How AI can automate your M&A process

For now, GenAI can assist with low and medium level complex tasks and may have the potential to partially or fully assume the responsibility for them. However, considerable efforts are needed to determine how best GenAI fits into M&A solutions and to build these capabilities. In the immediate future, GenAI can:

• Assist with brainstorming
  • Frameworks
  • Functional and industry knowledge
  • General idea generation
• Accelerate due diligence process
  • Document analysis
  • Data analytics
  • Secondary research

#1 M&A vision & strategy & #2 Deal Sourcing, screening & pipeline management

Currently, GenAI can assist by providing suggestions or ideas. However, due to the lack of access to private data and non-recorded data, GenAI can’t be relied on to develop a holistic M&A vision and corresponding strategy without human involvement. A couple of examples:

• Private data - Acquirer has a proprietary product about to launch and is determining its M&A vision to best complement that new product.
• Non-recorded data - Several key meetings regarding product vision and strategy that were not recorded.

Without the GenAI having access to the data, it would recommend a vision that isn’t as relevant or customized.

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#3 - Due Diligence

GenAI can combine its vast knowledge and pattern recognition to provide insights and recommendations. It has the potential to provide much-needed analysis horsepower and insight to perform faster and with higher quality, eliminating the need for functional SMEs on large transactions.

This area is broad and includes many domain areas: finance, commercial, operational, insurance, real estate, environmental, organization, etc. In each domain area, GenAI has potential to make a significant impact, given which some will be explored. Below are some preliminary examples:

Example One - Operational Due Diligence

Often, companies will compare two sets of cost spending categories and vendors to find out cost synergies. GenAI is capable of enhancing the existing data science and analytics tools like Alteryx to provide a more detailed analysis of the variances between different datasets for both numerical and textual data. Below is a real-world example of a deal that could have used GenAI to assist with Operational Due Diligence.

Situation - A global market leader in manufacturing chemicals is merging with a similar-sized competitor, and each company has approximately 1,000 suppliers.

Task - An M&A practitioner is tasked with identifying non-labor cost savings and synergies.

Action - The M&A practitioner needs to compile all vendor data by both acquirer and target, clean the data, sort spending in descending order by vendor, identify overlapping vendors (with the help of fuzzy match), review contracts of overlapping vendors for opportunities (e.g., consolidating vendors to the one that has better terms), and calculate savings and synergies based on the deal thesis. To complete this, the M&A practitioner can use data science and analytical tools to clean data, identify data gaps and integrity issues, and provide insights. Additionally, document analysis tools are also available (for example, DealRoom).

Opportunity - There’s an opportunity to advance the analysis and process further by enabling GenAI to emulate the thought processes and actions of M&A practitioners. GenAI can not only integrate data science and analysis with document analysis but also perform calculations (e.g., cost savings by selecting the vendor with the most competitive pricing per SKU) and provide potential risks (e.g., termination clauses and fees) and recommendations (e.g., advantageous discount/rebate program based on supplier vendor terms).

Example Two - Commercial Due Diligence

GenAI possesses the potential to significantly impact the desktop research component of commercial due diligence, particularly in the context of competitive and market landscape analysis. M&A practitioners have already used it to generate ideas, conduct research and synthesize findings, such as market headwinds and tailwinds. However, it is important to note that primary research, such as the voice of customer studies and market sizing in niche industries, still requires the involvement of practitioners to design tailored questionnaires (e.g., open vs. closed questions, order of questions, industry-specific). 

Situation - A private equity is evaluating a potential acquisition of a medical claims editing software from a market-leading healthcare provider.

Task - Assess the commercial attractiveness of the acquisition target.

Action - The M&A practitioner needs to calculate the target addressable market size, understand the market and competitive landscape and trends to provide insights, identify additional growth opportunities, and determine potential commercial risks.

Opportunity - GenAI can be deployed to assist with aspects of secondary research. That said, calculating an estimated range for the target addressable market of niche industries remains a top opportunity. This process, which relies on primary and secondary research (e.g., Forrester, Gartner, IBIS) and a methodology created by an M&A practitioner, is more of an art than science at times and can take weeks to develop. Future GenAI capabilities can hopefully provide suggestions on how best to calculate an estimated range (e.g., criteria and corresponding weights) and provide one.

Example Three - Legal Due Diligence

Given the many different regulatory bodies (e.g., FTC, Federal Reserve) and compliance for certain industries (e.g., banking, healthcare, airlines), GenAI can help with research and compliance. It can analyze vast amounts of legal documents and identify potential compliance risks or opportunities. For example, antitrust is often a reason FTC uses to prevent deals (e.g., JetBlue / Spirit, TD Bank / First Horizon) from happening that they perceive as potentially harmful to consumers. M&A practitioners and attorneys can leverage GenAI to help with their research and litigation strategies.

Example Four - Tax Due Diligence

A tax attorney advises on the post-close legal structure(s) to minimize tax liabilities. Future GenAI capabilities may offer the ability to provide recommendations by analyzing all legal, tax, and financial documents and presenting the optimal legal structure(s) with the least amount of estimated tax liability while being compliant with all tax laws.

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#4 - PMO

In the future, GenAI will be able to create customized templates and processes based on factors such as deal type, size, industry, and function. It will also provide estimated ranges for integration/separation budget and resourcing, track synergies through various systems, recommend adjustments based on insights developed, identify potential PMO risks, and develop potential mitigation solutions. Here are a few opportunities:

Functional Current State - It is recommended to have a functional SME conduct a comprehensive review of relevant documentation to evaluate the current state and recommend an integrated future operating model. GenAI can assist with empowering a generalist M&A practitioner to operate more effectively, lowering the advisory expenses and speeding up the evaluation and progress procedure.

Comms - GenAI can be leveraged to design the comms strategy (e.g., platforms, frequency) and potentially communicate with stakeholders, including investors, customers, employees, and regulators, during the integration/separation planning and post-close. AI-powered tools can potentially assist by generating personalized communication materials, onboarding and migration guides, and FAQs.

It’s exciting to witness and be part of streamlining the M&A process by modernizing obsolete approaches. To summarize, 

• There is tremendous potential for GenAI to upend current processes in many phases of the M&A lifecycle, especially in due diligence and PMO, resulting in better operational efficiency.
• Future opportunities for GenAI to potentially absorb private datasets to generate customized results will be transformative.
• Professional service providers will need to evaluate their value proposition in the long-term as their clients might leverage GenAI more often with their in-house resources, affecting their need for service providers.

While growing pains and impacts on individuals are inevitable with any disruptive technology, the long-term advantages of a more efficient and effective M&A process are expected to outweigh the challenges.