introduction
- AI Agents are the next wave of Artificial Intelligence. Unlike traditional AI tools that wait for user input, these systems take autonomous action
- Key use cases for PE’s and PortCo’s include customer retention, customer journey attribution, business intelligence, and workflow automation
- While the benefits are compelling, effective deployment demands rigorous oversight and thoughtful governance
What are AI Agents?
AI agents are intelligent systems built on large language models (LLMs) that can operate independently toward defined goals. Instead of simply responding to user prompts, agents:
- Plan their own steps to reach a goal
- Interact with tools and databases
- Take actions like sending emails or pulling reports
- Learn from past interactions to improve performance over time
This next step in AI evolution is being actively explored and implemented by leading companies across sectors including private equity, SaaS, and financial services.
What Makes Agents Different from Traditional GenAI?
Most of us are familiar with tools like ChatGPT, which generate text or other forms of content based on user prompts. But AI agents go further:
- Autonomous execution: Agents don’t need step-by-step instructions. Set a goal (e.g., “detect churn risk in our CRM”) and the agent determines how to achieve it.
- Tool integration: They connect to platforms like Outlook, Slack, HubSpot, and internal databases.
- Decision-making: They evaluate options and choose the best course of action.
- Continuous learning: They get better over time by processing outcomes and feedback.
Real-World Use Cases in Action
CRM Monitoring and Automated Outreach
Retool and similar platforms are already using agents to monitor CRM data for signs of churn. These systems:
- Spot warning signals like inactivity or declined engagement
- Flag accounts for review
- Automatically send personalised emails or offers to re-engage users
In one case, an AI agent flagged a high-risk account three weeks earlier than a human rep would have.
Customer Journey Automation
AI agents are now playing a growing role in end-to-end customer experience management. Platforms like Beam, Voiceflow, and OneReach.ai are helping businesses automate routine but critical parts of the customer journey:
- Instantly respond to common questions (“What’s my policy status?”, “When will my order arrive?”)
- Trigger reminders and renewal messages via email or SMS
- Collect documents or confirmations automatically
- Execute service updates (e.g., changing details, rescheduling appointments)
- Seamlessly escalate complex cases to human agents with full context
This type of automation is gaining traction across industries like financial services, e-commerce, and logistics — helping reduce support costs while improving response time and consistency.
Dashboard Copilots
Traditional dashboards are powerful, but require users to dig for insights. Beam AI is pioneering AI agents that:
- Accept natural language questions (“Which region had the highest sales drop last quarter?”)
- Query live data sources
- Return answers with visual context in seconds
This not only speeds up analysis but also puts insights into the hands of more team members.
Competitor Intelligence
In private equity and strategy, staying on top of competitor moves is essential but time-consuming. AI agents like those developed by Dynamiq and Hebbia:
- Scan press releases, financial filings, and job boards
- Summarise market trends
- Alert teams when key competitors make strategic changes
The result? Faster reaction times and more informed investment decisions.
Why This Matters for Private Equity and PortCos
Agentic AI presents a new frontier for operational improvement across the portfolio:
- PortCos can cut cost-to-serve by streamlining support, reporting, and analytics
- Deal teams can automate early-stage research and target screening
- Boards gain faster visibility on key KPIs with less manual effort
The Risks: Not to Be Overlooked
1. Trust
Giving agents the power to act autonomously — especially in customer-facing roles — requires high levels of trust. A misfired email or incorrect decision could damage relationships.
2. Security
Agents often need access to sensitive data and internal tools. Without robust access controls and audit trails, they could introduce new vulnerabilities
3. Oversight
As Anthropic’s Claudius experiment showed, even advanced agents can make irrational or flawed choices. Human-in-the-loop governance remains critical.
Getting Started: Practical Tips
- Start small: Pilot agents in internal or low-risk workflows
- Monitor outcomes: Evaluate performance before scaling
- Keep humans in the loop: Ensure oversight and review
- Build safeguards: Use permissions, alerts, and version control
Conclusion: From Buzzword to Business Value
AI agents are already delivering tangible ROI. The key is knowing where they can add value — and deploying them with intention. Companies that move early, with the right controls, will gain an edge in decision-making speed, operational efficiency, and market responsiveness.
At DVS, we work with private equity firms and their PortCos to explore how agentic AI can unlock capacity, improve customer outcomes, and enhance reporting.
Let’s talk about where AI agents could make the biggest difference in your business.
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