Getting Started with AI

By Mary Yurkovic, Director, Smart Content Council, MESA –

Artificial Intelligence (AI) continues to be a big buzzword in the M&E space and for a very good reason. It not only represents a major step forward in how computers can learn, its most important benefit is how it helps to power essential business processes. The most tangible wins are in terms of automation and efficiency. This in turn improves time to market and enables stronger results as businesses add value for their customers. That is the good news. The bad news is that many organizations are still not adopting it.

AI applications mark the next evolutionary step in digital transformation: Computing, sensing, networking, and data generation are only the beginning. The ability to process data more quickly and intelligently across systems, leveraging hardware, sensors, and cameras, and digitizing language itself, marks the next era of organizational transformation.

On the macro level, AI falls into three categories: Big Data, vision, and language. Most think AI is driven by Big Data analytics, however, there is an explosion of areas having to do with vision and language perception capabilities, which will also feed the growth of AI long term.

Because AI is a combination of technologies, not just one, the landscape or “platform” consists of multiple types of AI applied or configured in conjunction with other technologies. In the digital asset management (DAM) world for example, DAM and media asset management (MAM) can be combined with deep learning and natural language processing (NLP) and connected with metadata and image recognition tools.

On the micro level, AI may seem like a massive, and intimidating, undertaking. One of the most valuable benefits of AI, however, is that it can be introduced in an incremental fashion. A great way to start is with a business problem. Keep it narrow at first, and see what solutions or resources exist to help solve for that business case. As in any technology adoption, it should be about solving for a business need, versus adoption just for the sake of the technology. Here are a few sample cases to get you started.

Visual recognition and tagging

In industries like ours, AI provides us with the ability to process large volumes of images and video, and to prepare them for discover-ability and reuse. Visual recognition functions like image classification can ultimately help creatives to discover content they have not have otherwise found. Those “leftovers” from a photo shoot may not have value for the original use, but once found by the right creative the reuses can be endless. This is also dependent upon the usage rights which can also be a part of the AI ecosystem. The ability to associate and classify content already recognized can also trigger workflows involving review and approval.

Converting paperwork into digital data

Processes like document scanning, optical character recognition (OCR), and other conversion processes have leveraged tools to digitize large volumes of talent releases, contracts, and other unstructured paperwork.

By digitizing your paperwork (or connecting your digital data from the beginning) you can leverage AI to expedite the process of capturing key metadata (like talent, title, subtitle, location). This digitization process can convert unstructured data into powerful “insights”.

These processes also can help to meet regulatory requirements without the burden of storing paper records, and increase the speed and accuracy of information discover-ability. Instead of just extracting the text, images and signatures from documents, there are AI tools that learn the context of documents, and can trigger workflows accordingly, to either file documents away in a repository, or send them to other applications for attention.

Prevention of threats

Human security analysts do their best to keep pace with the latest threats, but in many cases, they are overwhelmed by many emerging cyber threats. “Cognitive security” is a way for companies to gain leverage through strong AI.

As with implementing any technology, using AI requires a solid strategy. To be successful, one must start small and always take change management into consideration. With AI, we are talking about the ability to exponentially accelerate cognitive powers of the human brain. This will have meaningful impacts across the entire value chain of a business – from back office operations like finance automation to improved customer insights, personalized marketing and consumer experience. Now that is smart content!


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