2025 INSIGHTS REPORT
The State of Conversation Intelligence
Intro
In 2025, conversation intelligence has made its way to the center of product roadmaps across industries, sectors, and use cases.
Startups and enterprises alike are now embedding conversation intelligence into their products at lightning speed to generate unmatched customer insights, automate and improve workflows, and drive measurable business outcomes. From post-call summaries to real-time coaching, 76% of respondents said conversation intelligence is embedded in more than half of their customer interactions.
We surveyed industry-leading founders, product leaders, and engineers to find out how they’re leveraging conversation intelligence today, what challenges they're facing, and where they see this burgeoning tech going next.
We surveyed industry-leading founders, product leaders, and engineers to find out how they’re leveraging conversation intelligence today, what challenges they're facing, and where they see this burgeoning tech going next.
CHAPTER 1
Something to talk about
80%
Of respondents integrated conversation intelligence more than a year ago.
Conversation intelligence is no longer a future bet anymore—it’s business-critical infrastructure.
In 2025, teams aren’t just experimenting with a single conversation intelligence use case, they’re scaling it across departments.
In 2025, teams aren’t just experimenting with a single conversation intelligence use case, they’re scaling it across departments.
More than 80% of respondents integrated conversation intelligence into their stack over a year ago, and nearly half say it now powers the majority of their customer interactions.
What started as basic transcripts and post-call summaries is now rapidly evolving into a sophisticated engine for insight, efficiency, and growth. From sales floors to support desks to product teams to compliance leaders, conversation intelligence is being used to automate work, coach agents, uncover trends, and deliver better outcomes at scale.
What started as basic transcripts and post-call summaries is now rapidly evolving into a sophisticated engine for insight, efficiency, and growth. From sales floors to support desks to product teams to compliance leaders, conversation intelligence is being used to automate work, coach agents, uncover trends, and deliver better outcomes at scale.
Teams are using conversation intelligence for a variety of use cases
Additionally, over 85% of teams have integrated generative AI models—most commonly OpenAI, Anthropic, and Google—to support advanced summarization, classification, and automation use cases.
A value machine
The primary reason for the rapid rise of conversation intelligence lies in the fact that it doesn’t just drive a single point of value—it benefits teams, businesses,
and their customers in a myriad of ways.
Improved Customer Experience
Sentiment tracking and journey analysis allow companies to personalize interactions, streamline solutions, and better meet user needs with increased satisfaction rates, customer loyalty, and CSAT scores.
Enhanced Sales Performance
Teams are seeing boosted sales outcomes thanks to live agent coaching, prospect behavior insights, and risk and opportunity identification—with some respondents noting increased ACV and topline revenue growth.
Operational Efficiency
With automated workflows, call summaries, CRM updates, and task creation and routing, teams are streamlining their processes in revolutionary ways—and increasing productivity to more time for revenue-driving outputs.
Actionable Insights
Respondents value conversation intelligence for identifying trends from customer feedback and conversations and generating insights for product development, marketing, and strategic planning.
Agent Training
Real-time coaching, post-call reviews and scorecards, and helpful feedback loops improve agent outcomes, with 69% of companies citing improved customer service after implementing.
Compliance Monitoring
Automated risk detection, call monitoring, policy adherence, and even redaction help teams streamline compliance management.
Top features driving these outcomes
+70%
More than 70% reported a measurable increase in end-user satisfaction, with some seeing 50%+ gains.
No matter how advanced a conversation intelligence strategy may be, every fancy feature or analysis backs up to the accuracy of a transcript.
If the words are wrong, the outcomes are too.
Industry-leading conversation intelligence tools rely on industry-leading accuracy—and partners like AssemblyAI allow leaders to power their conversation intelligence with the most accurate speech-to-text on the market.
If the words are wrong, the outcomes are too.
Industry-leading conversation intelligence tools rely on industry-leading accuracy—and partners like AssemblyAI allow leaders to power their conversation intelligence with the most accurate speech-to-text on the market.
CHAPTER 2
The future is in real time
Conversation intelligence will move from post-call analyses and insights toward a real-time, scale-creating, efficiency machine.
Jason Tatum
VP of Product at CallRail
If there’s one thing we heard loud and clear, it’s that real-time capabilities are the next requirement. Whether live transcription, in-the-moment coaching, or agentic workflows, the shift is already underway. And it’s not just about speed. Real-time conversation intelligence also means better customer experiences, smarter teams, and more open doors in all directions.
The next iteration of conversation intelligence won’t just analyze what happened—it will guide what happens next in real time.
The future is also cross-functional
Conversation intelligence isn’t just evolving—it’s expanding. What first started as a sales tool has quickly become a cross-functional powerhouse for teams across industries and disciplines.
We'll see it move from early adopters to a deep early majority. It will become less of just a sales thing and be more broadly used across most functions.
Jeff Whitlock
Founder & CEO at Grain
What other future capabilities of conversation intelligence are most exciting?
Voice agents with real-time conversation control: 61.5%
Automated quality scoring: 26.9%
Speaker recognition and voice embeddings: 50.0%
Multimodal models: 30.8%
What are your top investment priorities for the next year?
Generative AI features: 57.9%
Expanding language support: 52.6%
Adding real-time STT and agentic workflows: 47.4%
What’s driving conversation intelligence?
As conversation intelligence adoption continues to accelerate, respondents identified three key factors driving that growth—as well as the features and capabilities needed to reach those industry goals.
Driver 1
Cost reduction and efficiency gains
→
Predictions
More Automation, Real-Time Workflows, Agentic AI
“[There will be a] huge focus on real-time functionalities—coaching and so on. Also on automation—getting answers in front of people before they even think of the question.”
Galya Dimitrova
Head of Product at Jiminny
Driver 2
Advancements in AI and machine learning
→
Predictions
Better Models, More Contextual Understanding
“Strong, sustained tailwinds from improving model accuracy will bring conversational intelligence into more workflows.”
Craig Bonnoit
Co-founder at Trellus
Driver 3
Demand for better customer experience
→
Predictions
Personalization at Scale, Embedded AI Agents
“Businesses will leverage hyper-personalization using AI-driven insights to tailor customer interactions in real time, improving engagement and satisfaction.”
Rishabh Jain
Engineering Leader at Clapingo
Takeaway
No longer a “nice to have”
- Conversation intelligence is no longer confined to experimental pilots.
- The value of conversation intelligence is clear and has only served to inspire bigger and better intelligence—with an ever-widening application across use cases.
Takeaway
CI is not just a sales tool
- Modern teams are leveraging conversation intelligence for a wide range of functions—with the most common use case now being analytics and intelligence.
- This indicates a clear expansion beyond its original sales enablement days and into a core infrastructure for customer and operational insights.
Challenges: What will it take to get there?
Despite strong momentum, teams face real challenges implementing conversation intelligence, with the top 3 hurdles reported being: Accuracy, Integration Complexity, and Security & Privacy.
01
Accuracy
Transcription quality remains a primary pain point—especially in noisy environments—but is the most important requirement across all use cases. Accuracy doesn’t just impact transcripts—it determines and defines everything downstream of them too, including summaries, insights, risk scoring, sentiment, compliance, and more.
Accuracy is still a challenge—especially when dealing with different accents or poor audio quality.
— Founder & CEO
The ongoing need for a human in the loop
Because of ongoing accuracy challenges, many teams still require manual review to validate AI outputs, especially in regulated workflows.
Companies are still not confident in leaving everything to AI.
Jeff Whitlock
Founder & CEO at Grain
Real-world solution
Our conversion rate doubled after implementing AssemblyAI.
Colin Treseler
Cofounder at Supernormal
Learn how Supernormal partnered with AssemblyAI to increase transcript accuracy and ROI.
Read the full story
02
Integration complexity
Connecting conversation intelligence tools to internal systems like CRMs, call centers, or analytics stacks often proves time-intensive and brittle. Finding ways to simplify the process is key to staying nimble without compromising on quality.
Real-world solution
Partnering with best-in-class AI providers lets you serve your customers better and faster—and accelerates revenue growth. We tried to use other providers, but it was always an integration headache. With AssemblyAI, it just worked.
Krish Ramineni
Co-founder and CEO at Fireflies.ai
Learn how Fireflies simplified integration and scaled fast with AssemblyAI.
Read the full story
03
Security, privacy, and explainability
30.8% of respondents cited security concerns like data privacy and security as a significant challenge when incorporating speech recognition capabilities into their products—the third most commonly cited challenge.
Real-world solution
AssemblyAI continuously improves capabilities to protect your data and ensure the confidentiality, integrity, and availability of AssemblyAI’s systems, so you can build with confidence.
Learn more about how AssemblyAI keeps data private, safe, and secure with enterprise-grade protections.
Learn more
Takeaway
Be in it together
Challenges are a guarantee and will continue to precede progress, but the teams that prioritize strategic partnerships with industry leaders and experts will be the first to overcome them—and the first to lead the way.
Conclusion
Final Thoughts
Conversation intelligence has reached a tipping point. Companies are moving from exploration to execution, from experimentation to automation. As accuracy improves, real-time intelligence matures, and security concerns are addressed, conversation intelligence will continue to establish itself as foundational infrastructure—not just for sales or support, but for the entire customer experience.
Winning teams in 2025 and beyond will be the ones to view voice data as more than just a transcript—but as the very foundation of any successful conversation intelligence strategy. Not only will they prioritize accuracy, but they’ll choose strategic partners to help them build, scale, and improve—in real time—with confidence, reliability, and industry expertise.
Winning teams in 2025 and beyond will be the ones to view voice data as more than just a transcript—but as the very foundation of any successful conversation intelligence strategy. Not only will they prioritize accuracy, but they’ll choose strategic partners to help them build, scale, and improve—in real time—with confidence, reliability, and industry expertise.