AI will go where the data is

AI will go where the data is

When discussing artificial intelligence, people often end up visualizing what our world will look like 50 years from now. Let’s not look that far, let’s instead focus on which industries AI is most likely to revolutionize in the coming few years.

The key here is data. AI is nothing without a good amount of intelligence (it’s in the name, duh). For AI to be effective, the data collection needs to work well, and it must be available.
Because of this, AI might actually be most effective in some of the world’s oldest industries, like agriculture and health care.

In agriculture, the vast amount of harvest data is used to place seeds and chemicals exactly where they’re needed, autonomous harvesting, automatically watering the soil, and notifying the farmer of what’s going on with the crops. With sensors in the soil monitoring temperature, water levels, and movement, farmers can water only the areas that actually need it, which is both more efficient, cheap, and environmentally friendly.

In healthcare, AI helps doctors make better decisions for each patient with predictive analysis, as well as identify at-risk patients by using pattern recognition. AI has also improved the chances of early detection of certain diseases like breast cancer. With AI, mammograms can be reviewed 30 times faster with a 99 percent accuracy, which can drastically reduce the number of unnecessary biopsies.

Within this field, it also helps that many consumers are joining in on the trend, using wearable devices powered by the Internet of Medical Things (IoMT). The data these gadgets register can be used to help consumers change unhealthy habits, facilitate for doctors to detect and monitor heart problems earlier, and give medical staff better insights into day-to-day patterns.
A more controversial usage of AI in healthcare is humanoid robot caretakers for the elderly. These robots could decrease the pressure on the healthcare system by treating each patient in an optimal way and offering human-like interactions (or even conversations) which could help patients with diseases like dementia stay sharper. Agriculture and healthcare are not the only sectors at the forefront of the AI revolution. Other industries that already have enough data for AI include transportation, delivery services, manufacturing, and construction.

Context trumps data

Context trumps data

Now it’s been proved – context is super important for ads in digital media. With the right audience and the right context advertisers can triple their effect.

This is shown in a study on how advertisers should navigate the digital landscape of new technology, data and purchasing methods. The study is conducted by Schibsted Sales and Inventory (SSI) and Erik Modig, researcher at Stockholm School of Economics, together with 16 advertisers from major Swedish brands.

The fact that an advertisement’s impact is significantly affected by the type of media in which it appears, might not sound like a big surprise – it has been a well-known truth within print for decades.

But within digital marketing there are many opinions about what matters, not least now that programmatic buying is growing. Some say that the context does not matter as long as the right pairs of eyes are reached, others consider the context to be key. There are also differing opinions on how to build brands and create sales. Should you advertise broadly – or focus on target audiences?

And finally, when it comes to conversion and call-to-action – what should be done then? Should slow-moving brands think in the same terms as fast-moving brands? What distinguishes high-engagement products from those with a lower degree of involvement?

The effect doubles

The SSI study focuses on the importance digital context has on the effects of advertising and how an advertiser should think regarding broad and targeted communications. It’s divided into three parts:

• The importance of the digital channel context in creating advertising effects when advertising online.
• When advertisers should choose a broad audience for their communications and when is it better to focus on a specific target audience.
• What effect different types of target audience data have.

The result shows that the context in which the advertising message is published is of great importance. On average the effect doubles with the right audience and triples with the right context and the right target group.

Therefore, even when there is a lot of data about who is being reached, the context almost always trumps data, especially when it comes to getting customers to act and, not least, with lesser-known brands.