The Sales Compensation Show
Inside RevOps at Sage: Sales planning, AI, and GTM's future
September 16, 2026
What does it take to run a $2B go-to-market plan when the targets need to stretch the business, the forecast needs to stay honest, and AI is starting to change how the work gets done? Dominic Ballinger, VP of Revenue Operations at Sage, joins us to share what he’s learned about setting credible growth targets, translating executive ambition into quotas and incentives, and why bad news has to be able to travel through the forecast. He also takes us inside how Sage is putting AI to work across RevOps today—and considers what comes next: jobs unbundled into tasks, pressure on seat-based SaaS pricing, collapsing GTM silos, and a bigger role for RevOps as the “revenue architect” of the business.
What does it take to run a $2B go-to-market plan when the targets need to stretch the business, the forecast needs to stay honest, and AI is starting to change how the work gets done?

Dominic Ballinger, VP of Revenue Operations at Sage, joins The Sales Compensation Show to share what he’s learned from operating at this scale—from setting credible growth targets and surfacing bad news early to translating executive ambition into quotas and incentive plans the field can actually execute against.

He also takes us inside how Sage is putting AI to work across RevOps today, including structuring AI initiatives around real internal customer problems and building in a week what once could have taken months.

Tune in to hear Dom's take on:

→ Why RevOps is uniquely positioned to become the revenue architect of the AI era
→ How AI will likely unbundle jobs and collapse GTM silos
→ What separates a credible stretch target from an arbitrary one
→ Why suppressing bad news can undermine forecasting and planning
→ How executive growth goals should translate into quota and incentive design
→ Why AI may disrupt the traditional SaaS seat model
→ How Sage is approaching AI inside its RevOps organization
→ Why “everyone build everything” is the wrong AI strategy


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