Can AI improve M&A outcomes through better sourcing? A conversation with Comparables.ai

Most M&A deals don’t deliver the expected results. Studies suggest 75% of acquisitions fail to meet the value criteria set before the deal, and many fall apart long before closing. Dealmakers are increasingly looking to technology to improve those odds, with Bain revealing that AI adoption more than doubled in 2025. 

To understand AI’s potential in changing the way deals are sourced, evaluated, and closed, I spoke with Niko Nalli, CEO of Comparables.ai. Before founding the company, Niko spent four years in mid-market M&A at PwC, where he worked on transactions valued at more than $4 billion in total. 

Niko shared his perspective on why transactions fail, where legacy deal sourcing platforms fall short, and how AI will reshape M&A in the years ahead. 

Q. Can you tell me about your career and what led you to found Comparables.ai? 

I started my M&A career in 2017 in mid-market M&A and during that time, I advised on 30 transactions. My bread and butter was sell-side mandates, but I also rotated through financial, tax, and operational due diligence, as well as post-merger integrations. 

What I loved most was the feeling of making deals happen. It’s a critical moment, whether for an entrepreneur selling their life’s work or a corporate making a strategic acquisition. It can be a complete bust or a home run that sets the strategic direction of a company for years to come. 

During that time, I was experimenting with AI and automation. I had already built tools that reduced cost and effort in M&A processes, so I knew there was an opportunity in this space. 

Q. What impact do you think AI will have on M&A? 

Companies spend trillions on acquisitions every year, yet a large percentage of deals fail to achieve the outcomes they were meant to deliver. Buyers walk away, synergies never materialize, and many completed acquisitions erode value instead of creating it. 

But when M&A works, it’s transformational. Facebook bought Instagram for one billion, and it’s now worth over 70. Google’s acquisition of Android transformed the global mobile ecosystem. When the right companies connect at the right time, the impact can be extraordinary. 

That’s why AI is gaining so much traction in M&A. The opportunity isn’t simply about making workflows faster or automating repetitive tasks. The real value lies in improving decision quality and uncovering opportunities that can shape markets and industries. 

AI has the potential to help firms identify better-fit targets, surface patterns that people miss, and reduce the friction that causes promising deals to fail. In other words, it can increase the probability that the right transactions are found and completed successfully. 

Q. How does Comparables.ai differ from traditional deal sourcing platforms?

PitchBook is a popular solution, but they cover around 4 million companies globally. Our coverage is 400 million. As a user, if you want to find the most relevant target, how do you know it’s in that 4 million? You may already be missing half of the relevant results before you even click search. 

Platforms like Moody’s Orbis have hundreds of millions of companies, so raw coverage isn’t the key difference. What really matters is the technology, and how you find relevant results.

Legacy platforms are great when you already know the company you’re looking for. But if you want to find every company globally similar to a specific business, that’s practically impossible without spending days on the platform, and M&A professionals don’t have this luxury. 

Historically, you’d filter by industry terms like “software development,” but that returns a very broad list, and maybe one in 500 is actually relevant. Customers end up with extensive coverage, but no real way to surface what matters.

Q. So how does Comparables.ai solve this problem? 

We filter companies based on qualitative, financial, and geographic data. It’s the mix which makes our platform unique, as other businesses in our space may be strong on the financial side, but they lack qualitative information. 

That combination matters in M&A, because the best targets are rarely identified by numbers alone. Strategic and contextual factors often determine whether a deal actually creates value after closing. 

What we’ve validated through our customers is that Comparables delivers 110% more relevant results. It surfaces additional companies and transactions they completely missed, but that are highly relevant. On top of that, analysis times are consistently 20 times faster than other methods.

Our North Star is how relevant the insights are. Speed doesn’t matter if the results don’t align with what our clients are looking for. 

Q. Comparables.ai also supports valuations. Can you tell me how that process works? 

Valuation comes down to two things. First is framing the business: how you define and position a company to justify a valuation. This matters especially for diversified businesses that don’t fit neatly into a single category. 

Take a company like Tesla. It spans electric vehicles, energy storage, and solar. So the question becomes: what is the right framing? Is it a car manufacturer, an energy company, a battery business, or a technology platform? 

That choice is important because different categories trade at very different multiples. Automotive companies might trade at ~2x revenue, whereas technology companies can trade at 10–15x or more. So the narrative you use materially impacts valuation. 

Second is benchmarking: identifying the right set of similar companies and transactions to support that valuation. This is about grounding the narrative in real market evidence. 

That’s where Comparables comes in. We help customers build that benchmark set by surfacing relevant peers and transactions across their space, along with their valuations. Often, clients are surprised by what appears – deals or companies they weren’t previously aware of – which can meaningfully change their valuation.

Q. Where is human judgment still critical in M&A, and what can Comparables.ai not yet do? 

My view is that AI should be treated as a coworker, and today, the technology is still at a relatively junior level.

If you ask it to complete a task, you need to understand how that analysis was generated. What did it evaluate? Why did it make those choices? You work with the system the way you would with a colleague, improving the outcomes over time. 

What’s clear is that the “seniority” of these AI systems will increase. They won’t just perform junior work – they could potentially reach manager or director-level output in the future. As these tools develop, the key will always be transparency. You need to understand why it does what it does so that you can communicate with the system and trust its conclusions. 

For the foreseeable future, it’s about augmentation. Comparables helps M&A professionals reach better insights, which they then layer with their own judgment and expertise on top.

Q. How do you think AI will change M&A in the years ahead? 

The primary goal of Comparables is to improve the success rate of M&A transactions. Our platform can significantly compress timelines by accelerating preparation and analysis, but it’s the quality of that analysis that will have the greatest impact. 

We want to help M&A teams be more successful by identifying stronger targets sooner, and this approach can also reduce post-merger underperformance. When we enable clients to uncover relevant, well-matched targets from the outset, this naturally increases the probability of long-term success. 

It’s not simply about more deals; it’s about better ones. Comparables is helping M&A professionals make smarter decisions earlier in the process, rather than just increasing their output. This is ultimately what increases the success rate in M&A.