Data, AI, business intelligence & analytics most in-demand areas for M&As
AI, data, business intelligence & analytics are reshaping modern businesses
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Data and artificial intelligence (AI) along with business intelligence and analytics are the most in-demand areas for mergers and acquisitions (M&A), according to buyers. That’s a key finding from new research by JEGI CLARITY.
The advisory firm conducted an in-depth analysis of the data and AI consulting market, shaped by direct conversations with strategic buyers across the sector.
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Buyers are prioritizing in-filling capabilities in high growth areas of the market, the research found. The most common is data and AI (65 percent) followed by business intelligence and analytics (35 percent). Other priorities include enterprise software and cloud platforms, cybersecurity and IT operations, research and product development and industry-specific solutions.
These capabilities are considered key to addressing complex challenges in specific markets such as financial services, healthcare, manufacturing, energy, retail and consumer, with tier 1 geographies (US, UK, Germany) being major economies.
“As AI reshapes business applications, demand for data solutions has been rising fast,” JEGI CLARITY stated. “Companies require service partners who can manage complex end-to-end data solutions. This segment is primed for growth, scaling alongside the data software platforms.”
The market has moved beyond experimentation and hype into real-world use cases. With greater scrutiny around investments, businesses are turning to trusted advisers to guide strategy, optimize spend and drive measurable outcomes.
“Our recent survey of 25 Global Strategic Acquirors demonstrates strong appetite for data, AI and business intelligence capabilities, especially when embedded within or built around core third party data platforms,” JEGI CLARITY added.
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Importance of data governance in the era of emerging AI
AI is undoubtedly transforming the business landscape at an unprecedented scale, but behind the momentum lies a critical enabler of sustainable AI success – data governance. As businesses accelerate generative AI adoption, strong data governance becomes non-negotiable. What’s more, with the shift from generative AI to agentic AI, the importance of data governance will only intensify.
However, over half of organizations do not measure data quality, while 60 percent of businesses will fail to realize the value of their AI plans due to poor data governance, according to Gartner.
Many organizations lack effective data governance strategies generally, let alone those specifically focused on the integration of emerging AI. This is a trend that must be addressed if businesses are to extract meaningful and consistent value from AI adoption.
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