There are moments when new technology arrives not only with a thunderclap, but also with a longer-term promise.
In the case of agentic AI, that promise seems to be that if we learn to use it wisely, new technology solutions can widen opportunity, sharpen judgment, and help us make better decisions than we did before. In M&A, an arena defined by uncertainty, ambition, and high stakes, that promise has captured imaginations across boardrooms and deal teams alike.
In this series, we’ll explore the fundamentals behind agentic AI’s promise, separating signal from noise, ambition from execution, and architectural theory from deal‑team reality. Because in M&A, success has never been about adopting the newest tool first. It has always been about making better decisions, faster—without losing sight of stakeholder responsibility, trust, and long‑term value creation.
Enhancing M&A Without Handing Over Control
That is why the conversation on agentic AI in M&A must move beyond enthusiasm. While we believe wholeheartedly that each phase of the M&A lifecycle poses great opportunities for agentic AI to serve as a benevolent contributor, it’s also clear that the boundaries must still be set by humans. As McKinsey notes[1], unlocking value requires re‑imagining processes from the ground up—supported by the right data foundations, governance models, and operating structures—not simply plugging agents into legacy workflows.
In this blog series, we will peel back the layers and identify how and where agentic AI can help you during several phases of the M&A lifecycle. Through our combined professional experience, we’ve each lived through the good and the bad of the M&A lifecycle and there have been many times we’ve said “I wish there was a service that could find my client just the right sorta buyer overnight” -or- “What if I had a macro that could scan customer contracts to immediately find clauses incompatible with my policies?”
In many ways, it seems that the future is already here. Tools and services exist today that can help at various steps along the M&A journey. We still have to piecemeal the tech stacks together and verify their accuracy, but it’s a start.
The Real-Real of Tools to Assist at Certain Phases
With new AI tools being developed and launched at breakneck speed, recognizing exactly how and when to use relevant tools can be challenging for even the most tech-oriented leaders. Here, we’ll provide a few high-level examples aligned with specific phases of the M&A process as a starting point.
Preparation
Agentic AI Chat Assistant – regardless of which phase of the M&A process in which one is engaged, issues and complex and answers are not simple. Whether the issue is what to do, how to do it, or when to do it, support from a knowledgeable guide in the form of an intelligent chatbot could make the process easier and faster.
Initiation & Structure
AI-assisted Matching of Capital Seekers/Capital Providers – for buyers, finding target transactions is both time consuming and expensive. For sellers, shopping for the best deal is inherently limited by the small number of identifiable capital sources at hand. With an AI search and matching process, the actual universe of alternative “successful matches” is within grasp.
Transaction Analysis
Intelligent Document Management & Evaluation – anyone who has ever been involved in M&A knows the most time consuming and difficult process in any deal is 1) getting the “right” information in place and 2) testing it is credibility. AI assistance with this process is critical to successful outcomes. Today there are multiple AI-assisted document management tools available to help with this process.
Closing
Claw-Assisted Follow Up – so-called “Claw” AI assistants (such as OpenClaw) are a new generation of open-source, autonomous AI agents that can execute multi-step tasks across systems independently, performing actions rather than merely making suggestions, and retaining context across sessions for long-term projects. With the variety of locally run and “always-on” claw tool options available, it is now possible to set up an AI assistant to work on behalf of your transaction. The claw can be set to stay continuously active on your behalf looking for updated rates, new possible deal terms or new partners. Failure to engage in continuous research until your deal closes, could lead to lost opportunities.
Looking Forward
Potential AI solutions now permeate the entire M&A lifecycle. From initial preparation through closing, AI tools can accelerate research, automate manual tasks, reduce risk, and enable teams to dedicate more energy to strategic decisions.
While M&A will always involve a degree of uncertainty, the tools we use to navigate it are evolving rapidly. Agentic AI may not eliminate complexity, but it is fundamentally reshaping how we manage it.
For teams operating in increasingly competitive and data-driven environments, this shift offers more than incremental improvement. It has the potential to deliver a significant competitive advantage.
Historically, finding the right deal depended heavily on personal networks and relationships.
But what happens when AI can leverage vast datasets to effectively “know” the market?
Agentic systems have the potential to continuously scan for opportunities, identify strategic alignment, and connect buyers, sellers, and capital providers, possibly even before either side formally enters the process. As a result, deal sourcing becomes less reactive and far more dynamic.
In our next installment, we will explore how agentic AI could further redefine the process of identifying the ideal merger partner by connecting parties in ways previously unimaginable.
[1] Seizing the agentic AI advantage | McKinsey
Learn more about PQ-Suite at https://pq-suite.com/
Want to discuss your credit union’s post-merger integration in more detail? Contact ALM First’s team of experts to learn more.
