The media industry roundtable discussion was hosted by James Mawson, founder and editor-in-chief of Global Corporate Venturing. It took place on the second day of the eighth annual Global Corporate Venturing Symposium in London.
The session was prefaced by an observation on the evolution of market capitalisations of media companies, some of which have grown tremendously over the past two decades. The media space has also encountered the entry of players from the broader tech industry, such as Apple, Alphabet, Facebook and Microsoft, that were not actively involved in the media space, or which simply did not exist 20 years ago.
While participants noted the shift to digital marketing and the increasing importance of data analytics, much of the discussion revolved around the general paradigm shift driven by artificial intelligence (AI).
Some participants expressed that, in terms of content production, the fundamental change in the past decades concerns better equipment and streams of data, while the nature of a journalist’s job has remained essentially the same. Technology has spurred the rise of data-based journalism and allowed for some automation, but at present no machine can write an article better than a human.
Participants pointed out that AGI (artificial general intelligence – AI that is equally or more powerful than human intelligence) is at least 30 years away from the present, which lies far beyond the investment horizons of most media corporate venturers in the room.
Some noted that one of the hottest issues involves content distribution over online channels, which are dominated by companies like Facebook and Alphabet. Among other things, participants appeared to agree there are opportunities on the monetisation side of distribution and the reinvention of subscription-based models.
The quality of AI-generated media output is largely contingent on the quality of the data available, it was noted, so platforms like Google and Facebook which oversee large amounts of data hold a clear competitive advantage.
Other applications of AI mentioned during the discussion were in image recognition or analysis that can used by e-retail and e-commerce platforms.
Many AI-focused companies are sector-agnostic, so media companies should try to use them to help analyse large quantities of data. This way, they can streamline internal processes, which would allow them to reduce the need for data analysts and scientists.
It was generally agreed that while media and telecommunications is a key space likely to be disrupted by AI, at the moment the overall focus is placed on complementarity – simplifying and organising jobs done by humans – rather than the replacement of human labour.
However, the most astounding example given was from a business services company, which has managed to automate the equivalent of 40,000 jobs while nonetheless managing to provide its employees with other positions, allowing it to expand tremendously.
One participant drew a distinction between AI and machine learning (ML), and others pointed to examples of ML being used to identify fake news by enabling users to verify the veracity of a story. ML technology is also used to identify sources of fashion in video content such as films or TV shows, linking to retailers selling similar clothing.
ML and AI technologies have a wide range of possible applications in call centres, human resources and recruitment, localisation including real-time multilanguage transcription and translation, brand safety and customer services.
A participant cited the example of a recruitment chatbot, with which job seekers were willing to spend more than 30 minutes on average. There was also an example of a bot that can be sourced to design a logo for a company.
During the discussion it became clear that media markets differ widely and the applicability of AI and ML may greatly vary across geographies. In Asia, media tends to be highly regulated, which requires editors to make sure no important stakeholders are offended or that content is not explicit in nature.
Participants also touched on the issue of ethical concerns in media investment. One pointed out that they often have to ask themselves whether to invest in gaming companies, as their products are consumed by children and teenagers and are potentially very addictive.
On a broader scale, the more pressing apprehensions touched on whether it is really ethical to invest in automation, AI or ML if it could directly result in workers losing their jobs at some point in the future.
The end of the discussion revolved around the most interesting existing strategies for media investors, and the app market and ecosystem around Tencent’s WeChat messaging app was cited as a great example of how media can be converged with other commercial activities.
However, it was noted that one of the biggest challenges in integrating media, entertainment and commerce (for instance, linking to attire worn by stars on TV shows) lies in the difference in margins, which can be in the double digits in media and up to 10% in e-commerce.
Attendees also highlighted the importance of creating a relationship with end users. One noted that consolidation is happening in the sector and in order to be a winner, one must first strive for scale, though participants generally agreed on the importance of partnering and collaboration.
