How Should Private Equity Firms in Calgary Use AI Across Their Portfolio?

Last updated: August 2026

Calgary's PE Firms Are Asking the Same Question About AI

Three different private equity firms in Calgary asked Solway the same question in the past 90 days: how do we systematically deploy AI across our portfolio companies? It's not a coincidence. McKinsey's 2025 survey shows 88% of organizations now use AI in at least one business function, and PE firms are realizing that AI readiness — or the lack of it — directly affects portfolio company valuations, operational efficiency, and exit multiples. For Calgary's concentrated PE ecosystem, where firms like Triwest, CPS Capital, and dozens of mid-market operators manage buy-and-build platforms across industries from tree care to pet food, AI has shifted from a nice-to-have technology conversation to a core value creation lever. Here's how the smart firms are approaching it.

The Valuation Impact: AI Readiness Is Becoming a Diligence Item

The biggest shift in 2025 and 2026 is that AI readiness is showing up in M&A diligence. Buyers are beginning to ask three questions that didn't exist two years ago: Does this company have an AI policy? Has the team been trained on AI tools? Is there a roadmap for AI integration post-acquisition?

A Calgary-based M&A advisor told us that in recent transactions, buyers are using AI maturity as a discount mechanism. A company with no AI policy, no training history, and shadow AI risk (employees using free ChatGPT accounts with sensitive data) gets flagged as an operational risk. The discount isn't formalized yet — but the conversation is happening, and the firms that recognize it early will protect their portfolio valuations.

PwC's 2025 analysis found that technology and AI capabilities are increasingly factored into enterprise value assessments, particularly for service businesses where labor productivity drives margins. For PE firms running buy-and-build strategies — which describes most of Calgary's mid-market PE landscape — this means AI readiness needs to be part of the 100-day plan for every new acquisition.

The Portfolio Operating Model: From One-Off to Systematic

The mistake most PE firms make is treating AI adoption as a portfolio company-level decision. Each company experiments independently, different tools get adopted in silos, and the operating partner ends up with twelve portfolio companies using twelve different approaches to AI — none of them systematic.

The alternative is what Solway calls a "portfolio AI operating model" — a standardized approach that gets deployed across every company in the portfolio, customized for each company's industry and workflows, but built on a common foundation of policy, training, and measurement.

This model has three layers. First, a common AI policy framework that covers data handling, acceptable use, tool selection, and governance. Solway's AI Policy Framework includes 14 components across three sections (Role & Purpose, Accountability & Trust, Ethical Use), each configurable on a sliding scale from Caution-Oriented to Innovation-Oriented depending on the portfolio company's industry and risk profile.

Second, a standardized training curriculum that gets every portfolio company to a baseline level of AI literacy. This doesn't mean everyone uses the same tools — a tree care company has different workflow needs than a healthcare platform — but everyone understands what AI can do, where the risks are, and how to evaluate opportunities.

Third, a measurement framework that tracks AI adoption, time savings, and operational impact across the portfolio. This gives the operating partner visibility into which companies are capturing value and which are stuck in pilot mode.

Where AI Creates Value Across Common PE Portfolio Company Types

Calgary PE firms typically build portfolios across a range of service and light-industrial businesses. Here's where AI creates the most immediate value in the company types we see most often:

For service businesses with recurring revenue (HVAC, landscaping, property management): AI streamlines scheduling, route optimization, customer communication, and quote generation. A property management company can use AI agents to handle tenant inquiries, maintenance requests, and lease renewals — reducing the administrative burden that typically requires 2-3 full-time staff.

For healthcare platforms: AI automates clinical documentation, patient intake, insurance verification, and scheduling optimization. The key constraint is data privacy — healthcare companies need strict AI policies that govern what data can and cannot interact with AI tools. Solway's Capabilities Matrix specifically addresses healthcare use cases.

For manufacturing and distribution: AI accelerates quoting, order entry, inventory forecasting, and quality inspection. One Calgary manufacturer we work with spends 300 man-hours per year on manual order entry that AI could reduce by 60-70%.

For financial services and advisory: AI enhances deal screening, due diligence research, portfolio reporting, and investor communications. PE firms themselves can use AI to process CIMs faster, build more comprehensive industry landscapes, and generate investment memos from raw diligence materials.

The Agent Revolution: What PE Firms Need to Know

McKinsey's 2025 Global Survey on AI found that 62% of organizations are at least experimenting with AI agents — systems that can plan and execute multi-step workflows autonomously — and 23% are scaling them in at least one business function. For PE firms, agents represent a step change in how portfolio companies can operate.

The practical impact is straightforward: tasks that currently require a human to orchestrate multiple steps (receive an inquiry, check availability, generate a quote, send a follow-up, update the CRM) can be handled by an AI agent working within defined guardrails. The agent doesn't replace the human team — it handles the coordination layer so humans focus on relationship building, complex problem-solving, and strategic decisions.

This matters for PE firms because agent deployment directly affects the operating metrics that drive valuations: revenue per employee, gross margin, customer response time, and operational capacity without proportional headcount growth. A portfolio company that deploys agents effectively can grow revenue 30-40% without adding proportional staff — exactly the kind of operating leverage PE firms are built to capitalize on.

The risk side matters too. In recent deal discussions, a Calgary PE firm told us that AI agent risk is starting to appear in due diligence questions. If a target company is using AI agents to handle customer-facing interactions, buyers want to understand the governance framework, the error rate, and the liability exposure. Having a documented AI policy isn't just good practice — it's becoming a prerequisite for clean transactions.

The Solway Approach: AI Clarity Sprints for Portfolio Companies

Solway's AI Clarity Sprint is a six-week engagement that gives PE firms a repeatable playbook for AI adoption across their portfolio. The Sprint follows six structured steps: a Startup and State of AI Briefing, Discovery and Baseline Scan, Team Input (via survey and workflow mapping), Executive Vision Lab, Draft Policy and Opportunity Matrix, and Leadership Wrap-Up.

The Sprint delivers three tangible outputs for each portfolio company: a co-created AI Policy Framework customized to the company's industry and risk profile, a Staff Decision Guide that answers the everyday question "Can I use AI for this?", and an Opportunity & Risk Matrix that categorizes AI opportunities into Quick Wins, Quality Lifts, Strategic Upgrades, and Not Yet.

For PE firms, the Sprint also produces a portfolio-level view: a standardized assessment of AI maturity across companies, a prioritized implementation roadmap, and a measurement framework for tracking value capture. This gives operating partners a dashboard-level view of AI adoption and impact across the entire portfolio.

Shaheer Tariq, Co-Founder of Solway, regularly delivers State of AI presentations to PE firms, M&A advisors, and investment professionals across Calgary. These briefings cover the current capability frontier, where the technology is heading, and specifically how AI affects deal flow, diligence, and portfolio operations.

CAPG Funding: How Portfolio Companies Can Offset Training Costs

Every Alberta-based portfolio company can access the Canada-Alberta Productivity Grant (CAPG) to offset AI training costs. The CAPG reimburses up to 50% of eligible training costs for existing employees ($5,000 cap per trainee per year) and up to 75% for newly hired unemployed Albertans ($10,000 cap per trainee). Each employer can receive up to $100,000 per year.

Importantly, CAPG has no minimum-hour requirement, so even a half-day workshop qualifies for reimbursement. The 21-hour minimum and formal-certification rule belong to the separate Canada-Alberta Job Grant, a different program.

For a PE firm with five Alberta-based portfolio companies, each sending 10 employees through AI training, the CAPG could reimburse up to $250,000 in aggregate — making the ROI case for systematic AI adoption across the portfolio even stronger.

AI training qualifies under the CAPG's "Digital and Technological Skills" category. Training must be delivered by a third-party provider (Solway qualifies), and applications must be submitted before training begins through the Alberta.ca portal.

The 90-Day PE AI Playbook

For PE firms ready to move from conversation to action, here's a practical 90-day sequence:

Days 1-30: Assessment. Run an AI readiness survey across all portfolio companies. Identify which companies have existing AI usage (including shadow AI), which have policies, and which have the most immediate workflow opportunities. This can be done with a simple questionnaire plus a 60-minute call with each company's leadership.

Days 31-60: Foundation. Deploy the AI Clarity Sprint at the two or three portfolio companies with the highest readiness and biggest opportunity. Establish the common policy framework and training curriculum that will scale across the rest of the portfolio.

Days 61-90: Scale. Roll out the standardized AI policy and baseline training to remaining portfolio companies. Begin tracking adoption and time savings metrics. Identify the first agent deployment opportunities at the most advanced companies.

The goal isn't to transform every portfolio company in 90 days. It's to establish the operating model, prove the value at a few companies, and build the internal capability to scale AI adoption as a core part of the PE value creation playbook.

Frequently Asked Questions

How are Calgary PE firms currently using AI?

Most Calgary PE firms are in the experimentation phase — individual partners and analysts use Claude or ChatGPT for research, memo drafting, and deal screening, but few have systematic approaches. The firms pulling ahead are those deploying AI across portfolio operations, not just at the fund level. Solway has worked with multiple PE and M&A advisory firms in Calgary on both fund-level and portfolio-level AI adoption.

Does AI readiness actually affect company valuations?

Increasingly, yes. Buyers are beginning to assess AI policy maturity, training history, and shadow AI risk as part of operational diligence. While there's no standardized AI readiness score yet, the conversation is happening in Calgary deal rooms right now. Companies without AI policies face potential discount discussions; companies with documented AI strategies and trained teams present as more operationally mature.

How much does it cost to deploy AI training across a PE portfolio?

For a typical portfolio of five companies with 10-20 employees each, expect $50,000 to $150,000 in the first year across training, policy development, and initial tool deployment. With CAPG reimbursement covering up to 50% of training costs per company (up to $100,000 each), the net investment drops significantly. Tool subscriptions (Claude Team or ChatGPT Team at $25 USD per user per month billed annually, or Microsoft Copilot at $21 to $30 USD per user per month depending on plan tier) are additional.

What's the difference between AI at the fund level versus portfolio level?

Fund-level AI improves how the PE firm itself operates: faster deal screening, automated CIM processing, more comprehensive industry landscapes, and streamlined investor reporting. Portfolio-level AI improves how each portfolio company operates: workflow automation, customer service agents, operational efficiency, and capacity growth. Both create value, but portfolio-level AI typically has a larger impact on enterprise value because it directly affects the operating metrics that drive exit multiples.

How long does it take to see ROI from AI adoption in a portfolio company?

Immediate time savings appear in the first two to four weeks on tasks like meeting notes, email drafting, and research. Meaningful workflow improvements take 60 to 90 days. The compounding effect on operating metrics — revenue per employee, margin improvement, capacity growth — becomes measurable within six months. For a PE hold period of three to five years, early AI adoption creates compounding advantages that directly affect exit value.

Can AI help with due diligence processes?

Yes. AI can process CIMs, extract key financial and operational data, generate preliminary industry landscapes, draft investment memos from raw diligence materials, and identify red flags in target company data. The PE firms we work with are also using AI to build custom diligence checklists, including AI readiness assessments, that get deployed across every potential acquisition.

Is our portfolio company data safe when using AI tools?

Business-tier subscriptions for Claude and ChatGPT include enterprise data protections that prevent your inputs from being used for model training. Microsoft Copilot operates within your existing Microsoft 365 data boundaries. The critical step is establishing a clear AI policy — which is one of the three deliverables from Solway's AI Clarity Sprint — that specifies what data can and cannot be shared with AI tools, and training every team member to follow it consistently.