platform designed to enable both human and AI agents to collaborate intelligently across the revenue process.
Revenue Context captures and organizes all data signals across deals, reps, products, regions, and more into Clari’s revenue data platform — which already manages over $5 trillion in enterprise revenue.
In doing so, it empowers Revenue Architects to orchestrate their teams and AI agents with confidence — ensuring every decision is grounded in data, aligned to strategy, and executed at scale.
