Since artificial intelligence was first coined in the 1950s and advanced by Alan Turing and Marvin Minsky as a field of study, the technology has been focused on enabling computers to mimic human beings’ ability to solve problems and make decisions. However, early attempts to match human intelligence, including creative processes, have not come with much success.
However, this has radically changed. Today, it’s clear that AI can be more efficient than humans across many disciplines, and it’s time to accept those intelligent machines trained on robust datasets, know more about our business, industries, customers, and even ourselves than we do.
Like anyone who makes a living creating content or solving problems, it’s easy to perceive this technology as a clear threat.
Although counterintuitively, the evolution of AI offers us an opportunity to accelerate and expand our cognitive and productive processes as a species. AI solutions are becoming powerful assistants that free us from specific, tedious, repetitive tasks to help us chase higher pursuits.
If not, ask Gary Kasparov, the first chess global champion who shamefully lost to an AI system and now advocates for machines and humans to work together.
Like modern cars and electricity, both technologies eliminated jobs and created new ones while increasing productivity and efficiency across society.
However, there are valid concerns around general AI becoming more self-aware and improving itself entering a stage of technological singularity, that is a point in which self-improvement cycles become uncontrollable and irreversible.
Beyond the known difficulties of reaching human-level AI, policies based on Asimov’s Three Laws of Robotics to restrict robot/AI behaviour together with new approaches to make these technologies safe and compliant will become the norm, not the exception. Regulation across parts of Asia and the Western Worldis underway.
The vast amounts of text-based and audiovisual content owned and created every day by media Enterprises marketing teams in companies and freelancers, from archives to live content, makes these segments a fecund vertical for AI solutions to flourish.
By making AI part of creative, production, distribution and monetisation processes, companies have begun to see their early adoption translate into higher returns. A 2020 report by McKinsey shows that 80% of the companies that incorporated AI into their marketing strategy in 2018 and 2019 have witnessed revenue growth.
It is also worth noting that the global artificial intelligence market is exploding at USD 93.53 billion in 2021, with the most significant share of revenue (18%) coming from marketing advertising.
Since early 2020, much talk has happened of AI as a tool to enhance or even replace human copywriters and power chatbots/virtual assistants, mainly due to the impact of GPT-3 and the latest language models coming out of big tech and academia. Many companies have emerged in that space, and VC money has followed.
However, this is just the tip of the iceberg for Generative AI defined as new content created by intelligent algorithms that utilise existing text, audio or images. The next stage of development is not in natural language but the merger of models applied to language, speech, visual and 3D media giving birth to a new Renaissance in digital content creation at scale and fully personalised.
We believe that for the immersive and persistent Metaverse utopia to come to life, social media and user-generated content will not be created manually but assisted by AI initially and then fully automated and personalised.
While we wait for that golden age of 3D Human-Computer creativity to flourish, the next immediate frontier is accelerating video creation without sacrificing minimum quality standards. After all, video is the most potent content for marketers due to its high ROI and strong influence on traffic, leads, sales and audience understanding.
Human beings are great with the creative aspects of marketing and social media but fall short in repetitive tasks, workflow management and data analytics. That’s why AI companies focused on process automation, orchestration, distribution, logistics, and deep analytics have become the first AI unicorns in this space.
For example, Norwegian Air used a machine-learning algorithm to understand customer profiles and behaviours most likely to lead to a booking. They then used the insights from the analysis to match the right content to the right audience, which led to a decrease in cost-per-booking by 170%. Norwegian Air might have slightly more resources at their disposal to generate their machine learning algorithms and manually tag their datasets.
Nevertheless, this is changing fast. Costs of tagging images and videos are decreasing due to technological advancements, and there are plenty of other resources we can take advantage of today as creators and marketers.
For example, on the analytics side, Tubebuddy help creators and marketers find high-performing, searchable video topics. Also, companies like vidIQ allow customers to analyse videos and compare their performance to competitors.
AI is also used to analyse qualitative data through Natural Language Processing(NLP) and Computer Vision (CV) models.
While NLP teaches computers to understand human language (mainly in English), CV models applied to emotion analysis and face recognition can also be used for sales, brand monitoring, recruiting and more.
Audiovisual sentiment and emotional analysis is essentially the process of assessing the tone and contents of spoken and visual communication. They allow us, for example, to understand how your customers react to the content created and what kind of user-generated content is working. Gong.io for sales and Realeyes for customer research and brand awareness are recommended tools in this space.
Even if you clearly understand how your audiences engage with your content across platforms, you still need to create high-quality content to get people’s attention. However, this is expensive and takes way too much time. 66% of marketers don’t make videos because they think it’s too time-consuming, and 37% because it’s too expensive. This leads creators and small businesses not to invest enough time or resources in video, even though it has proven time and time again to be the most effective type of content.
What are we left then as entrepreneurs, social media marketers and creators? We often use our webcams and screen recorders to reduce costs and time spent in content creation using tools like Apple’s Macbook recording tool, Loom, or OBS.
However, this then creates another problem for us: hundreds of recorded videos that our target audiences will hardly ever watch again (the famous “TL: DR” effect). Unless we hire an editor or spend the time ourselves to find the best snackable highlights, that recording will sit somewhere in the cloud or your laptop’s drive to be forever forgotten.
With an AI-powered video highlights generator like Imaginario, there is no need to watch hours and hours of long videos and audio. Its AI automatically extracts snackable clips by topic, or searches inside footage for moments, quotes, objects, characters, emotions… the list goes on.
You can then schedule and publish these hidden gems directly onto YouTube, Facebook, Instagram, LinkedIn, etc. If you’re someone who wants to be in control of the final video cut and design, this platform will soon be integrated with Adobe, iMovie and other similar editing suites.
If you’re a beginner or if what you need is a low level of customisation (e.g. brand logo, background image, CTA), Imaginario will also soon offer this as well and some basic templates for each social media platform. We also recommend using Canva, Animoto, and Biteable, all outstanding options and widely adopted by millions of amateur creators worldwide.
AI has enabled the development of synthetic media: text, audio, images, videos and 3D content created or altered through AI with minimal or no human intervention. This technology promises to democratise content creation by making effective, professional-grade content production cheaper and much more accessible. It is expected that this AI will expand the market from professional creatives to billions of amateur creators.
However, most people are familiar with synthetic media through deep fakes, a process in which this technology replaces a video, image or audio with someone else’s. This technology has been criticised for being used for misinformation, fraud, or other malicious activities.
However, despite its ethical and legal challenges, generative AI is also incredibly useful in content marketing in many different ways.
Beyond the automated copywriting solutions mentioned before, here is a non-exhaustive list in other essential areas:
Text-to-video digital humans:
Synthetic models, product shots, images:
Despite the proven value of these tools to repurpose existing content and adapt it to new marketing needs, the reality is that it is very early days for Generative AIand, especially, in more advanced areas such as:
Because this technology is still nascent, original AI-generated content is currently used in pre-production (inspiration, ideation) and generative art — examples from BMW here and Google’s Deep Dream Generator here. However, it’s just a matter of time for the technology to create the same level of visual effects as a Hollywood studio, but from the comfort of your laptop.
If you’re interested in knowing more about how this technology is impacting the world of marketing, media and advertising, follow us on Twitter (@Imaginario2030) or sign-up for a demo.