In this post TPP founder Ian Smith walks us through the TPP M&A playbook and invites Kalle Kilpi to predict how AI will transform it.

Kalle’s remarkable bio gives him a distinct edge to help us understand the impact. He brings a uniquely relevant background to help us explore the evolving role of AI in M&A. With a decade-long commitment to enhancing M&A processes through technology, his insights are grounded in real-world experience. He recently founded DealMap.AI, a venture specifically aimed at integrating advanced Generative AI into M&A with purpose-built software solutions. Prior to this, as the technical co-founder and CTO of Midaxo, he gained firsthand experience in the intricacies of M&A deal management software. This blend of practical expertise and industry-specific knowledge should make for an interesting conversation.

In the M&A world, it’s about leveraging AI to get deals done faster, better, and with less risk—all while enhancing value creation at each stage of the M&A process. If we look at the M&A process, it’s clear that AI could act as a very powerful tool to speed up analysis, assist decision making and identify risks. This post examines TPP’s six phase acquisition process map with Kalle and how Generative AI will help improve the effectiveness and efficiency of M&A.

Let’s take each phase;

Phase 1 Strategy: A successful acquisition program starts with strategy. It’s about defining who you are. The story should explain what’s wrong with the current market or what challenges are not being met by the current players. It should articulate what your unique solution achieves and why its credible. Depending on the size of the group this could cover many sectors and product solutions. In this context you will consider how M&A can accelerate your success. How could acquisitions bring products and services into the family to satisfy customer needs? This should lead to a well defined one pager called the Acquisition Profile.

So how could AI help clarify your strategy and ultimately lead to a stronger, better aligned and credible Acquisition Profile?

Kalle: Generative AI can offer a valuable and objective perspective on the market environment by analyzing large amounts of data to identify trends, customer preferences, emerging technologies, and the offerings and capabilities needed to succeed across various market segments. This analysis can help in evaluating your company’s current business portfolio, capabilities, and performance, both present and future. By identifying gaps or areas for improvement, AI can help in determining the rationale for acquiring new offerings or capabilities, or for divesting existing ones. This, in turn, aids in pinpointing potential targets that would align with your company’s goals and lead to the desired end state, while also creating value and crafting a compelling equity story.

Moreover, AI can also help in identifying potential acquisition targets by analyzing a vast array of data sources, including financial statements, social media, news articles, and other publicly available information. This can lead to a more comprehensive understanding of potential targets, their strengths, weaknesses, and alignment with your company’s strategic goals. Additionally, AI can help in predicting the potential impact of an acquisition on your company’s performance, customer satisfaction, and overall market position, thereby contributing to a stronger, better aligned, and credible Acquisition Profile.

 Phase 2 Identify & Assess Targets: An Acquisition Profile’s criteria should allow a research exercise to kick off. The challenge is to build a long list of potential targets that match your criteria. Of course, in practice the world is messy. Some potential target companies operate in many different product areas, but you may only be interested in one of those areas. For example, you are searching for an NPS survey platform company but many of the potential targets are owned by large marketing groups who also have Customer Data Platforms, ESPs, DSPs, etc. Of course, there are also independent NPS players who focus solely on that niche. You need to gather key information on all targets, create filters that capture your priorities and sort this long list into a prioritized list of candidates.

So how could AI help you accelerate this process and pull together a shortlist of targets perfectly aligned with your strategy?

Kalle: AI can accelerate the process of target identification and assessment by analyzing extensive datasets and a high number of companies to pinpoint those that align with your specific criteria, such as NPS survey platforms. It can differentiate between conglomerates and niche players, ensuring clarity in the search process. Customized filters and screening criteria echoing your strategic priorities can be applied to rank targets based on their alignment with your Acquisition Profile. This accelerates the shortlisting process and ensures precision in target selection.

 Additionally, AI can continuously update the list using real-time data. As market dynamics shift and companies evolve, your target list remains current, ensuring you stay ahead in your M&A strategy.

There are two main approaches to utilizing Generative AI or Large Language Models (LLMs) like the GPT model. The first approach is to ask tools like ChatGPT or Anthropic’s Claude to identify companies and explain their organization, offerings, and other data points of interest. This is an easily accessible and cost-effective option but works best in industries with a limited number of targets, as LLM models provide concise answers and may not always provide accurate facts. However, they often identify truly great and new targets, making it worth trying with caution.

 The second approach involves developing and using purpose-built solutions that use AI to interpret text from various sources, such as company websites, PDFs, PowerPoints, or Word documents. LLM technologies, commonly referred to as Generative AI, are also brilliant at reading and analyzing text. While standard products like ChatGPT are not designed for this, specialized products and custom solutions are being built for this, by companies that as my team at DealMap.Ai, to help automate deal sourcing, screening, and analysis activities. While the early solutions like this are highly tailored for each customer at the moment, over time the core parts of these solutions will be generalized into standard products that can be adopted without investing in custom development. This applies to all parts of the process from screening to integration.

Phase 3 Target Meetings & Valuation: The challenge for acquirers at this stage is to collate all the facts, answers to questions asked, research studies, published data, confidential data to build a post-acquisition picture of the target. This picture will rely on your integration strategy and how the business will operate under your ownership. Only then can an acquirer place a range of values on the specific target.

So how could AI help you gather this information in a format that informs your post-acquisition strategy and the value range you could justify?

Kalle: AI can greatly facilitate the process of collating and analyzing the myriad of information needed to build a post-acquisition picture of the target. By synthesizing information from the public domain, research studies, published data, confidential data, and insights from face-to-face meetings, AI can help in early validation of the assumed integration model. This not only helps estimate the value of the target for the acquirer (vs market value) but also speeds up the process of analyzing the strategic fit.

 The AI can manage the foundational work of compiling and analyzing information, freeing up human bandwidth. This shift allows M&A teams to engage in higher-level strategic thinking and guide the AI to think through various scenarios and delve deeper into post-deal organizational configurations and synergistic go-to-market strategies.

 Ultimately, AI helps in gathering information in a format that informs your post-acquisition strategy and justifies the value range, thereby enabling a more informed and strategic decision-making process.

Phase 4 Negotiation of Price & Structure: The penalty box to use a soccer analogy is the negotiating room. This is where deals are created. Preparing for these vital meetings especially the Letter of Intent meeting requires a review of all data captured from all previous meetings and reports.

So how could AI help you prepare for negotiation meetings?

Kalle: AI is an invaluable ally in the negotiation process. It swiftly compiles and analyzes vast volumes of data from prior engagements and external market trends, ensuring negotiators have a comprehensive understanding of all relevant factors, thereby providing a strategic advantage. Beyond data accumulation, AI’s ability to discern patterns is transformative. By detecting trends in a counterparty’s negotiation behaviors, negotiators can anticipate potential challenges or windows of opportunity during discussions. This insight, coupled with AI’s predictive prowess in modeling potential outcomes of various negotiation strategies, empowers teams to craft a tailored approach for success.

 During core discussions, AI serves as a vigilant assistant, generating timely reminders to ensure crucial deal points or documentation aren’t overlooked. Additionally, negotiators can leverage AI for on-the-spot data retrieval, invaluable for immediate validation or rebuttal of claims. AI also provides a broader perspective by drawing from market data, past transactions, and predictive analytics to pinpoint a fair price range for the target. This data-driven approach is bolstered by AI’s ability to suggest optimal deal structures inspired by historical deals or current market shifts. Additionally, AI assesses potential risks tied to different deal terms, guiding the team towards minimizing vulnerabilities.

Post-negotiation, AI aids in deconstructing outcomes, juxtaposing them against set objectives, and providing insights on potential recalibrations for upcoming engagements. In essence, integrating AI into the negotiation phase ensures meticulous preparation and dynamic adaptability during discussions, steering teams towards optimal deal outcomes.

Phase 5 Due Diligence & Legal Agreements: You are under tight time constraints to close the deal, but due diligence is an essential validation exercise before you sign an agreement. There is a sea of information to clarify especially the need to validate your assumptions regarding the post-acquisition integration strategy.

So how could AI help you complete due diligence and sign off on an appropriate Sale & Purchase Agreement?

Kalle: As the M&A process progresses to due diligence and legal agreements, time constraints intensify. Due diligence is a crucial validation step before finalizing an agreement. It involves clarifying a vast amount of information, especially to validate assumptions regarding post-acquisition integration. In this critical phase, AI proves to be an indispensable ally.

AI excels in managing large volumes of data, distilling extensive information into summarized insights that validate the provided data. Additionally, AI plays a pivotal role in stress-testing post-acquisition strategies using predictive modeling to evaluate various strategies under different conditions. Beyond validation, AI’s efficiency is transformative. It can generate detailed disclosure schedules accompanying M&A agreements by integrating with a target company’s internal data systems, producing these schedules in minutes instead of weeks.

In legal matters, AI tools equipped with a deep understanding of legal language and contracts meticulously analyze Sale & Purchase Agreements. They identify standard provisions, highlight potential issues, and pinpoint areas requiring customization tailored to the deal’s nuances. While legal counsel is irreplaceable, AI supplements their expertise, ensuring a rigorous examination of every facet of the agreement in a time-efficient manner.

 AI is a dynamic learner; its predictive accuracy and analytical prowess are honed with each deal processed, enriching the M&A process with cumulative wisdom. As the agreement’s finish line approaches, AI facilitates seamless collaboration between teams by offering a unified platform filled with insights, validations, and advisories. This cohesion ensures synchronized understanding among stakeholders, mitigating surprises or oversights at the last moment.

 In summary, during the intricate dance of due diligence and legal agreements, AI acts as both the choreographer and the safety net. It streamlines complexities, fosters informed decision-making, and accelerates procedures, instilling the entire process with renewed confidence and precision.

Phase 6 Post-acquisition integration: Assuming you have a credible post-acquisition integration plan and you’ve set up an Integration Management Office (IMO) driven by an experienced practitioner; how can you ensure you will be successful? How will you move people forward to create a future state for each department that makes sense to the operators on the ground?

So how could AI help you successfully integrate the target especially given this failure is the biggest reason behind the failure to create shareholder value from acquisitions?

Kalle: The post-acquisition integration phase is like the crescendo of a symphony, where each element must harmonize perfectly. With a robust integration plan and a proactive Integration Management Office (IMO) led by an experienced practitioner, the challenge often lies in ensuring effective implementation on the ground.

In this complex landscape, Ai serves as the conductor, ensuring cohesive synchronization of all elements. AI excels in connecting key insights from the due diligence phase to strategic initiatives that shape the integration process. This ensures that valuable insights from the deal’s evaluation inform the execution of the integration.

 For instance, if operational efficiencies or potential risks were identified during due diligence, AI ensures these insights inform actionable strategies rather than remaining confined to reports. AI dynamically suggests checklists, acting as a vigilant guardian to ensure that no crucial step in your M&A playbook is overlooked. It effectively becomes a living memory, retaining key findings and prompting timely actions based on them.

 Additionally, AI can function as a virtual consultant or guide, available to instruct individual team members more comprehensively than the integration leadership typically can. This AI guide relies on the directional best practices defined by the integration leadership, its own general understanding of functional best practices, and learns from past deals. As organizational learnings and best practices accumulate, they become an incredibly valuable part of the organization’s institutional M&A capability and competence. This enables increasingly effective post-acquisition execution and value creation, as well as increasingly accurate pre-deal projections.

The power of AI to transform any process will reshape the way we execute and scale businesses. It will bring insights, efficiencies, risk mitigation, and automation to every aspect of business life. And as you can see, it will revolutionize the M&A process. Sound interesting? Let Kalle and I discuss your M&A process and the potential to deploy AI, just email me at to fix a date.

TPP is buy-side investment banking reimagined. We create successful acquisition programs collaboratively with our clients. We seamlessly become an extension of your team and integrate at all levels to add deep mergers & acquisitions expertise into your business. Always ready for a conversation – 978 395 1155 or