AI’s role in recommending TV programming to viewers and informing programming decisions are just two examples of how the technology is changing the media workplace. three main drivers for AI’s adoption in today’s workplace: the enormous amounts of data now available for driving business decisions; the role of cloud-based solutions in accelerating technological upgrades; and the quickening pace of computational processing power, as demonstrated by today’s smartphones.
Last week, an IBM computer successfully debated human beings. The computer may have even bested one of its opponents. Artificial intelligence (AI) and machine learning is all around us. The good news is that it has some practical and value-enhancing applications for TV broadcasters and other media companies.
Last month, at Media Finance Focus 2018, the annual conference for MFM and its BCCA subsidiary, AI was the topic of several educational sessions.
Consider programming. Thomas Siegman, EVP of client relations at RSG Media, moderated a session focused on ways media companies are using AI’s predictive analytic capabilities to generate better returns on licensed programming. He introduced the discussion explaining AI can help the bottom line by identifying small changes in organizational decisions that produce big results.
Oktay Arifkhan, SVP of analytics and measurement sciences at Viacom Media Networks, described how predictive analytics allow the company to anticipate the audience that a show will attract depending upon which shows from a competing TV network are scheduled for a certain time slot. The decision is complex he said, “there are thousands and thousands of variables that have to be analyzed.”
Combining audience projections with advertising data helps networks determine the best ways to maximize their return on investment (ROI) for a piece of video content. Sameel Osuri, VP of global content operations at Discovery Networks, was also a panelist in the session. He explained to attendees: “In the old ROI model, if it wasn’t going to generate enough money right away, we didn’t do it. Now, we can predetermine the value an asset will provide to us over time through a variety of different channels, including merchandising, online and global distribution opportunities.”
Viewers Feel Overwhelmed
The bad news is that consumers have more choice than ever before. In an article for the May-June 2018 issue of MFM’s member magazine, The Financial Manager (TFM), Zone-TV CEO Jeff Weber looked at the competitive landscape for video programming and the opportunities for AI to help direct viewers to programs of interest. He begins by saying that a few years ago, FX Networks’ CEO John Landgraf predicted that there would be nearly 500 original scripted series available from broadcast, cable, and OTT services by 2017. The actual 2017 number, says Weber, was 487.
Whether you believe that the number will continue to increase, plateau or decrease, no one can argue that it is easy to find all this content or that consumers really know where to look for it. In fact, there is research to show that the number of TV networks watched by any one viewer is actually decreasing. Between 2012 and 2017 channel surfing decreased markedly, according to a fall 2017 study from Forrester and Simulmedia. The study also found that the number of people who watch one network daily has doubled and the number who watch just two networks daily has almost doubled.
It appears that viewers are becoming overwhelmed. Weber cites a PricewaterhouseCoopers study, which reports that 62% of TV consumers find it a “struggle” to discover something to watch. That sentiment was also reflected in a study by Hub Research, where half of the respondents agreed with the statement “there are so many TV programs to choose from it’s hard to know where to start.”
Pairing Interests with Recommendations
OTT services such as Amazon and Netflix are already using machine learning to recommend video programming based on consumer viewing history and indicated areas of interest.
ZoneTV’s Weber believes TV programmers can use AI to provide their viewers with increasingly tailored and personalized content in real time. As he explains: “This content discovery imperative would be met if MVPDs could leverage the EPG to maximize exposure, providing simple navigation without switching inputs or devices.”
Similar capabilities could also become available to local TV broadcasters as new technologies like ATSC 3.0 provide more viewer data. In the meantime, AI can help stations take advantage of their online connection with viewers to pair interests in particular programming, such as local high school sports, with notifications concerning upcoming shows they may want to watch.
AI’s role in recommending TV programming to viewers and informing programming decisions are just two examples of how the technology is changing the media workplace. Todd Lohr, a principal and U.S. practice leader in KPMG’s artificial intelligence practice, encouraged Media Finance Focus 2018 attendees to “look left and right” within their organizations and see how the tools of the “fourth industrial revolution” are already being used for optimizing their company’s financial performance.
These examples include financial management operations, such as accounts payable and other accounting functions that involve highly manual processes.
Lohr sees three main drivers for AI’s adoption in today’s workplace: the enormous amounts of data now available for driving business decisions; the role of cloud-based solutions in accelerating technological upgrades that were once reliant on replacing on-site computers; and the quickening pace of computational processing power, as demonstrated by today’s smartphones.
KPMG’s Lohr also pointed out that devices, such as smartphones, are show that society has moved from machines that “acted like humans,” like the robotics introduced in assembly plants, to “learning like humans,” as demonstrated by Apple’s Siri app. The next big step will be machines that can “think like humans,” which is considered the Turing Test.
Lohr points to the belief among some AI prognosticators, like Google’s lead engineer Ray Kurzweil, that the year 2029 will be this point of singularity, when a single computer can demonstrate human-level intelligence.
As with any industrial revolution, AI’s adoption is going to result in a major workforce shift. A recent gathering of CEOs in France addressed the importance of retraining employees for new, value-driven jobs when machines take on the tasks they once performed. Media enterprises and other companies that depend upon a breadth of consumers with disposable income have a lot riding on this discussion.
Regardless of how soon or how sweeping the changes from AI’s adoption, Zone TV’s Jeff Weber reminds us that machines that can learn like humans are already providing a competitive advantage to some media organizations.
I am interested in learning how your company is already harnessing some of its potential and how MFM’s upcoming educational programs can help you to address both its challenges and opportunities.
Mary M. Collins is president and CEO of the Media Financial Management Association and its BCCA subsidiary, the media industry’s credit association. She can be reached at [email protected] and via the association’s LinkedIn, Twitter or Facebook sites.