Global M&A Dealmakers See AI Adoption Accelerating, SS&C Intralinks Survey Finds

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SS&C Technologies Holdings, Inc. (Nasdaq: SSNC) has released the SS&C Intralinks 2024 Artificial Intelligence in M&A Report, based on a survey of 300 global M&A professionals. The report highlights the accelerating adoption of AI in the M&A industry, with 97% of participants believing AI will profoundly impact their operations.

Key findings include:

• Talent and skills are seen as the biggest challenges in AI adoption
• 43% have already invested in AI training for deal teams
• 25% cite quality control and reliable performance as top risks
• Predictive analytics and generative AI are considered the most valuable AI tools

The report also explores practical applications of AI in dealmaking, such as generating more accurate valuations and enhancing data analysis. As AI adoption accelerates, it is expected to become a significant competitive differentiator in the M&A industry.

SS&C Survey of 300 Global M&A Professionals Highlights AI as a Competitive Differentiator

WINDSOR, Conn., July 24, 2024 /PRNewswire/ -- SS&C Technologies Holdings, Inc. (Nasdaq: SSNC) today announced the publication of the SS&C Intralinks 2024 Artificial Intelligence in M&A Report. Intralinks surveyed 300 global M&A dealmakers from 225 corporations and 75 private equity firms in H1 2024 to understand how and why dealmakers use AI to facilitate mergers and acquisitions (M&A).

M&A professionals believe AI is going to change every aspect of dealmakers' work.

"The rate of AI adoption in M&A has been intense and is unlikely to slow down anytime soon," said Bob Petrocchi, Co-Head of SS&C Intralinks. "M&A professionals believe AI is going to change every aspect of dealmakers' work. The extent of their ability to exploit these novel technologies will be a factor in their ability to stay ahead of competition."

Key findings from the report include:

• The majority of participants (97%) believe AI will profoundly impact their operations and how they run M&A processes. About a third of the respondents are early adopters, confident in AI's transformative potential and its practical applications for their businesses.
• Talent and skills are seen as the biggest stumbling blocks in AI adoption in the next 12-24 months, with 18% of respondents citing the need to recruit and retain knowledgeable personnel. A further 17% point to the need to train existing staff so their firms can move on from legacy technologies.
• Nearly 43% say they've already invested in AI training for deal teams. A third of the respondents (32%) intend to consider restructuring deal teams and their responsibilities as AI adoption accelerates.
• A quarter of the respondents cite quality control and reliable performance as the top risks associated with AI adoption. Another 19% point to data security and privacy as a key issue.

The report also highlights viewpoints on practical applications for AI within dealmaking:

• Predictive analytics and generative AI are the most valuable AI tools for M&A dealmakers, followed closely by machine/deep learning.
• Nearly a quarter (23%) of all respondents believe AI can help generate more accurate and dynamic valuations by analyzing financial data, industry trends and competitor information.
• Close to 30% of respondents believe advanced predictive analysis and modeling will be a key trend shaping the future of AI's use in dealmaking. In contrast, a quarter think the growth of generative machine learning algorithms will be influential.
• A quarter of all respondents think AI will most impact data analysis, while 16% believe AI will be most important for risk and opportunity identification.

Click here to read the full report.

SS&C Intralinks is a pioneer of the virtual data room, delivering software-enabled services across the entire deal lifecycle, including deal marketing, deal prep, due diligence, insights and post-merger integration. Intralinks technology enables and secures the flow of information by facilitating M&A, capital raising and investor reporting. SS&C Intralinks has executed more than USD 35 trillion worth of financial transactions on its platform.

About SS&C Technologies

SS&C is a global provider of services and software for the financial services and healthcare industries. Founded in 1986, SS&C is headquartered in Windsor, Connecticut, and has offices around the world. Some 20,000 financial services and healthcare organizations, from the world's largest companies to small and mid-market firms, rely on SS&C for expertise, scale and technology.

Additional information about
SS&C (Nasdaq: SSNC) is available at www.ssctech.com.
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SOURCE SS&C

FAQ

What percentage of M&A professionals believe AI will impact their operations according to the SS&C Intralinks 2024 report?

According to the SS&C Intralinks 2024 Artificial Intelligence in M&A Report, 97% of M&A professionals believe AI will profoundly impact their operations and how they run M&A processes.

What are the main challenges in AI adoption for M&A professionals in the next 12-24 months?

The main challenges in AI adoption for M&A professionals in the next 12-24 months are talent and skills. 18% of respondents cite the need to recruit and retain knowledgeable personnel, while 17% point to the need to train existing staff to move on from legacy technologies.

What percentage of M&A professionals have already invested in AI training for deal teams?

According to the SS&C Intralinks 2024 report, nearly 43% of M&A professionals say they've already invested in AI training for deal teams.

What are the top risks associated with AI adoption in M&A according to the SSNC survey?

The top risks associated with AI adoption in M&A, according to the SS&C survey, are quality control and reliable performance (cited by 25% of respondents), followed by data security and privacy (cited by 19% of respondents).

Which AI tools are considered most valuable for M&A dealmakers?

According to the SS&C Intralinks 2024 report, predictive analytics and generative AI are considered the most valuable AI tools for M&A dealmakers, followed closely by machine/deep learning.