Artificial Intelligence and Machine Learning are Entering a Time of Massive Market Consolidation

Yesterday, Intel announced the acquisition of machine learning startups Nervana Systems for a rumored $400M. This move is intended to improve Intel’s artificial intelligence(AI) and machine learning (ML) capabilities in its next generation architecture. The acquisition follows the news of Apple’s acquisition of Seattle-based AI startup Turi for about $200M. These series of M&A events are signaling that we are entering a time of consolidation in the AI and ML markets.

The volume of M&A activity in the AI-ML space has to be one of the most active in recent technology trends. Typically, technology markets require certain level of maturity and development before entering a phase of consolidation. From that perspective, the AI-ML market can be considered an outlier as it has triggered large levels of M&A activity since the very early days. The following matrix summarizes some of the high profile AI-ML acquisitions of 2016.

Who Will Be The Most Active AI-ML Acquirers ?

The M&A trends in the AI-ML space are likely to accelerate in the near future. With AI becoming an increasingly important competitive differentiator, the frenzy for AI-ML talent and technology is not likely to stop any time soon. More importantly, the M&A activity in the AI-ML markets is not constrained to a specific sector. The following list examines some of categories of companies that are likely to remain very active acquiring AI_ML talent:

· Internet Companies: Internet power-houses like Twitter, Facebook or Amazon are actively investing in AI-ML technologies as a competitive differentiators. Some of those companies have very healthy balance sheets from their performance in the public markets which should make them very active acquirers.

· Traditional Enterprise Software Vendors: Companies like SAP or Oracle are running behind in the AI-ML space and are likely to bridge that gap with acquisitions.

· SaaS Vendors: Salesforce has been incredibly aggressive investing in AI-ML capabilities. Other SaaS platforms like Workday, Box or Zendesk could also become acquisitive in the space.

· Cloud Platform Providers: Microsoft, Google, Amazon and IBM have been rapidly building their AI-ML capabilities. With large cash reserves, these companies are likely to be active acquirers in the AI-ML market.

· Chip-Device Manufacturers: GPU-based architectures are at the forefront of the AI-ML battle. Intel, Qualcomm, NVIDIA are some of the companies competing for dominance in the space and they should be an attractive destination for AI-ML startups.

· Large System Integrators: Companies like Accenture, Wipro or Infosys have recently announced new services and solutions in the AI-ML space. Those vendors are likely to rely on proprietary software platforms as a unique differentiators and could be active acquirers in the space.

· Big Data Platform Providers: The next chapter of big data platform providers like Cloudera, Hortonworks or MapR is certainly going to be influenced by AI-ML. These companies can also become more acquisitive in the AI-ML markets.