The RevOps world is once more abuzz with excitement!
A recent LinkedIn "Jobs on the Rise" post — the social media giant's yearly report on emerging job trends— underscored the growing demand and recognition for skilled RevOps leaders, with "Head of Revenue Operations" cracking the top five for two years in a row. (The only job title of all job titles to claim that victory, I should add.)
This rising prominence of the function isn't surprising to us here at Rattle: We hear it all the time. RevOps are increasingly expected to take ownership of new capabilities – including aspects of the growing need for AI tool adoption – to drive revenue growth and ensure operational excellence. It's a thrilling time to be in ops (honestly, really!), but one filled with challenges as growth rates slow and customer acquisition costs climb higher and higher.
At the same time of this LinkedIn report, was our very own State of RevOps 2024, which asked forty-some questions to over 100 RevOps pros about what they're seeing, feeling, fearing, and the like. This year, given the hype around AI, we centered a lot of our queries around the AI world and found quite a few striking/standout facts (though it was only one of six sections so check it out for other stuff, too).
Anyway... so what did we find?
The AI Revolution, but make it for squeamish RevOps
With AI tools gaining traction pretty much everywhere in the world (including an internal favorite: AI Hairstyle Generators), we shockingly found that adoption rates for RevOps to be lagging behind.
It's true that opinions on AI aren't exactly lukewarm: people either love the possibilities or are wary of the implications. But that wasn't necessarily the issue here.
Interestingly, we found that once RevOps professionals dive into AI implementation, they become far more likely to find multiple valuable use cases. While nearly 40% of those surveyed haven't yet leveraged AI, a compelling 51% of active AI users deploy the technology for two or more purposes. This underscores the potential for wider adoption once initial hesitancy is overcome. Still, that 2 out of 5 of every RevOps pro out there hasn't found a use for it made us think: hey... maybe we should take the lead here and make some suggestions.
Overcoming Barriers to AI Adoption
While many RevOps pros recognize the long-term promise of AI (a full 82% said they saw it, at least), there are clearly hurdles to immediate adoption.
Concerns about bandwidth, budget constraints, data privacy, and an uncertain ROI loom extra-large. It's particularly important to address these barriers strategically to pave the way for smooth AI integration.
Think back to the bygone days of other now-ubiquitous technologies like CRMs. Initial resistance and skepticism were common, but the value prop gradually became too compelling to ignore. AI is likely on a similar trajectory, and RevOps leaders can expedite the process with the right approach.
In our report, David Ma, an operations leader at Zip, captured this sentiment perfectly: "We’re waiting for companies to actually stand out. There are just too many experimental things that haven't proven they work yet. We should probably pick some to experiment with, though. They just require a lot more technical expertise and are often not as valuable after the first demo."
Here's our shortlist of three of the most common worries we heard, and some quick ideas around how to get over them.
- "I have limited bandwidth and budget": Start small, yo. Choose a few high-impact, low-complexity AI use cases to demonstrate value quickly. This builds confidence and generates buy-in to expand the scope of AI initiatives. Prioritize solutions with straightforward pricing models to manage costs.
- "I have data privacy concerns": Prioritize AI tools that are associated with products that already have robust data security protocols. Work closely with your IT and legal teams to establish clear data governance policies, ensuring transparency and compliance with regulations.
- "I'm uncertain of the ROI": Okay then, quantify the potential benefits of AI through pilot projects that track key metrics. Compare these KPIs to the costs involved for a clear understanding of the return on investment. You've done this before, no doubt, with other tools. (Waiting on AI adoption because of this one seems like the least justifiable of reasons.)
6 Real-World Applications of AI in RevOps
Even as we have created our own AI tools here, and sincerely believe the tech's potential in RevOps is immense, it's important to approach all of the use cases with both enthusiasm and a healthy dose of realism.
AI has the potential to absolutely transform the way RevOps functions, particularly in these cases below. But for those who are still worried, we're including some important nuances too.
- Automated Data Entry: AI can significantly reduce manual input, but ensuring data quality is essential. Prioritize both automation and rigorous data integrity checks to create a strong foundation for subsequent AI-powered tasks.
- Predictive Analytics: Simply put: Robots can see stuff we simply can't. Predictive analytics enables data-driven insights for proactive decision-making. When building predictive models, ensure that AI analysis is guided by your team's knowledge of your business and specific market dynamics.
- Sales Forecasting: AI-powered forecasting tools offer valuable insights. For optimal results, combine AI predictions with the analytical expertise of your team. This allows you to refine forecasts and make data-driven decisions with greater confidence.
- Personalized Content Creation: AI is constantly improving in its ability to personalize content. Use AI as a starting point to generate ideas and tailor messaging for maximum relevance. Human oversight is still key to ensuring content is compelling and aligns with your brand voice. The last thing you want is for people to think you're trying to manipulate them with bot-creatred drivel.
- AI Chatbots: Chatbots can enhance customer interactions, particularly for routine queries. For complex issues, though, a seamless handover to human agents ensures customers receive the support they need.
- Lead Scoring: AI can identify subtle patterns in lead behavior that might get overlooked in traditional scoring models. This helps refine lead qualification processes. Continually monitor and refine your AI scoring model alongside human expertise for the best results.
Two Big Takeaways To Assuage Your Fears:
1) Data Quality is Everything: Across all AI use cases, having accurate, well-structured data is non-negotiable. Invest in data governance measures to ensure your AI initiatives have a rock-solid foundation.
2) AI Enhances Human Capabilities: View AI as a powerful tool for boosting productivity and efficiency. Let it handle repetitive tasks and surface patterns humans might miss. The best results come from a blend of human's expertise and AI's analysis.
The Future of AI in RevOps is the Future of RevOps
The journey of AI in RevOps, just like the journey of RevOps itself, has only just begun. That makes all of this uncertainty fun, we think.
As AI technologies mature, their applications will become increasingly sophisticated, transformative, and even scary. But you're a smart, strong, sophisticated human yourself. And to be frank: it's no match for you.
The key to success lies in continuous learning, experimentation, and adaptation — and that means RevOps teams must stay current with AI trends, actively seek out use cases to test in the light of day.
You must align with your specific needs, and approach implementation with a clear understanding of both the potential benefits and the importance of human-guided processes.
RevOps friends: AI is here to empower you. By embracing it as a strategic partner, you and your team can up-levels efficiency, insights, and customer-centricity. This translates into streamlined operations, optimized decision-making, and a competitive edge in a world where we all sorely need it.
And if you're looking to find out more on howAI can help you and your team: Book a demo. Seriously. We'd love to show you how hundreds of high-performing teams like Qualified, Gong, and more have used our Meeting Intelligence tool to save time and bolster collaboration, and do so with literally the littlest risk imaginable.
