In the rush to embrace AI, many private equity portfolio companies face a common dilemma: diving in without a clear objective or stalling while waiting for ideal conditions. Tony Aug, Co-Founder and CEO at Nimble Gravity, works hands-on with PE-backed businesses to turn strategy into execution, especially when it comes to making data and AI deliver real results.

In this Q&A, Tony unpacks the most frequent mistakes companies make with AI, how to assess if your portfolio is on the right path, and what it truly takes to unlock measurable value. If you're looking to cut through the noise and make AI work for your bottom line, this conversation is a must-read.

Q: What's the biggest mistake you see companies make with AI?

We see two common missteps in PE portfolio companies. The first is analysis paralysis - waiting for a "perfect" data strategy or more internal capabilities or something else before acting. In competitive markets, that delay often means missed opportunities to gain an edge, optimize operations, or enhance customer experience. And in any market, it's a wasted chance to start building a new capability.

The second is pursuing AI for AI's sake without a clear or even remotely considered business objective - chasing buzzworthy projects that aren't tied to EBITDA growth or exit value. This leads to wasted resources when results don't materialize because there was no defined problem to solve. It's okay to experiment and learn, but ideally, that's being done "toward" some outcome.

In both cases, the underlying issue is misalignment with the investment thesis. Successful portfolio adoption of technology tends to happen when technology is viewed as a tool for measurable value creation, not an end in itself. That's the mindset we help instill across PE-backed organizations.

Q: How do we know if our portfolio companies have the right approach to leveraging data and AI?

It starts with ensuring alignment to the value creation plan, or at least a plan for how it someday connects to a value creation lever in a future phase. Whether it's go-to-market, inventory reduction, process automation, etc. -- if the work doesn't support the investment thesis, it's likely a distraction.

Then, achievability is evaluated. Is the use case or cases a heroic, multi-year odyssey, or something that can happen in a few weeks? The ideal starting point is a project that has high potential benefits and low anticipated costs.

We also examine intent versus execution. Some portfolio companies discuss data and AI extensively but aren't deploying resources effectively. Others may be trying but lack the right skills, governance, or metrics to make real progress.

An effective approach is focused, properly resourced, and outcome-driven. If the management team can clearly articulate how AI or data initiatives impact key performance indicators, and they're executing with discipline, they're likely on track. If not, they may need external support - and it's crucial they feel empowered to seek it.

Q: How do we ensure we get measurable value out of data initiatives at our portcos?

Value realization begins with clear measurement. Before project kickoff, we help portfolio companies define success metrics that will prove or disprove impact. This means isolating effects through methods like test-and-control groups or using benchmarks or baselines to track efficiency improvements over time.

A common pitfall is assuming value will be evident and completely attributable post-implementation. Without a disciplined measurement framework, it's challenging to determine what worked, especially with multiple variables at play in a business (and in the market).

We also emphasize quick wins. Not every initiative needs to be transformative. Smaller, faster experiments often yield quicker insights and better long-term results. When companies see tangible improvements in EBITDA or other key metrics, they can reinvest with confidence, accelerating value creation across the portfolio.

Tony will share more insights during our panel on "Leveraging AI and Digital Transformation for Value Creation" at the 2nd Value Creation Summit, taking place June 4th in New York.

Don’t miss the opportunity to learn from experts like Tony and explore how data and AI can drive real, measurable outcomes in your portfolio companies. Join us for strategy, execution, and smart innovation in PE.