Event Series: How to Drive GTM AI Strategy in 2025
Operations Leaders
Sales Leaders
November 21, 2023
November 23, 2023

Interview with Kanako: RevOps in an AI-driven World

Note: The following post was generated by Copy.ai, but based on the human conversation from the video above. While this post is excellent at highlighting the main points of the conversation, we highly recommend watching the entire video. 

In today's interview, we are excited to feature Kanako Tone, the Senior Manager of Revenue Operations at SmarterX. With over five years of experience in RevOps, Kanako brings a wealth of knowledge about how to optimize revenue generation and support customer success. 

More specifically, Kanako provides valuable insights into the future of Revenue Operations and how AI will shape the skills and roles within the field.

Here are the main takeaways from our conversation. 

AI is Automating Repetitive RevOps Processes

AI is rapidly taking over many of the repetitive, rules-based tasks that eat up employee time in RevOps departments. For example, AI chatbots can handle a large volume of simple customer service inquiries, freeing up human agents to work on more complex issues.

AI is also adept at swiftly processing orders and handling other repetitive workflows. 

The key to successfully implementing AI is clearly defining the specific problems you want it to solve. Not every process can or should be fully automated - there needs to be a balance between AI and human involvement.

Careful scoping ensures the technology focuses where it can make the most impact.

As AI takes over the nitty gritty skills in RevOps, the focus shifts more to understanding what needs to be done rather than how to do it. Yet humans are still needed to provide quality assurance and validate AI output. 

While the technology can take over rote tasks, human oversight remains essential.

Humans Still Needed to Oversee AI

While AI takes over many of the repetitive and rules-based RevOps tasks, human involvement remains important. Humans are needed to provide quality assurance skills to validate the output of AI systems. 

Since AI is not perfect, there needs to be a human layer defending against errors before any AI-generated work is pushed out into the world. 

Even as AI learns and improves over time, it cannot be blindly trusted. The recommendations and results produced by AI must be carefully reviewed by human experts. They can spot check the logic and outputs, making corrections where needed. This allows the AI system to continue learning from those human interventions and enhance its capabilities. 

But without that ongoing human oversight, errors could slip through which lead to downstream issues.

The ideal scenario is humans and AI working together - with people focusing on the high-level validations and strategy while enabling AI to handle the repetitive grunt work. But the humans are still required to validate that the grunt work was done properly before fully accepting the results.

AI should be treated like a "junior team member", whose work warrants oversight before being pushed into production. With humans and AI combining forces in this way, RevOps teams can operate much more efficiently and effectively. 

The AI brings scalability while the humans bring fail-safes and quality control.

There should still be a human layer of quality assurance to defend against errors before AI output is pushed out. 

AI is not perfect; blind acceptance of its results could lead to downstream issues if not properly validated. 

Humans provide empathy, nuanced judgment and discretion that AI simply cannot replicate. For example, Kanako reflected on how her challenging first job shaped her perspective on work-life balance and empathizing with reports. Her personal experience made her very cognizant of monitoring her team for signs of burnout. 

An AI system lacks the ability to pick up on these emotional cues and motivate employees accordingly. It takes human intuition.

While AI transforms RevOps processes, companies must keep the human touch front and center when implementing these technologies. The combination of human and AI is more powerful than either on their own.

Final Thoughts

AI is revolutionizing the world of RevOps by taking over repetitive, rules-based tasks like processing orders and handling simple customer service inquiries. This is freeing up human RevOps professionals to focus their time and energy on more complex, strategic initiatives. 

However, as promising as AI is, the human element remains essential in RevOps.

While AI excels at automating basic processes, it still requires human oversight and quality assurance. There should always be a human layer reviewing AI's work before it gets pushed out, since the technology is prone to errors. 

Moreover, AI cannot yet replicate core human skills like good judgment, empathy, and nuanced communication. 

As companies continue implementing AI systems, they must keep the human touch front and center. The ideal RevOps team should leverage the strengths of both AI and human employees. 

Tasks should be allocated based on which resources are best suited - repetitive and straight-forward to AI, complex and strategic to humans.

With the right balance of advanced technology and human collaboration, companies can build an efficient, productive and customer-focused RevOps function. AI and humans each have an important role to play. By combining their complementary strengths, businesses can drive revenue growth while delivering top-notch experiences.

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