5 AI-Powered Workflows to Help You Unlock RevOps Efficiency

Revenue operations (RevOps) is evolving fast, and artificial intelligence (AI) is at the forefront of this transformation. But where do you start? In this session, Jake Obremski, CEO and Co-Founder at Swyft AI, and Lisa Nikolau, RevOps Lead at Gatekeeper, break down five AI-powered workflows that can help streamline processes, enhance data accuracy and drive revenue efficiency.

1. Automating CRM Updates for Better Data Hygiene

One of the biggest RevOps challenges is maintaining clean, accurate CRM data. AI can significantly reduce manual efforts in keeping customer data up to date.

• AI-powered enrichment tools like Clay help with contact updates, ensuring you’re not reaching out to outdated emails
• Meeting and email transcription AI captures key insights from customer interactions and automatically updates CRM records - reducing admin work and eliminating human bias
• Duplicate detection and merging can be streamlined using AI models that analyze multiple data points to suggest accurate record consolidation

“AI removes bias and ensures that CRM data reflects reality, not just a salesperson’s gut feeling.” – Jake Obremski, CEO and Co-Founder at Swyft AI

For more on the AI impact on RevOps, check out this podcast episode with Jake Hofwegen, the VP of RevOps at Contentful.

2. Automating Sales to Customer Success Handoffs

The transition from sales to customer success can often feel clunky and unstructured. AI can bridge this gap by ensuring a seamless handoff with complete, accurate information.

• AI-generated handoff summaries compile key sales conversations, deal terms and customer goals into structured reports
• Customer onboarding plans can be automatically populated based on past interactions, reducing redundant questions and improving customer experience
• Risk flagging allows AI to detect potential issues in account transitions, such as misalignment between expectations and product capabilities

“AI lets us capture important customer context at the moment of sale—so three years down the line, we still know exactly why they bought.” – Lisa Nikolau, RevOps Leader at Gatekeeper

This blog post on Managing the Sales to Customer Success Handoff offers additional strategies to improve this crucial transition, ensuring smoother onboarding and long-term retention.

3. Capturing Expansion Opportunities Automatically

Expansion opportunities often slip through the cracks when reps rely on memory or manual tracking. AI can proactively surface signals for potential upsells.

• Call and email analysis can detect mentions of new team hires, upcoming projects or shifting priorities - indicating a need for additional products or services
• AI-driven alerts notify account managers when an expansion opportunity is detected, reducing the chances of missing a revenue-driving conversation
• Automated deal creation can be triggered based on predefined criteria, ensuring every expansion lead gets immediate follow-up

“AI helped one of our customers source a $250,000 expansion opportunity that otherwise would have gone unnoticed.” – Jake Obremski, CEO and Co-Founder at Swyft AI

4. Finding Case Study Inspiration with AI

Your best marketing asset is happy customers, but finding compelling success stories can be time-consuming. AI makes it easier to identify case study candidates.

• Conversation analysis surfaces customer quotes that highlight positive experiences and product impact
• Sentiment analysis can flag customers who express high satisfaction, making them prime candidates for case studies
• Automatic content generation turns AI-identified insights into draft case studies or testimonial snippets, saving marketing teams hours of work

“We now send customer success quotes directly to our CRM, making it easy for marketing to extract impactful stories.” – Lisa Nikolau, RevOps Leader at Gatekeeper

For those thinking about the intersection of Marketing Automation and CRMs, check out our blog post What CRM Admins Should Know About Marketing Automation.

5. AI-Enhanced Data-Driven Decision Making

AI isn’t just about automation—it’s about improving the way RevOps leaders make decisions. By leveraging AI for predictive insights, RevOps teams can optimize their strategy.

• AI-powered forecasting identifies trends and potential revenue risks before they impact the bottom line.
• Churn prediction models analyze customer behavior to alert teams when proactive retention efforts are needed.
• AI-enhanced territory planning ensures reps are working the right accounts at the right time.

For a closer look at AI-driven forecasting and decision-making, check out this RevOpsAF Podcast Episode with Jake Hofwegen, VP of RevOps at Contentful, about the impact AI is having on Revenue Operations.

“Instead of digging through spreadsheets, AI helps us instantly see the big picture and make data-driven decisions faster.” – Jake Obremski, CEO and Co-Founder at Swyft AI

The Future of AI in RevOps

AI is already reshaping RevOps by automating tedious tasks, improving data quality and uncovering revenue opportunities. Whether you’re just starting with AI-powered workflows or looking to scale, these five areas are great places to begin.

Looking for more insights on AI in RevOps? Check out our blog and join the community.