With virtual connectivity on the rise, the tech industry has seen an increase in dual- and tri-track M&A processes, as well as in private equity investments.
2020 was a year in which technology facilitated rapid changes in how people work and live. Despite fewer M&A megadeals and a lower volume overall, tech stood out as an increasingly active and competitive sector that is poised to see further growth in investment activity, particularly as companies look to upgrade their capabilities and offerings by harnessing technology. Several notable M&A transactional trends emerged in 2020, including a rise in dual-track and even tri-track processes. Growth equity also rose significantly as Europe’s startup scene further matured. Amid these developments, key IP and privacy questions have arisen for businesses in the digital sector to consider, including those surrounding artificial intelligence (AI).
Tech M&A transactions
The COVID-19 pandemic accelerated the shift by businesses to digital capacities. For example, e-commerce has further displaced physical stores, and mobile app-based food-delivery providers have become increasingly popular. Consumers have also hastened their switch from traditional media to streaming services. The movement towards digitalisation will likely spur M&A activity by companies seeking to improve their capabilities in this space.
Companies that adapt their business strategies and deliver value in the current environment will be strongly positioned when the economy recovers. Large technology companies face favorable future growth prospects, although they should be mindful of increasing regulatory scrutiny globally.
Increased dual-track and tri–track processes
The substantial capital markets activity that the technology industry has seen will also impact the M&A process. In particular, companies that view the IPO road as a credible alternative to a sell-side liquidity event can use this leverage to drive better terms in an M&A event. The German market experienced several examples of this trend in 2020, including ThyssenKrupp’s sale of its elevator business. In the US, the tech industry has also seen a rise in the number of direct listings and special purpose acquisition company (SPAC) transactions. It remains to be seen whether these trends will also manifest in Germany this year.
The rise of growth equity
Emerging companies have traditionally been backed by venture capital funds. But with Europe’s startup scene maturing, the number of private equity investments in emerging companies is on the rise — particularly in the tech, consumer, and digital health sectors.
The number of PE investments in emerging companies has increased year on year. Recent investments in businesses such as Wolt, Moonbug Entertainment, Zwift, Klarna, Epic Games, and Oatly demonstrate the range of opportunities available to private equity sponsors in this space. While private equity investors are becoming increasingly familiar with venture capital deal dynamics, they are also pushing to align growth deal terms more closely with traditional buyout concepts. (See Latham’s blog for more information on the rise of growth equity.)
AI gives rise to new challenges
AI has rapidly developed in the past decade. Not only has AI gained a solid scientific basis and produced many successful applications, but it has demonstrated the ability to provide opportunities for economic, social, and cultural development, as well as energy sustainability, improved healthcare, and the spread of knowledge.
As society moves from the age of AI development to the era of implementation, governments and companies are wrestling with the ethical, legal, and business challenges of deploying AI and machine learning technology in a globally competitive environment. AI requires collecting vast amounts of data from the real world; for example, autonomous driving cars need video feeds from around the city, and digital health applications depend on the constant availability and comparison of sensible health data. Collating data will initiate many discussions, and intelligent solutions based on data protection law will be important for every business driven by AI.
The significant hardware required for AI is also raising intellectual property challenges for companies. When businesses equip hospitals, cars, and factories with AI, a diverse array of sensor-enabled hardware devices is required to convert the physical world into digital data that can then be analyzed and optimized by deep-learning algorithms. Businesses will need to protect the intellectual property contained in these smart devices beginning from the early development stages, all the way through to long-term exploitation.