Blog. From Time-Saving Tool to Strategic Partner: AI Transforms M&A Integrations
- minnahyvari
- 22 hours ago
- 5 min read
Our recent webinars on AI in M&A were a great success – we managed to engage hundreds of professionals in 28 countries. Given the strong interest, I wanted to share some key insights here: How can we leverage AI in the context of mergers and acquisitions, especially during the integration stage?
M&A integrations are inherently data-intensive, with plenty of use cases where AI can add value: vast volumes of information to absorb, plans to formulate, risks to assess, processes to implement, and business decisions to make; often under tight timelines, with limited resources and imperfect data. AI can be a powerful ally - but how?
Start with Interactive Use
You have essentially two options. Using AI ad-hoc, interactively, is the easy way to get started. This use of Generative AI fits well at both ends of the workflow: in the early stages (e.g., drafting strategies, business plans, or communications) and at the end (e.g., reviewing content or identifying gaps).
For example, AI can create an initial draft of your integration strategy or stakeholder communication. You then refine and finalize the output. AI can help review not just text but also structured content like budgets and timelines — suggesting edits, spotting anomalies, and identifying omissions. It improves both the quality and consistency of your work.
You can use AI as a co-writer: throw in a rough outline, let it shape the content, and refine back-and-forth until you are both satisfied with the outcome.
Go Deeper with Embedded AI
All of this is, of course, just scratching the surface. To unlock more value, you should embed AI systematically in your processes. This requires more planning and preparation but offers far greater impact.
Some strong use cases for M&A include:
Cascading plans throughout the organization
Identifying risks and mitigations with automated tracking
Summarizing progress according to the integration plan
Monitoring deviations and escalating as needed
Some of the applications will need Agentic AI to automatically plan and trigger sequences of actions.
The business benefit is not only increased efficiency but also improved quality — bringing in new ideas, reducing bias, and expanding the data-driven analytical approach.
Choosing the Right AI Model – and Data Strategy
There’s a wide spectrum of AI models to choose from. Options include:
Building a custom model (data-heavy and costly)
Fine-tuning a pre-trained model (much more moderate data needs)
Using commercial services (fast, cheap, but quite generic)
Your model choice will determine your data needs. Many prepackaged AI solutions come with built-in models. There’s no one-size-fits-all, and navigating these options requires expertise.
In the M&A context, you might not have the volume of repeatable data, nor the time, to justify building custom AI models. Instead, fine-tuning existing models with your own (typically small) datasets - like spreadsheets or structured documents - is a practical path forward. This can support use cases such as risk assessment, anomaly detection, or schedule generation.
Getting Data Ready
Talking about data, you likely have more data in the M&A integration than you realize: integration strategies, plans, budgets, performance reviews, meeting minutes, risk logs, org charts, and more. AI thrives on connecting the dots across diverse sources and formats. You can use a mixed bag of structured and unstructured data for the AI to do its magic.
Pre-processing often helps. Anything which makes the data more logical and connected will enhance AI performance. You can even use AI itself to help with this — for example, by tabulating information, extracting key facts, or prioritizing issues.
One important point: Always anonymize personal data (and company names, too). Never share identifiable personal information with commercial AI platforms — and certainly don’t allow them to use your data for training. In our case, we use a separate secure AI tool to redact personal information before any further processing begins.
A Human in the Loop
AI isn’t perfect and you cannot fully trust it. While it excels at content generation, it has been less talented in reasoning, though that’s improving.
For the foreseeable future, a human must own critical decisions. It’s about quality and accuracy (AI probably lacks deep domain expertise and case-specific nuance), but it’s also about ethical and strategic alignment. AI does not fully understand values, strategy and intent.
These checks and balances are not about a human double-checking every fact. This is about a human understanding what’s going on, intervening when necessary, and being accountable.
More than anywhere else, this is important when people are involved, as is the case in M&A integrations.
In our own implementations, we’ve embedded review steps where AI-generated summaries on our platform are passed to human specialists for their review and approval. The AI and the human work in tandem, with great efficiency and accurate, reliable results.
A Word from the AI
So much talk about the AI – and we haven’t yet heard what the AI themselves has to say about the matter! I asked, and these are the top AI use cases for M&A integrations that the AI recommended to consider (the comments are mine):
Culture analytics to detect people risks and culture clashes early (True — this is very close to what we do, so the AI may have utilized its awareness of my background!)
Talent mapping and retention risk (Valid — but handle with care. Ensure human oversight and respect evolving AI regulations like the EU AI Act.)
Organizational Network Analysis to improve team alignment via analyzing collaboration patterns (To be frank, I wouldn’t rank that as highly.)
Optimizing communication to boost clarity, trust, and alignment (A low hanging fruit for improving and speeding up communication.)
Integration planning intelligence to navigate integration scenarios, forecast risks and support decision-making (Strongly aligned with the use cases I’ve described above.)
Looking Forward
There is no reason to think that the progress has come to an end. We can do with AI things today which were impossible just a year or two ago, or at least unfeasible hard.
Massive investments, hundreds of billions across the world, are driving fierce competition in AI development. With all the key players heavily invested, how could this not lead to rapidly developing technology and applications, for better or worse.
Even if AI weren’t improving — and it is — there are tons of untouched use cases in every part of our work and personal lives, where AI can make a huge impact.
AI is evolving from a tool to a strategic partner — enabling, sooner or later, self-orchestrating workflows, adaptive culture management, multimodal reasoning, transparent AI-driven governance, and more than we can yet imagine. It’s an understatement to say that we live in very interesting times.
Please, contact us for further discussion – we are delighted to explore these possibilities and support you with your integrations. Please send a message or book an appointment.
Petri Järvinen, CEO - Partner
NayaDaya Analytics Inc.
Tel. +358 45 238 5537
Watch the webinar recording on "AI in M&A Integrations - Experiences and Reflections" either in English or in Finnish. Choose below!
NayaDaya Analytics Inc. is the innovator behind People Impact Analytics™, a game-changing solution for addressing people-related risks and engagement drivers in M&A integrations and transformations. Data-driven, actionable insights empower both operational and strategic decision-making. Powered by science- and AI-based emotion and behavior intelligence, the patent-pending method and technology offer a unique approach to promote successful change and foster inclusive, sustainable growth. Discover more at www.nayadaya.com.
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