Stonehill Insights

Most conversations about AI governance start and end with security: model access controls, data encryption, vendor risk assessments, defenses against prompt injection. Those protections matter. But they solve the wrong problem for most organizations right now.

Every organization says it wants to innovate faster. Most respond to that ambition by doing the one thing guaranteed to slow innovation down: adding people.

Everyone wants to talk about the shiny thing. The new AI model. The automation platform. The dashboard that finally makes the data "make sense." Innovation, in most boardrooms, has quietly become a synonym for technology - as if buying the tool is the transformation.

Most consulting firms in the M&A space are built the same way: a partner sells the engagement, a team of analysts builds the deck, and a senior advisor shows up for the steering committee meetings. The recommendations are sound, the frameworks well-worn, and the language polished. What's frequently missing is anyone on the team who has actually run a business through the kind of change they're advising on.

Every middle-market executive has sat through an AI pitch built around some transformative, company-changing use case. Fewer of them have seen AI actually pay for itself. That's not because the technology doesn't work, it's because most companies point it at the wrong problems first.

Every carve-out comes with a Transition Services Agreement, and every TSA comes with a clock. The problem is that most organizations treat the TSA period like a safety net instead of what it actually is: a countdown with a hard deadline and real financial consequences if you miss it.

Most deals don't fail because of a bad thesis. They fail because the people expected to execute the thesis simply ran out of capacity to absorb more change. In the middle market, this failure mode is especially common and especially invisible. There's no line item for it on the model. No one flags it in diligence. It shows up eighteen months later as slipping synergy targets, unexplained attrition, and a leadership team that seems oddly disengaged from a deal they were excited about at close.

Every week, another headline announces a Fortune 500 company's nine-figure AI investment - a dedicated innovation lab, a bench of PhD data scientists, a partnership with a hyperscaler. If you're running a $50M–$1B middle-market company, it's easy to conclude that an "AI Center of Excellence" is someone else's game.

Most AI initiatives don't fail because of the technology. They fail because the organization wasn't ready for what the technology would expose.

The champagne has been poured. The press release is out. The deal team is celebrating a transaction that took months — sometimes years — to negotiate, structure, and close. And somewhere in the back of the room, a quiet clock has started ticking.

Because the deal closing isn't the finish line. It's the starting gun.

You closed the deal. The press release went out. The champagne was opened. And somewhere across town, your newly acquired VP of Operations just updated her LinkedIn profile to "open to work." It happens in nearly every acquisition. Not because the deal was bad. Not because the pay wasn't right. It happens because the integration plan treated people as an assumption rather than a strategy.

Cross-selling is the revenue synergy every deal model loves and almost no integration delivers. The reason is that it has been misdiagnosed for decades.

Walk into 2026 and the headlines read like a reversal: Amazon at five days, Microsoft at three, Instagram fully back, and a long roster of household names tightening their in-office requirements. Despite the directives, only about a quarter of companies have actually returned to fully in-person work.

Most companies that set out to "fix the org" start by redrawing the org chart. New boxes, new reporting lines, a few titles changed, a reorg memo on Monday. Ninety days later the same things are still falling through the cracks: decisions stall, two people own the same number, three people own none, and the founder is still the bottleneck for anything that matters.

Every merger comes with a deal thesis. A compelling strategic rationale, a financial model with synergy assumptions, and a leadership team convinced that this combination will create something greater than the sum of its parts. What the model rarely captures is what happens in the 90 to 180 days after the ink dries.

Most acquisitions don't fail at the negotiating table. They fail in the first 12 months after close. Study after study puts M&A value-destruction rates between 70% and 90%, and the post-close integration phase is where the majority of that value leaks out. Synergies get pushed to next quarter. Talented people walk out the door. Systems run in parallel for years longer than planned. Customers feel the seams. And the thesis that justified the multiple quietly erodes.

Artificial Intelligence now dominates modern business discussion. It is a standing agenda item in boardrooms, earnings calls, strategic plans, and industry conferences. Yet despite this attention, most organizations remain uncertain about how to move from experimentation to sustained economic impact.

Technology investments are often initiated in response to operational pain - inefficiency, lack of visibility, scalability constraints, or risk exposure. The common failure point is not execution quality or tool capability; it is sequencing.

Innovation is one of the most frequently used and misunderstood terms in business. It is often equated with new technology, digital tools, or breakthrough inventions. While these can be outcomes of innovation, they are not its definition. Innovation is not just about what is new; it is about what creates meaningful value.

Financial due diligence tells you what the numbers are. Operational due diligence tells you whether those numbers are real, repeatable, and scalable - or whether they’re being held together by overtime, heroic managers, and fragile systems.

Organizations often treat their merger and acquisition integration as the final objective. Systems are connected, teams are combined, and the business is stabilized under a single operating structure. Leadership moves forward assuming the hardest work is behind them. In reality, this moment marks the end of integration, but not the beginning of value realization.

Private equity value creation is often framed as a set of internal initiatives: improve margins, grow revenue, upgrade technology, strengthen leadership. These efforts matter, but they rarely deliver their full potential because they overlook the most important reality of all: a portfolio company is a multiplayer system.

Total Experience (TX) is a strategic approach that unites Customer Experience (CX) and Employee Experience (EX) to create seamless, connected interactions across every touchpoint. It’s built on the understanding that the same systems, processes, and culture that empower employees to deliver great service also shape how customers perceive your brand.

For decades, the concept of “Skunkworks” has been synonymous with innovation under extreme constraints. Originating with Lockheed Martin’s Advanced Development Projects in the 1940s, Skunkworks projects proved that small, highly focused, and autonomous teams could achieve breakthroughs faster than traditional corporate structures allowed.

Private equity firms have perfected the art of sourcing deals, structuring capital, and driving value through operational improvements. But when it comes to post-merger integration, too many firms underestimate the complexity and it’s costing them real money.

Agility and innovation are the currency of success, one critical investment is quietly being sidelined: employee training. At Stonehill, we’ve seen firsthand how companies are scaling back learning and development budgets in favor of short-term gains. But here’s the truth, neglecting training isn’t just a missed opportunity, it’s a strategic risk that can erode your competitive edge from the inside out.

Mergers and acquisitions (M&A) are designed to accelerate growth, unlock synergies, and increase enterprise value. Yet, studies show that most deals fail to deliver their intended results. While financial due diligence and strategic alignment receive significant attention, the people side of integration is often underestimated.

Mergers and acquisitions are powerful tools for growth, but they are also notoriously difficult to get right. While the headlines focus on deal size and market opportunity, the real test begins once the paperwork is signed. Studies consistently show that more than half of mergers fail to deliver their expected value. The main reason? The complexity of bringing two businesses together after the deal closes.

At Stonehill, we are passionate about unlocking the transformational potential of AI. Yet, time after time, we’ve seen organizations eager to deploy AI-driven solutions without first fully understanding or even documenting their internal processes. The result? Underwhelming outcomes, stalled deployments, or even failed rollouts.

In private equity, every decision is driven by value creation. Investors expect returns, limited partners expect performance, and portfolio company leadership is under pressure to deliver measurable results quickly. Traditionally, private equity firms have focused on financial levers like operational efficiency, cost reduction, and growth through acquisition.