AI Agents are everywhere: A field guide to what's actually working

If you're building an AI agent, you're not alone.

After working with hundreds of agent companies at Paid, we've seen a clear pattern emerge. The most successful agents aren't trying to do everything for everyone. They're solving specific problems for specific industries.

Here's what's actually working in the wild.

🏭 Industry-Specific Powerhouses

These agents don't just add AI features to existing workflows. They completely automate entire job functions.

Mortgage processing companies like Alpha7x handle the full pipeline from application to approval. One agent, end-to-end automation.

Insurance operations have massive appetite for agents. Claims processing, underwriting decisions, policy renewals. Companies like Gradient AI and Quandri are replacing entire departments.

Legal automation is heating up fast. Contract generation, document review, paralegal research. Lawhive processes thousands of legal documents daily with their agents.

💡 Pick an industry with expensive labor doing repetitive work. Build agents that deliver the same outcomes at 70% lower cost.

🗣 Voice Agents Are Taking Off

Voice technology finally works well enough for production use. We're seeing agents handle complex conversations across industries.

Restaurant ordering agents like Kea take phone orders during rush hours. No more missed calls during peak dinner time.

Logistics negotiations through HappyRobot. Their agents call truckers, negotiate rates, book loads. They're processing thousands of calls daily.

Automotive dealerships use Fuzey for customer communication. Service reminders, appointment scheduling, follow-up calls.

💡 Voice agents work because customers already expect phone interactions in these industries. The friction is lower than you'd think.

💼 Sales Operations Revolution

Sales teams were early adopters. The workflows are predictable, the ROI is clear.

AI SDRs from Artisan and Sailes handle prospecting, outreach, and follow-up. They're booking qualified meetings at scale.

Sales intelligence agents like Aomni provide real-time prospect research. No more generic email templates.

Training simulations through Hyperbound let reps practice with AI buyers. They're getting reps ready for complex enterprise deals.

💡 These agents integrate with existing CRM workflows. Sales teams don't need to change how they work.

⚙ Process Automation Specialists

Some of the most profitable agents handle very specific business processes.

Government contracting with American AI Logistics. They automate proposal generation for federal bids. One agent, millions in contract value.

Debt collection through Bircle. Multi-channel recovery across email, SMS, and voice. Better outcomes than human collectors.

Procurement automation with companies like Kavida. Purchase order processing, vendor management, approval workflows.

Fleet management through RubyFleet. Route optimization, maintenance scheduling, driver communication.

💡 These agents succeed because they solve painful, expensive problems that businesses already understand.

📊 The Data Intelligence Layer

Smart companies are building agents that make sense of business data.

Causal AI from Causalens helps understand cause-and-effect in business metrics. Not just correlation.

Explainable AI through ExplainX makes AI decisions transparent. Critical for regulated industries.

Data storytelling agents automatically generate reports and insights from raw data.

💡 The opportunity is huge. Most companies are drowning in data but starving for insights.

🔒 Security and Compliance

Security agents are growing fast. The use cases are clear, the stakes are high.

Autonomous penetration testing with XBOW. Continuous security assessment without human pen testers.

Threat intelligence agents detect disinformation and security threats in real-time.

💡 Security budgets are large, and CISOs understand the ROI of automation.

🛠 Developer Tools

Technical teams are building agents to automate their own work.

Code generation through Engine Labs and Qodo. Agents that write, test, and deploy code.

Browser automation with Magical and OpenAI Operator. Universal workflow automation across any web application.

No-code platforms like OmniMind democratize AI development for non-technical teams.

💡 Developers building tools for developers creates a natural feedback loop for improvement.

🌱 Sustainability and GreenTech

Environmental compliance is driving agent adoption.

Net zero reporting with Twin4Green. Energy management and sustainability metrics.

Solar installation design through SuntropyAI. Automated renewable energy planning.

Digital twins with IoT integration for real-time environmental monitoring.

💡 Regulatory requirements make these agents must-haves, not nice-to-haves.

📈 Marketing and Advertising

Marketing agents are solving attribution and personalization challenges.

Privacy-first advertising with Crumbless. Cookieless targeting that actually works.

Programmatic job advertising through Wonderkind. AI-generated recruitment campaigns.

Cold email automation at scale with Salesforge. Personalized outreach without the spam.

💡 Marketing budgets are under pressure. Agents that deliver measurable ROI get renewed.

What we’ve learned

After working with hundreds of agent companies at Paid, three patterns stand out:

Narrow focus wins - the most successful agents solve one specific problem extremely well. Don't try to be everything to everyone.

Industry expertise matters - the best agents are built by teams who understand their target industry deeply. Technical excellence isn't enough.

Pricing drives adoption - agents priced like tools get treated like tools. Agents priced like outcomes get renewed like essential services.

💡 The agent economy is real. These companies are generating serious revenue by automating work that used to require humans.