AI Is Already Entertaining You
How
technology endowed with creative intelligence changes the way companies
generate and distribute content.
In the fall of 2016, a pop song was released in Japan.
“Daddy’s Car,” derivative of a Beatles tune, had a soothing beat and vaguely
uplifting lyrics: “Good day sunshine in the backseat car / I wish that road
could never stop.” The ditty was distinctive for its authorship. Sony’s
Computer Science Laboratories in Paris produced the song, which was written
by an artificial intelligence (AI) system called Flow Machines. The melody and
harmony were composed by AI, and a human musician mixed the sound and wrote
lyrics for the track.
AI — the new set of technologies that perform tasks that require
human intelligence, such as speech recognition, decision making, and learning —
is rapidly working its way into business operations within many global
industries. Some members of the entertainment and media (E&M) industry have
downplayed its potential. After all, these are creative industries in which
both the germ of the business and the value added to it stem from the
contribution of human ingenuity and people exchanging ideas. The most
successful E&M products and services rely on connecting creative content,
brands, and experiences with audiences.
The more creative you are,
the conventional wisdom holds, the more protected you are, or the less able you
are to benefit from the many advances in technology. And skepticism seems
justifiable when it comes to the ability of machines to be truly creative. In PwC’s Consumer Intelligence
Series (CIS) survey, 24 percent of respondents
said AI could, by 2025, create a Billboard Hot 100 song, but only 12 percent
said it could write a New York Times bestseller and 7 percent
said it could win a Pulitzer.
And yet AI is already very much present in the creative
industries, just as it is exerting an influence on financial services,
healthcare, manufacturing, and most other industries. Which isn’t surprising.
Whether in the form of digitization or social networking, the E&M industry
has long had the necessary levels of creativity, content, technology know-how,
and consumer passion to kick-start innovation. Throw in the low level of legal,
financial, and regulatory barriers surrounding business models in entertainment
and media, and you have a natural proving ground for new technologies.
Artificial intelligence is starting to transform the role of
creativity — in the factors of both production and customer experience. You can
see the impact clearly at two extremes in virtually every market: in startups,
where innovation and disruptive media models are tested, and in industry giants
that are facing an urgent need to alter their 20th-century processes,
technology, and structures.
Working Hand in Hand
As AI becomes more powerful, a sense persists in the entertainment
and media industry that there is a trade-off between creativity, ingenuity,
compelling content, and originality on the one hand, and standardization,
scale, optimization, and repetition on the other. Left brain and right brain.
Instinct and execution. Creativity develops the concept, the film, the ad
campaign, the song, the app; standardization is required to turn it into a
marketable product, a functioning, scalable business. In this view, creative
work is the preserve of humans, and if AI can play any role, it will be in a
small way. Left entirely to its own devices, the thinking goes, technology
would produce bland material, or, worse, go off the rails.
But this polarized view
takes into account only the extremes — as if every ad jingle writer is Mozart
and every computer is HAL from 2001: A Space Odyssey. We have been
conducting extensive consumer and executive research via surveys, and holding
conversations with leaders throughout the E&M and technology, media, and
telecom sectors. And we’ve concluded that the reality lies between these two
extremes. AI has the potential to help transform companies by reimagining the
ways in which people and machines interact — as workers, content creators, and
consumers. It is possible for AI to reach deep into companies’ core operations
to foster creativity and originality at scale. When it comes to creative
intelligence, in fact, the purported trade-off between humans and machines may
in fact be a set of synergies. As technology leaders will tell you, AI is an
industrial advance on a par with the arrival of electricity — it’s that big
(see “Human vs. Machine”).
Human vs. Machine
Historically, the advent of powerful technologies has inspired
equal doses of fear and hope. But something is particularly compelling and
terrifying about AI, which clearly has the potential to displace labor. Our
most recent PwC UK Economic Outlook suggests that up to 38 percent of U.S. jobs
and 30 percent of U.K. jobs are at high risk of being automated by the 2030s.
We know that the most “at risk” jobs are those that are repetitive,
process-driven, and rules-based, such as administrative support positions or
bank teller jobs. Rather than fighting the process, companies should consider
devoting resources to skills training for the many service and manufacturing
workers who will be displaced by machines, and preparing them for the new jobs
that will emerge.
Grappling with new
technologies will be unavoidable for leaders because of two important
structural forces driving AI. First is the supply of new products, services,
and platforms. The typical person’s media diet is, in effect, already designed
by computer-based nutritionists. Every day, millions of Spotify listeners take
their cues from AI-generated playlists. During one National Novel Generation
Month (NaNoGenMo), coders wrote programs that, in turn, generated some 500
novels. “For me, asking if a
business can benefit from AI is like asking if a business can benefit from the
Internet,” said one leader. “It is that fundamental a shift in technology. If
you don’t figure out how to use it and benefit from it, you are going to go out
of business. Your competitors will destroy you.”
The second structural force is demand. The industry shift is being
driven by consumers’ desire to move to a world in which they have greater
customization, spontaneity, and personalization in the way they consume
content, communicate, and engage in commerce. More than half (55 percent) of
millennials in the CIS survey said they would like to select their media by
curating a list that draws heavily on AI recommendations, or simply have it
selected altogether by a bot. The acceleration of AI is arriving just in time
to meet the demand for new forms of digital experiences, to cope with the
growing complexity of curating and accessing digital media, and to address
evolving concerns about security and privacy.
Thus considered, AI is both a strategic imperative and an immense
opportunity — to improve efficiency, create new and better user experiences and
products, free up human labor for more intense creative efforts, and contribute
to value creation. It can be applied to all areas of corporate endeavor:
process, monetization, distribution, and creative work. To date, many companies
have been in AI denial. Some are beginning to experiment, focusing on specific
activities (e.g., the back office or customer service). Others are taking a
strategic, organization-wide view. But in order to make the most of AI, leaders
have to learn to think more analytically about the challenges and opportunities
at hand.
Grasping Opportunities
No single path is best for integrating AI into the E&M
business. The key is to understand the dimensions in which AI can aid, abet,
optimize, enhance, and, yes, occasionally replace human work — and to learn
from what companies are already doing. Next, prioritize the opportunities and
assess whether your current capabilities will allow you to pursue AI
effectively. Doing so will either free up resources or impose new requirements
on you and your colleagues.
Drawing on our interviews
with clients who are leading this work for their organizations today, we’ve
created an illustrative framework of organizing principles for evaluating AI
projects. This approach examines the use of AI tools and strategies in two
dimensions (see exhibit). One (the vertical axis) considers whether the
functions are aimed primarily at optimizing existing workflows or primarily at
creating innovations in the consumer experience. The other (the horizontal
axis) considers whether the activities involve people working alongside AI or
whether the functions are fully automated. We should note that the assumption
typically applying to a 2x2 matrix, in which the lower left quadrant is for
underperformers and the upper right is home to the most evolved companies,
doesn’t necessarily apply here. In fact, significant business value can be
derived in each quadrant. Companies may have activities and initiatives that
fall into multiple quadrants. The level of investment in each quadrant depends
on an organization’s views about value creation and protection, its appetite
for change, its risk profiles, and its ability to execute.
Freedom from Repetitive Tasks
Because of the availability of proven, off-the-shelf artificial
intelligence solutions, many companies start in the lower left quadrant —
automating processes, often in human resources and finance. Many media
companies have lagged in putting effective back-office processes and technology
into place. Thus, the potential for the application of AI is great. One U.K.
media company that is a leader in the exhibitions industry is experimenting
with back-office automation, and expects it will help the company boost margins
from activities such as credit control and customer acquisition.
But these efforts aren’t confined to the back office.
Historically, the out-of-home ad industry hasn’t kept up with other
media-buying trends. One of the brands within a large ad holding company in
Japan developed an AI-based solution for making purchasing decisions on
out-of-home advertising locations, such as billboards. By deploying bots, the
unit has automated the online bidding process for clients.
Efforts aimed at creating
content can also fall into this quadrant. News services (for example, the
Associated Press) are now using AI platforms such as Wordsmith to
generate short articles that summarize a baseball game via statistics or that
are based on the earnings reports of publicly held companies. A movie studio
has used IBM’s Watson to create trailers. By watching an entire film and
selecting six minutes’ worth of scenes, the AI solution can do in less than 24
hours what normally takes 10 to 30 days. When Shelly Palmer, a leading media
technology consultant, publishes his daily newsletter, he writes one new
article and algorithms aggregate additional articles (see “Media’s
Data-Driven Future,” by Deborah Bothun and Art Kleiner). Next, AI generates four
versions of the newsletter, one aimed at maximizing engagement, another at
maximizing clicks, and so on. Programs then mine data on subscribers to
determine which of the four versions will be sent to each recipient.
Better, More Creative
Decisions
A useful rule of thumb says that if you have a playbook for
managing a work process — editing and publishing a magazine, distributing a
film, planning an advertising campaign — algorithms can be developed to help
execute the playbooks more effectively. AI can work alongside people to carry
out tasks that are complex yet repeatable, thus generating powerful insights
and freeing up time that professionals can use to make more intelligent
decisions, as seen in the exhibit’s lower right quadrant.
Studios are getting better at applying advanced analytics and
real-time feedback to shape their marketing campaigns. Using an analysis of
initial uptake and social chatter surrounding a new movie release, one studio
is using an AI-powered solution that makes recommendations for marketing and
monetizing the content across downstream windows such as premium cable and
video-on-demand platforms. Beyond measuring eyeballs for content aired at a
specific time, the new “data factories” that studios are constructing allow
them to measure, and often help direct, a consumer’s online journeys and
actions.
A major U.S. digital company is developing an AI-powered interface
for its ad sales team. When ad reps input information on upcoming client
meetings, the tool provides recommendations on which individuals to target,
challenges that have arisen in previous campaigns, and which ad products and
types of campaigns will be especially compelling to the client.
One of the most powerful contributions AI can make is to shed
light on emerging preferences for people who are designing products intended to
appeal to large audiences. An advertising holding company in the U.S. has
teamed up with technology partners to develop a proprietary AI tool that scours
social media platforms and delivers insights into what types of ads resonate
with consumers. Creative directors and writers thus approach the creative
process with a better handle on what might be expected to work well.
Simplifying Content Creation
A useful way to think about
consumer-facing innovation is to look at it through the lens of “customer
jobs.” Harvard’s Clayton Christensen has put it this
way: “Customers don’t simply buy products or services; they ‘hire’
them to do a job.” And customers — whether they are the end consumers or
companies — are hiring AI to do a growing array of jobs.
In the upper left quadrant of the exhibit, AI fully automates the
creation of content, material, or services aimed at consumers, and the work
becomes more experimental. Here the company is, in effect, going all in on the
ability of AI to create a compelling product or service. In many instances, the
substitution for creative intelligence is complete. Facebook’s Moments app has
a tool that creates short films out of the videos and photos that users post on
their timelines.
Many of the early
experiments in E&M have been in music. Sony’s efforts in Japan to use AI to
write pop songs stand as one example. Bobbie Barrat, a high school student in
West Virginia, trained
a computer to rap in a week using open source
software on a Linux-driven laptop. Having cut its teeth on 6,000 Kanye West
lines, the computer can generate somewhat authentic rap verses. “Originally it
just rearranged existing rap lyrics, but now it can actually write word by
word,” Barrat said.
But companies are also
testing whether machines can effectively create useful advertising content.
McCann Japan decided to pit its AI director against the human creative director
to create a 30-second ad for Clorets gum. When it asked the Japanese public to
vote on which was better (without disclosing the authorship of the ads), the
concept generated by the human director was
preferred, but only by a 54 to 46 percent margin.
Elsewhere,
AI has been taught to improve the user experience of online readers by cleaning
up comments sections. On many news sites and social platforms, it is
difficult for humans to monitor the many comments being posted by readers and
users. Using Google’s Perceptive software, publishers such as the Economist in
the U.K. are able to leverage AI to intelligently filter comments. Empowered by
machine learning, computers can determine — on their own — which comments don’t
meet a site’s standards and can take them down.
Improving the Consumer Experience
With its ability to enable personalization and customization at
scale, AI can be a powerful differentiator for consumer-facing businesses. It
improves precision and speed-to-market, and increases and enhances the
potential for interactions, engagement, and transactions. In the upper right
quadrant of the exhibit are examples of how companies combine human and
computer expertise to create new services and enable people to discover and
engage with content and brands in new ways. Familiar examples such as Spotify
playlists, the Facebook newsfeed, and Netflix’s recommendation engine are just
the beginning (see “Discovery vs. Filtering”).
Discovery vs. Filtering
Content discovery is one
of the most common ways media consumers benefit from AI. Overwhelmed by the
exponential rise in online content, people rely on algorithms to serve up
curated lists and recommendations on the platforms they favor: Spotify,
Netflix, and Amazon, for instance. But the industry must address two challenges
if it is to make discovery and curation work more effectively.
First, although consumers
tend to seek out and access content on a range of platforms, very few companies
have developed tools that enable search and discovery across multiple
platforms such as Amazon, HBO, Netflix, Hulu, and iTunes. MightyTV, launched by
a former Google executive in 2016, aimed to let consumers do just that. But it
was acquired by Spotify in March 2017 and immediately dissolved.
Second, as more content discovery is determined by algorithms
based on consumption habits, our personalized bubbles become narrower and more
difficult to penetrate. In many instances, consumers are becoming defined by
what they are likely to like. The result is that they are less apt
to find new types of content and perspectives outside their prescribed comfort
zones. Having become proficient at making recommendations based on past usage,
AI’s next step of evolution may be to figure out ways to pierce the carefully
constructed filters and broaden the horizons of discovery.
A global technology company is working with athletes to deploy AI
in conjunction with sensors to provide unprecedented visibility into their
performance. Athletes can get instant measurements on key performance metrics
for their sport. The company also uses this information to provide richer, more
interactive viewing experiences for fans.
Tagasauris, a New York–based media technology startup, has
developed annotation programs that break television shows and films down into
shots and scenes, and document key elements of the story (characters, themes,
locations, music, product placements, etc.). Its consumer-facing app connects
events, people, and locations in the show to real-world locations, actors, and
social content. This provides viewers a visual-first deep dive into the drama
as it unfolds — episode to episode and season to season.
JD.com, a Chinese online retailer, has established an AI lab to
investigate perception and cognition with computer learning algorithms. The
results will be applied to face recognition and text and image searching. But
the first use will be a virtual reality fitting room for customers to try on
clothing and other products.
Organizing for AI
The universe in which AI operates is a fluid one. Your company may
easily find itself engaged in activities in every quadrant of this matrix. Some
of the apps on your phone today are purely for work, some are purely for play,
and some are useful for both. The same holds true for AI. This framework should
help you understand what are the best areas in which to launch AI pilots, where
the low-hanging fruit is, and what it will take to move AI opportunities
forward in the near term. Before you start, it’s important to have a handle on
the maturity of the AI technology you will be dealing with. There’s a vast
difference between chatbots and automated newsletter generation on the one
hand, and self-driving automobiles on the other (see “The AI Maturity Curve”).
Once you have a sense of where your company’s current plans or
pilots sit on the matrix, it’s easier to identify how your business strategy
needs to prepare and respond.
The AI Maturity Curve
In “A Strategist’s Guide to Artificial Intelligence,” our
colleague Anand Rao lays out three stages of AI’s maturity curve. In the first
phase, assisted, humans make all the decisions, but AI reduces the
costs of labor-intensive rules-based tasks: Think of Google Gmail’s self-sort
tabs. The next stage is augmented, in which people and AI work
together in a symbiotic way, with self-reinforced learning leading to better
decisions: Think of Netflix recommendations based on past behavior and user
review. The third stage is autonomous, in which people set the
rules and AI makes the decisions with very little human involvement or
oversight: Think of algorithm-driven stock trading.
Shaping Strategy
As shown by the many examples above, AI is here now for the
E&M industry. If you are an executive in the industry, the good news is
that many of these elements are within your reach already. Others will require
significant investment and a leap of faith. Making progress in any quadrant of
our matrix will require targeted investment, as well as some fundamental
changes in how you work, and how you organize to do that work. E&M
companies must evolve from the longstanding organizational architectures and
mind-sets that support a massive volume of repetitive, rules-based work.
The case for hiring AI into the business is compelling, whether
the goal is to have AI work alongside key professionals or to take over certain
tasks and functions entirely. The same IT revolution that has made AI possible
is increasing the necessity to use it. As organizations expand into new
markets, they are getting more complex, engaging with ever-longer supply
chains, and confronting a variety of regulatory regimes. The volume of
unstructured data that companies are generating and absorbing is rising at an
exponential rate. Every tweet, every transaction, every post on social media,
every view of a video — all these actions create data that needs to be managed
and begs to be mined for advantage. Companies’ connections with their
consumers, and with their partners and employees, have likewise escalated and intensified.
Regardless of how proficient a person is with Excel, he or she can’t hope to
stay on top of and make sense of the torrent of bits, bytes, comments,
opinions, purchases, and signals that our systems generate daily.
More Than a Tool
AI is not IT. It’s not simply a tool or a function that can be
outsourced or placed in a silo. Rather, it is increasingly evolving into an
element of strategy. So leaders, and their boards, have to define the strategic
role of AI. They also need to understand how it is playing into the strategy of
their competitors, both direct and indirect. Then they must ask themselves
where AI can have the biggest impact that can translate into shareholder or
enterprise value. Is the primary goal to cut costs or manage margins? Or is it
to drive new revenue growth and create a new level of engagement with
customers?
While these questions are being answered, leaders have to decide
on the important first steps to take in embracing AI. Most leaders in the
E&M world did not grow up in the industry talking about or using AI. And
neither did most of their direct reports. In order to combat the hype and fear
surrounding AI, leaders must educate themselves and their colleagues —
especially those who work in creative areas — on the potential of AI. They need
to move quickly, because the institutionalization of AI is happening much
faster than most people realize. As one executive put it, AI is now part of the
“stack” — the set of software that serves as infrastructure for a business.
The capabilities E&M companies require if they are to succeed
in adopting AI fall into two broad categories: data and organizational
(see “Checklist of Critical Success Factors”). At its root, AI rests on the
ability of people and machines to collect, manage, mine, analyze, and secure
staggering amounts of data. Companies need to attract data and computer
scientists. And once those specialists are on board, to succeed in today’s
competitive dynamics, companies must retain and empower them. They have to
invest to create what our PwC colleague Todd Supplee calls data factories:
systems that can combine data from proprietary, third-party, and public- and
partner-generated sources and extract value. While doing so, they must build
the capacity for data governance and be sensitive to norms, regulations, and
expectations surrounding transparency and privacy. In our CIS survey, 47
percent of respondents said they were unwilling to allow their online
entertainment and media consumption to be tracked, even if it would lower their
costs.
Checklist of Critical
Success Factors
•Build data factories to
feed and power your AI projects.
• Position AI as the new
member of your team, here to drive productivity and stay ahead of the
competition.
• Channel AI into the
business, creating the right environment to nurture and empower those leading
its development.
• Double down on the
human element. Make sure people understand that AI offers them the potential to
raise their game and increase their flow and creative insight.
• Embrace education to raise awareness and create AI advocates
throughout the business.
The Human Element
In adopting AI, a focus on talent is critically important, because
the gap between the opportunities inherent in AI and the number of skilled
resources available to implement them is large. This means that companies have
to make a cultural shift. It’s not simply a matter of CEOs and top leaders
becoming more conversant in the language of technology. Rather, they may need
to think about reordering the way their company relates to its employees.
As Shelly Palmer puts it, AI is a new employee that can help drive
productivity. Leaders must be willing to invite this new employee — and the
people who work with it — to disrupt existing processes and activities.
Companies have to make themselves and their working environments more open and
attractive to the people who work with AI. Beyond the usual imperatives of
appealing to younger workers with flexible, engaging workplaces, companies can
create greenfield sites, insulated from the day-to-day operations, that provide
more freedom to experiment.
Paradoxically, the advent of AI means companies have to double
down on the human element. As automation and machine learning release people
from repetitive, process-driven activities, they simultaneously impose new
pressure on people to deliver value. Employees will be able to spend more time
building relationships, understanding the competitive context, innovating for
the next wave, and creating more engagement within and outside companies. “At a
certain level, I think AI can drive out a lot of general ad agency laziness and
content mediocrity,” as Jon Cook, chief executive officer of the ad agency VML,
put it. “We have to be much better than AI-generated content. AI will force us
all to be better.”
AI is not coming to destroy your business. But neither is it here
to save your business from disruption. Rather, it has arrived at a pivotal
moment in the development of the E&M industry and the people who work
within it. If engaged in the right way, AI can be a catalyst for reinvigoration
of the very parts of companies that are most critical to their growth. AI gives
humans more space to generate more value — to unleash creativity, to exercise
judgment, and to think about the flow of their work rather than the processes
that govern it. When understood and managed properly, standardization and
creativity don’t have to clash. Increasingly, as with Sony’s AI-generated pop
song, they can produce harmonies.
by Deborah
Bothun and David
Lancefield
https://www.strategy-business.com/article/AI-Is-Already-Entertaining-You?gko=dc252&utm_source=itw&utm_medium=20170502&utm_campaign=resp
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