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The Next Phase of Artificial Intelligence (AI) Mergers and Acquisitions (M&A)

Next Phase of Artificial Intelligence Mergers and Acquisitions (M&A)

by Aaron Solganick, CEO

December 27, 2023

The next phases of artificial intelligence (AI) are expected to be characterized by several key trends and developments, which may also influence potential mergers and acquisitions (M&A) in the field. 

Here’s an overview:

  • Advanced Machine Learning Algorithms: As AI research progresses, more advanced machine learning models and algorithms are likely to emerge. These could offer enhanced abilities in areas like natural language processing, computer vision, and predictive analytics. Companies specializing in cutting-edge AI research may become prime targets for acquisition by larger tech firms looking to stay ahead of the curve.
  • AI Ethics and Governance: As AI becomes more integrated into daily life, issues around ethics, privacy, and governance will gain prominence. Companies that develop solutions to manage these challenges effectively could be attractive for M&A, especially for businesses looking to ensure compliance and public trust.
  • AI in Healthcare: AI’s role in healthcare is expanding, from drug discovery to patient care and diagnostics. Biotech firms and healthcare companies with robust AI capabilities are likely candidates for acquisition by larger healthcare or tech companies seeking to expand their footprint in this area.
  • AI-Enabled Cybersecurity: With the increasing sophistication of cyber threats, AI-enabled cybersecurity solutions are in high demand. Companies that excel in AI-driven security technologies might be targets for acquisition by larger IT and cybersecurity firms.
  • AI in Financial Services: AI’s application in financial services, such as for fraud detection, algorithmic trading, and personalized financial planning, is growing. Fintech firms with innovative AI applications could be attractive targets for traditional financial institutions or tech companies looking to expand into this sector.
  • Edge AI and IoT Integration: The integration of AI with the Internet of Things (IoT) and edge computing is a growing area of interest. Companies that specialize in edge AI solutions, which process data on local devices rather than in centralized clouds, could be potential M&A targets for larger tech companies.
  • AI Hardware Development: Companies that develop specialized AI hardware, like advanced GPUs or AI-optimized processors, could be attractive acquisition targets for larger tech companies aiming to reduce reliance on external suppliers and integrate hardware development in-house.
  • AI in Automation and Robotics: With the rise of automation, companies that combine AI with robotics to enhance automation in industries like manufacturing, logistics, and agriculture might see interest from larger industrial players or tech companies.
  • Geopolitical Influence: The geopolitical landscape, particularly the race for AI supremacy between the US and China, might influence M&A activities. Companies with technologies critical to national security or economic competitiveness could be targeted or restricted in M&A deals.
  • AI in Environmental Solutions: As global focus on sustainability increases, AI applications in environmental monitoring, renewable energy optimization, and climate modeling could attract attention from a range of industries.

In summary, the next 12 to 24 months in the AI space could see increased M&A activity centered around advanced machine learning technologies, AI ethics, healthcare, cybersecurity, financial services, edge AI, specialized hardware, automation and robotics, geopolitical considerations, and environmental applications. The exact nature of these mergers and acquisitions will depend on broader market trends, regulatory environments, and technological advancements.

Which companies may lead buying artificial intelligence companies in 2024?

Several prominent companies are likely to be at the forefront of acquiring businesses in the realms described previously, driven by their strategic interests, financial resources, and existing foothold in the AI domain. Here are some of the potential leaders in this space:

  • Google (Alphabet Inc.): Google has been a key player in AI and machine learning, with significant investments in areas like natural language processing, autonomous vehicles, and healthcare through DeepMind and Verily. They are likely to continue acquiring companies that align with their AI strategy, particularly those specializing in advanced algorithms, AI ethics, and healthcare applications.
  • Microsoft: With its Azure cloud platform and a strong focus on AI, Microsoft may target acquisitions that enhance its cloud AI capabilities, cybersecurity solutions, and enterprise AI applications. They have a history of acquiring companies that can integrate seamlessly with their existing suite of products.
  • Amazon: Amazon’s vast e-commerce and cloud computing arms (AWS) make it a likely acquirer in the AI space, particularly in areas of automation, AI-optimized hardware, and logistics. Their interest in healthcare AI, as evidenced by the launch of Amazon Care, might also prompt acquisitions in this sector.
  • Apple: Known for its consumer electronics, Apple might focus on acquiring companies that can bolster its AI capabilities in hardware integration, edge AI for devices, and user privacy-centric AI solutions.
  • Facebook (Meta Platforms Inc.): With its focus on social media and the metaverse, Facebook might look at acquisitions that enhance AI-driven content moderation, virtual reality, and personalized user experiences.
  • IBM: As a long-standing player in the enterprise AI market, IBM, especially with its Watson platform, may seek acquisitions in sectors like AI in financial services, healthcare, and enterprise AI solutions.
  • Salesforce: With a strong presence in CRM and cloud computing, Salesforce could target AI companies that enhance customer relationship management through personalized AI-driven insights and automation.
  • NVIDIA: Known for its GPUs which are critical in AI computing, NVIDIA might acquire companies to strengthen its hardware capabilities or to diversify into software and AI services.
  • Intel: Similar to NVIDIA, Intel could look to bolster its AI hardware offerings or expand into AI software and services through strategic acquisitions.
  • Siemens, GE, and other Industrial Giants: These companies, with a focus on industrial applications, might acquire AI companies specializing in automation, robotics, and IoT integration.
  • Biotech and Pharma Companies: Large players in this sector might acquire AI startups in drug discovery and patient diagnostics.
  • Financial Institutions: Banks and financial firms might look to acquire fintech AI startups to enhance their services in areas like fraud detection, algorithmic trading, and personalized banking.

These companies, among others, are well-positioned to be major players in the AI M&A landscape, given their existing investments in AI, strategic goals, and financial capabilities. The actual acquisitions will depend on how AI technologies evolve and align with these companies’ strategic objectives.

About Solganick & Co.

Solganick & Co. is a data-driven investment bank and M&A advisory firm focused exclusively on software and IT services companies. The deal team covers artificial intelligence software, applications and services and has deep experience within the sector.


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