In episode five of our podcast, learn how an AI expert approaches the adoption and concerns of generative AI in business today.
AI development continues at a breakneck pace, with the number of use cases increasing by the day. This raises the question for many Go-to-Market (GTM) leaders: how do we use AI to help sales? How do we ensure smooth adoption of AI? And what value does it bring to the business?
In this episode of the GTM Value Creation Corner Podcast, SBI Managing Director of Talent Services, Ray Makela, meets with Conor Grennan, Head of Generative AI at NYU Stern School of Business to take a deep dive into the state of generative AI today, the use cases and considerations in business.
With the prospect of higher efficiency and stronger messaging, companies and GTM leaders have much to gain from effective adoption of generative AI into their workflows. But while many leaders are interested, few have made the jump into making it work for them. GTM leaders will need to overcome that initial resistance and enable effective AI use.
Augmenting the sales engine with AI
For Conor, generative AI models such as large-language models (LLM) are more than just efficiency drivers and automation. He believes that it is most effective when GTM leaders use it as a reasoning tool to help them augment their existing capabilities.
While many companies are familiar with AI-based solutions, generative AI adopts a different approach to solving issues or enabling productivity.
“What this is doing is really taking the user interface off and allowing you to use, you know, anything you know to use it for anything you have. It's sort of a solution without a problem,” said Conor.
“And what generative AI is so outstanding at is actually augmenting what you do well.”
In sales functions, generative AI can play critical roles in helping sellers create focused messaging and make tactical plays in negotiations. By setting out themes and personas, generative AI can create targeted pitches for near infinite focus groups, providing ample opportunity for sellers and GTM leaders to practice skills in a realistic yet safe environment.
But what about privacy concerns? Many companies are wary of uploading their data to an AI model such as ChatGPT, citing concerns with legal regulation and data confidentiality. Conor believes that privacy concerns are typically exaggerated.
“It's not like if you upload your company secrets, you've left it on the table in Starbucks and somebody now has come along and taken it. It's just not how the system works. The system will have worked by processing all that data and seeing, oh, here's how words fit together, here's how people talk. It doesn't go into some repository that somebody else can take down.”
Careful adoption of AI with clear guardrails seems to be the way forward. But for many companies, the first step would be the most challenging. By starting small and simple, companies will quickly see the benefits manifest in their workflows.
“The more you use it, the more use cases you will come up with, because you're the expertise and all this really does is augment you. It augments your expertise.”