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For years, Amplitude has empowered teams to understand how users behave — what drives engagement, what causes drop-off, and how products grow. But translating that understanding into continuous improvement has often been a slow, manual process.
Teams collect data, investigate issues, form hypotheses, test, and learn — one step at a time. The result? Valuable insights, but at the cost of time, bandwidth, and focus.
That changes now.
Amplitude has just introduced AI Agents — a system that transforms analytics from a reactive tool into a proactive teammate. Instead of waiting for you to analyze what’s happening, AI Agents analyze, learn, and act — automatically.
This marks a turning point: the era of self-improving products.
From Dashboards to Autonomous Discovery
With Amplitude AI Agents, you’re no longer limited by how fast your team can investigate and test ideas. Agents continuously monitor your product performance, detect anomalies, identify patterns, and even propose and test optimizations — all within your Amplitude environment.
Think of them as embedded analysts and growth strategists, built from Amplitude’s own playbook of best practices. While you focus on strategy, your Agents are running experiments, validating hypotheses, and surfacing the results that matter.
The shift is massive — from a single-track, manual analytics process to a multi-track, autonomous system of continuous discovery and improvement.
How AI Agents Work
Everything starts with a goal. Whether it’s improving website conversion, increasing feature adoption, or reducing onboarding drop-off — your Agent takes that objective and runs with it.
Agents analyze behavioral data, session replays, experiments, and user feedback to understand what’s working and what’s not. From there, they act: generating hypotheses, setting up tests, and proposing the next best step — just like a skilled team member would, but faster and at scale.
And you’re always in control. You decide what level of autonomy to give your Agents, setting guardrails to match your comfort and governance needs.
Specialized Agents for Every Growth Challenge
Amplitude’s AI Agents come pre-built for specific objectives across the customer journey:
- Conversion Agent – Detects funnel drop-offs, runs root cause analysis, and suggests or runs A/B tests to fix friction points.
- Onboarding Agent – Identifies where new users struggle, launches targeted in-app guides, and collects direct feedback for continuous improvement.
- Feature Adoption Agent – Surfaces who’s engaging with new features and why, then recommends ways to boost adoption across cohorts.
- Monetization Agent – Recognizes when users are ready to upgrade or purchase and triggers personalized nudges at the right moment.
Each Agent operates as a specialized expert, informed by Amplitude’s extensive dataset and customer learnings.
Why This Matters
Most analytics platforms stop at insights. They tell you what’s happening — and leave you to figure out the rest.
Amplitude’s AI Agents go further:
- They learn from your data continuously.
- They act, not just observe.
- They work autonomously, around the clock.
- They adapt to your workflow and level of trust.
For companies struggling to bridge the gap between knowing and doing, this is a game-changer.
Instead of dashboards that show problems, you now have teammates that solve them.
The Future: Self-Improving Products
For over a decade, Amplitude has helped companies understand their users. With AI Agents, they’re now helping companies improve their products automatically.
It’s the next step in the evolution of analytics — from insight to intelligent action.
As more teams adopt AI Agents, we’ll see a new category of digital experiences emerge: self-improving products that analyze, adapt, and optimize continuously — without waiting for the next sprint.
What This Means for Growth Teams
At Adasight, we see this as one of the most significant advances in product analytics since the rise of event-based tracking.
Amplitude AI Agents don’t just make analytics faster — they make it smarter and more operational. They close the loop between insight and execution, freeing up teams to focus on strategy and innovation.
If you’re building or scaling a growth function, this is the moment to start thinking about how automation can augment your analytics operations — and how AI can help you achieve faster, data-driven decisions at scale.
