What CROs face leading AI experimentation

Everyone talks about the benefits of AI, wants the benefits of AI, even plans around the benefits of AI, but the revenue org is where experimentation around AI implementation actually happens.

CROs are often tasked with creating training grounds for AI adoption at their companies with little to no historic examples on how that should happen. From rethinking the traditional growth equation to reshaping teams around automated work, CROs are learning on the fly.

Revenue Brew spoke to two growth executives about best practices for creating effective AI strategies.

Solving the AI puzzle: For Matt Diederichs, VP strategic operations at conversation intelligence platform Invoca, AI has made him rethink how he organizes work on his team. He explained that the key is finding the right balance of what humans are good at and what AI is good at—and getting those pieces to work simultaneously. He also added that his role, which sits at the intersection of AI and revenue, offers a potential solution to challenges organizations face when implementing AI.

“If you get that wrong, it can be really weird and uncomfortable for everyone, but if you get it right, you end up in a situation where you’re outsourcing the things that we don’t really care if a human is doing to the AI and then using human capital for the important things,” Diederichs said.

Introducing new technology takes deliberation that often slows work down; however, without it, ineffective implementations could slow work down, too. For this reason, Diederichs recommends being pragmatic rather than swift when it comes to AI adoption.

Leading by example: For Brian Geddes, CRO at AI engagement platform AIQ, a new part of the workday involves setting aside time to experiment. It helps him keep up with new tools, and it allows him to give directive to employees once AI has been deployed.

Rather than just looking at what it can achieve, Geddes said that exploration is helpful for finding a tool’s limitations, informational or technical.

“You’re learning how these building blocks go together, and you’re learning the limits as a function of actually doing the projects,” Geddes said.

Once Geddes has identified the limitations of a tool (and has engineering create the proper safety protocols), he can feel comfortable giving these products to his team so they can further experiment. The initial research allows Geddes to be informed about how his team will approach the tools using their own curiosity.