A New Role Emerges at OpenAI: GTM Innovation

We look at innovation as reinvention of the current state.

If we look at the history of Revenue Operations, you only have to go back about 25 years to see the emergence of the function. It started with Salesforce in the early 2000s - and all modern CRMs to follow.

Pre-Salesforce, there wasn’t really Sales Ops or Rev Ops because existing tooling prevented companies from having the visibility needed for a true GTM Strategy role to exist in any meaningful way.

As Salesforce made real-time sales analytics possible for all, we saw the emergence of a data-driven, analytical Sales strategy.

This made way for modern Rev Ops and the explosion of GTM Tech innovation.

Artificial Intelligence is truly what makes the next leap possible. We will look back on today’s sophisticated Rev Ops teams as archaic with analytics that over-rely on historical trends and accuracy of human input. While we can't avoid the buzz around AI, we haven’t even begun to see the potential impacts on GTM planning and execution.

One thing is certain, though. Change is coming. But AI won’t show up as some silver bullet you switch on to solve everything. Instead, it will be methodical adoption leading to slow, compounding benefits that transform everything.

For most companies tapping into AI today, they think of themselves as the "early adopters". In reality, most in this cohort are consumed by shiny object syndrome and simply tacking AI on to narrow use cases without any holistic strategy in place.

They are primarily using it to enable existing processes - only now with the capabilities of AI - and focus on process optimization and productivity gains.

Valuable as these areas may be, it's low impact compared to the potential. Ultimately, the promise of AI in Go-to-Market is better decision making - and not just incrementally better.

But driving this kind of sustainable, lasting change requires AI to be adopted at a foundational level. It truly requires the ability to think about solving organizational challenges entirely outside the context of existing processes and systems.

GTM Innovation at OpenAI

Look no further than OpenAI to be at the forefront of GTM Innovation. While, they have an obvious advantage, we should all take note.

Their newly posted job for a Head of GTM Innovation is the leader of an “internal incubator” tasked with revolutionizing customer engagement.

This role partners with Sales, Success, Enablement, and Rev Ops functions with a mission of bringing AI into every team that engages customers. Sounds like an approach many of us understand on an intellectual level but the ability to implement it properly requires complete, unfettered buy-in to the task at hand.

At OpenAI, the GTM Innovation team is deeply embedded with internal stakeholders to understand their problems. The team conducts formal user research to fully understand the space - the kind of qualitative and quantitative analysis that goes into core Product Development, not the mere requirement gathering we often see from Business Analysts on the GTM Systems team.

From these insights, they ideate on potential solutions and create rapid prototypes to test assumptions and iterate on solutions. This seamlessly moves through a validation, synthesis, and formalization phase before more scalable solutions are designed and shipped.

Takeaways for All

This is the approach every single Go-to-Market team should take today. In theory, this is the role of GTM Systems teams - to drive Internal Product Innovation.

In reality, these teams are almost never set up for success. They are resource constrained, directed by stakeholders, and rushed to address today’s priorities - an approach that leaves little room for innovation even within the existing technology stack, let alone when it comes to the sprawl of AI innovation we're all working to understand.

This type of shortsighted, rushed approach won’t work with AI. Adopt AI at a foundational level, will require unwavering buy-in.

Budget. Resources. Time.
All 3 are non-negotiable and it's not even worth attempting without them.

Adopting AI properly and comprehensively will require unique, techno-functional strategists, who are given the time to embed within specific teams and absorb 100% of the business context and process.

Most importantly, they need the freedom of time to properly conduct user research - and to then experiment with prototypes and POCs. In the context of GTM Systems, we typically only see time spent on a Proof of Concept when the decision has been made - it's more of an MVP to help during discovery than it is a true experiment.

We're too afraid for our ideas to fail when it comes to Go-to-Market Systems today but that can't be the approach to AI - it needs to be one of curiosity and experimentation (with guardrails, of course).

I guarantee you that companies thinking this way will gain a material edge from AI, while everyone else sits around waiting on some product to hit the market that solves it all.

It’s not going to play out that way because the most sophisticated application of AI will be company specific - a more customized experience than anything we’ve ever seen.

Only the smartest minds in your company will get you there.