Putting wind in your sales with AI

Inflexion’s latest Commercial Exchange looked at how to improve efficiency and productivity using AI across go-to-market (GTM), in practical ways that demonstrably link to business outcomes.

Over the past year, GTM teams have seen an explosion of AI products, from feature releases to “must-try” point solutions. 

“With so many AI options available, it is essential to have a strong GTM foundation in place before implementing any tools. AI is an accelerant – it helps you move faster – but if the underlying GTM foundation isn’t sound, you risk accelerating it in the wrong direction,” points out Ada Pham, Inflexion Assistant Director focused on commercial strategy. 

To explore this, Inflexion invited its portfolio to hear from Vanessa Goolsby, author of “The $100M Push” and GTM and AI growth adviser who works with PE-backed businesses. She advised on key learnings from her experience to help companies as they adopt AI to boost productivity.

1) Start with pain points and outcomes, not tools

“We’re actually not here to play with AI,” Vanessa stresses. The market is saturated with options – she pointed to analysis revealing thousands of new AI start-ups in 2025 alone — and every major platform is also rolling out AI functionality at pace. It means teams are experimenting –but possibly at the cost of efficient progress.

It is therefore important to start with clarity on what needs to change commercially. Where is the bottleneck: pipeline creation, conversion, deal velocity, onboarding, forecasting confidence, or customer responsiveness? What would “good” look like in measurable terms — higher conversion rates, reduced cycle times, fewer manual handovers, faster ramp for new joiners, or improved data hygiene?

From there, tools become the means, not the end. Vanessa shared four tenets to keep teams grounded:

• Don’t chase tools. Define the pain points, use case and outcomes first
• Use the tech stack that you already have. Go low friction first: low/no code
• Impact comes before scale. Build MVP, pilot and prove value before scaling
• Design AI for the buyer first. GTM decisions shape the buyer experience; fragmented tooling can create a disjointed customer journey.

Also consider that tool decisions made in silos can inadvertently multiply messages to customers — automated outreach, sales emails, customer success nudges — and the buyer experience can get noisy. Considering the end-to-end buyer journey as one system helps avoid “AI-enabled spam” and protects brand trust.

2) Get the RevOps foundations and ownership right

AI can amplify strengths as well as weaknesses. It means data hygiene matters a lot: if it is poor, definitions are inconsistent, or handovers are unclear, and AI will increase confusion.

That makes RevOps foundations crucial: clean CRM data, agreed lifecycle stages, consistent activity logging, and operating accountability. Clear ownership is needed to ensure shared responsibility does not slip into no responsibility.

What can work is creating small AI subgroups or champions— who can translate needs into workable pilots and then own ongoing optimisation. Once a solution is built, accountability should sit with those champions, not remain with a central “innovation” team.

3) Treat this as a people and culture change: adoption over deployment

AI in GTM is a change in how teams work, learn and make decisions, making leadership essential. Communication also matters. Teams respond differently when AI is framed as “AI-enabled human efficiency” rather than job replacement.

Adoption is often the hardest part: even strong tools may plateau at partial usage when people must actively choose to use them. Jan Beitner, Director for Data & AI at Inflexion, pointed to a key distinction: “pull” models — where individuals must remember to use AI — often lead to limited adoption. “Push” models — where AI is embedded into workflows and reveals insights automatically — are more likely to be used consistently. Orchestration tools can help bridge the gap between buying off-the-shelf and building bespoke solutions, enabling automation without requiring heavy engineering effort.