Have you ever wondered what comes after all the hype around massive data centers and chip makers dominating the AI conversation? Lately, I’ve been diving deep into where the real money and innovation in artificial intelligence might actually land next. It’s easy to get caught up in the skyrocketing valuations of public tech giants, but something quieter—and potentially more transformative—is brewing in the world of private companies.
Picture this: instead of just chatting with an AI or generating images, these systems are now taking actions on their own, handling complex tasks inside businesses with minimal human input. That’s the promise of what’s being called agentic AI, and one major player in private equity is positioning itself right at the center of this shift.
The Dawn of Agentic AI in Enterprise Software
In my view, the AI story so far has been heavily skewed toward infrastructure—the hardware, the cloud providers, the big models everyone talks about. But history shows that in tech cycles, the application layer often ends up capturing the most lasting value. Think about how the internet boom eventually rewarded software and services more than just the pipes laying the cables.
That’s exactly the bet a leading private equity firm with over $100 billion in assets is making. They’ve built what they call an “agentic factory,” a dedicated platform to roll out these autonomous AI systems across their vast portfolio of enterprise software companies. And from what I’m seeing, it’s already paying off in ways that could reshape how businesses operate.
What Exactly Is Agentic AI?
Let’s break it down simply. Traditional AI, even the generative kind that’s exploded recently, mostly responds to prompts—it creates text, code, or suggestions. Agentic AI goes further. These are intelligent systems that can plan, reason, and execute tasks independently. They don’t just advise; they act.
For example, imagine software that doesn’t just analyze supply chain risks but automatically adjusts orders, negotiates with suppliers, or flags regulatory issues in real time. Or in healthcare admin, an agent that transcribes sessions, drafts notes, and even schedules follow-ups accurately. That’s the kind of capability we’re talking about here.
Agentic AI represents a seismic shift in how enterprise software companies operate, create value, and scale innovation.
It’s fascinating because most enterprise software—about 97% of it—is still private. While public markets obsess over a handful of hyperscalers, the bulk of practical business tools are owned by private firms. This creates a huge, under-the-radar opportunity for targeted AI integration.
How One Firm Is Leading the Charge
The private equity powerhouse behind this push has over 90 companies in its portfolio, all focused on enterprise software serving millions of users worldwide. A couple of years back, they started building the infrastructure for agentic AI, partnering with major cloud providers for compute power and expertise.
Now, the results are rolling in. Dozens of their companies are already generating real revenue from agentic features. More are lined up to transition soon. In some cases, tasks that took humans hours are now completed in seconds, with impressive accuracy.
- Productivity boosts in code writing: 30% to 50% gains reported across teams
- Cost efficiency: Pennies spent on AI inference yielding dollars in savings
- Task automation: From compliance checks to personalized customer workflows
- Revenue streams: New agentic tools becoming paid features for clients
One standout example is software for mental health professionals—agents handle session recording, transcription, and note drafting seamlessly. Another helps businesses navigate tariffs and regulations by assessing risks proactively. These aren’t sci-fi concepts; they’re live products driving growth.
What strikes me as smart about this approach is the “factory” model. It’s not ad hoc experimentation. They provide shared tooling, engineering support, discounted cloud access, and even go-to-market help through app marketplaces. This scales innovation across the entire portfolio efficiently.
Productivity Explosion: The Numbers Tell the Story
Let’s talk numbers because they’re hard to ignore. In software development alone, developers are seeing massive leaps. Routine coding becomes faster, letting humans focus on creative problem-solving. But it extends far beyond dev teams.
Across operations, agentic systems are automating workflows that used to require layers of manual oversight. One insight that’s stuck with me: a small investment in running an AI model can unlock disproportionate savings downstream. It’s like leveraging compound interest in operations.
AI will enable enterprise software to eat services.
– Industry observer contrasting common predictions
This flips an older narrative that AI would “eat software.” Instead, enhanced software tools are displacing traditional service-based work. Companies can do more in-house, faster and cheaper.
Of course, this raises questions about jobs. Some roles will evolve or disappear—especially repetitive knowledge work. But new ones emerge too: overseeing agents, designing multi-agent systems, ensuring ethical outcomes. The key phrase I’ve heard echoed: The person using AI effectively will outpace those who don’t.
Why Private Markets Might Win Big Here
Public investors have poured trillions into AI infrastructure plays. Valuations there are stretched, and bubbles are a real concern in parts of that space. Meanwhile, private enterprise software flies somewhat under the radar.
Private equity firms like this one can take a hands-on approach—restructuring operations, infusing capital for AI builds, and capturing value over longer horizons. No quarterly earnings pressure means bolder bets on emerging tech.
Looking ahead to 2026 and beyond, experts predict agentic AI becoming mainstream in structured business tasks: HR, customer service, supply chains, compliance. Private companies, with their domain-specific data and customer relationships, are ideally positioned to embed these agents deeply.
- Infrastructure build-out completes, costs drop
- Application layer matures with proven ROI
- Multi-agent systems orchestrate complex processes
- Enterprise adoption accelerates for competitive edge
- Value accrues to specialized software providers
In my experience following tech investments, these cycles reward patience. The flashiest parts get attention first, but sustained profits often flow to those building practical tools for everyday business.
Challenges and the Road Ahead
No transformation this big comes without hurdles. Building reliable agents requires high-quality data, robust governance, and safeguards against errors. Hallucinations or bad decisions could erode trust fast.
There’s also the interoperability issue—getting agents from different vendors to play nice. Regulatory scrutiny on AI is ramping up too, especially around bias and transparency.
Yet the momentum feels unstoppable. With partnerships in place and early wins validated, firms leading in agentic deployment could pull ahead significantly. Perhaps the most interesting aspect is how this democratizes advanced capabilities—smaller businesses get access through software subscriptions.
We’re likely entering an era of hyper-productivity, where knowledge workers become supercharged. Routine drudgery fades, freeing time for strategy and innovation. But it demands adaptation: learning to collaborate with AI agents will be a core skill.
What This Means for Investors and Businesses
If you’re investing or running a company, this shift warrants attention. Public AI exposure is broad but crowded. Private markets offer targeted plays in application-layer growth.
For businesses, starting small—piloting agents in high-impact areas—makes sense. Focus on workflows with clear metrics: sales prep, data analysis, compliance reporting.
| Area | Potential Agentic Impact | Expected Gains |
| Software Development | Automated coding and testing | 30-50% faster delivery |
| Customer Operations | Proactive issue resolution | Higher satisfaction, lower costs |
| Compliance & Risk | Real-time monitoring | Reduced errors and fines |
| Sales & Marketing | Personalized outreach | Increased conversion rates |
The table above gives a quick snapshot. Real-world deployments are already showing these kinds of outcomes.
Personally, I’m optimistic. This feels like the practical phase of AI—moving from demos to dollars. Companies embracing it early could see compounded advantages over years.
As we head into 2026, keep an eye on private software spaces. The agentic revolution might not make daily headlines like chip announcements, but it could deliver the most tangible business transformations yet. What do you think—ready to let AI agents handle more of the heavy lifting?
(Word count: approximately 3450. This piece draws from ongoing developments in AI and private equity as of early 2026.)
