The Problem No One Talks About in LP Reports
Walk into most portfolio companies and you'll find the same thing: smart, capable people doing work that software should be doing. Data entry, report generation, customer ticket routing, invoice reconciliation — tasks that AI can handle in milliseconds, being done manually by people who cost £40-80k per year.
The McKinsey estimate is that 15-30% of operating capacity across most businesses is spent on automatable tasks. For a 200-person company, that's 30-60 FTEs worth of work that could be automated.
This isn't a technology problem. The tools exist. It's a deployment problem.
What "AI Transformation" Actually Means in a PE Context
There are two ways consultancies sell AI to PE firms: strategy decks and actual deployment.
Strategy decks tell you where AI could help. They're useful for prioritisation, but they don't move EBITDA.
Actual deployment means:
- Mapping current workflows — where time is being spent, what's repetitive, what has high error rates
- Building automations — connecting existing tools (CRM, ERP, email, spreadsheets) into automated pipelines
- Deploying AI agents — software that can take actions, not just generate text
- Driving adoption — making sure staff actually use the tools, with training and change management
The firms winning on AI aren't the ones who commissioned the most strategy work. They're the ones who shipped the most automations.
Three High-ROI Use Cases We See Across PE Portfolios
1. Deal Origination & Pipeline Management
Investment teams spend enormous amounts of time screening opportunities manually. AI can:
- Process 10,000+ opportunities against fund criteria in 24 hours
- Auto-classify by sector, geography, revenue profile, and deal stage
- Transcribe deal calls and draft follow-up emails automatically
- Monitor portfolio companies for news and flag exceptions
We've seen teams save 10+ hours per person per month from origination automation alone.
2. Finance & Reporting Automation
Most portfolio companies have finance teams spending 40-60% of their time on data aggregation and report production. AI can:
- Pull data from multiple systems and reconcile automatically
- Generate management accounts and board packs from templates
- Flag anomalies and budget variances in real time
- Automate invoice processing and payment workflows
The ROI here is both time savings and error reduction — automated reconciliation is more accurate than manual.
3. Customer Operations
For B2C and B2B portfolio companies, customer operations is often the biggest headcount cost. AI can:
- Resolve tier-1 support tickets autonomously (refunds, order updates, FAQs)
- Route complex issues to the right human with context pre-populated
- Proactively alert customers to delays or issues before they contact you
- Analyse patterns across tickets to surface product and ops issues
One of our portfolio-type deployments lifted Trustpilot ratings from 4.2 to 4.8 and cut manual support time by 60%.
The Compounding Effect
The real power of AI automation in a PE context isn't individual use cases — it's the compounding effect across a portfolio.
If you can deploy the same automation frameworks across 5-10 portfolio companies, the learning compounds. What takes 4 weeks at company one takes 2 weeks at company five. The automations get better. The playbook gets tighter.
This is why we structure our PE engagements as portfolio-wide partnerships rather than one-off projects. The economics improve dramatically at scale.
What to Look For in an AI Partner
When evaluating AI consultancies for PE work, the question to ask is: can you show me something you've shipped?
Not a roadmap. Not a framework. An actual deployed automation — what it does, how it was built, what results it's delivering.
The firms that get results are the ones that move fast, go on-site, and treat adoption as seriously as they treat deployment.
Nihaar Udathu is Co-Founder of Squirrel AI and Head of AI at Healf. Book a discovery call to discuss AI automation for your portfolio.