The use of AI in healthcare has increased considerably in recent years due to the more widespread availability of big data. However, despite significant investment, most have yet to realize its full potential.
A recent survey from MIT Sloane Management of 2,500 executives found that the majority of projects failed to achieve anticipated results. This will have implications for how AI projects are approached in the coming year (guidance on that to follow in a future article).
There are many fascinating new positive breakthroughs that are also transforming the space. These include the ability to create synthetic data as well as open source language processors that require far less training than the older generation ones.
However, not all breakthroughs are so positive. Deepfake technology using GAN (Generative Adversarial Network – a type of Machine Learning) is now at a point that a single photo can be realistically manipulated into video content where someone is literally putting words in your mouth! I’m sure you have all seen the deep fake of Barrack Obama. If you don’t know about this, watch this YouTube video.
And of course, there are a lot of challenges for AI projects in the areas of GDPR and privacy, not to mention ethics and social implications.
As the technology and competitive landscape continue to evolve, here’s what we can expect in the year ahead:
1. AI and Human Collaboration Increases Throughout Pharma
I was asked repeatedly last year, ‘Will AI take my job?’ Obviously that depends on your job, but in pharma the answer is likely “no.” AI will take over the repetitive tasks and also analysis tasks, but humans are still required for the complex strategic tasks.
More of us will be working with AI-powered tools that are more collaborative. They will allow us to do more of the strategic work enriched with lightning fast analytics using real time big data. It is likely that more of us will be learning new skills to fix skill gaps caused by the changes in the way we work.
2. Personalization of Omni-Channel Marketing in Real Time Will Increase
Amazon, Google and their ilk have a significant amount of data on each person using their platforms. AI turns this information into 360-degree real time view of the customer, including their needs and preferences. That’s how they are able to deliver personalized experiences and recommendations in real time with such impressive results.
This is possible in pharma, too. Eularis have successfully completed next best action modelling projects for pharma clients, which included real time individual personalization of content, channel and sequence. And we did it with 10 big data platforms from the client using artificial intelligence to supercharge customer engagement and reach business goals faster. This demonstrates that you don’t need sane amount of data as Google. You can use this approach with the data you can currently access in healthcare and still get significantly better results.
Although there are many companies offering rules-based approaches, few are based on AI learning from millions of real customer journeys. Companies that get in now to properly implement the latter will have a significant advantage.
3. AI Becomes More Creative in Pharma Marketing
We don’t tend to think of AI as being capable of creativity. Since it has to be programmed to do what it does, how can it be creative? But when you look at how AI works, you realize the more accurate view is how could it not?
AI learns by being fed millions of data points or more relating to the task (so it may be analyzing novels, or images, or content) and learning what works and doesn’t. That’s the same way humans learn many areas, including creativity (even James Patterson has a formula for his novels).
Authors, for example, don’t produce best selling novels the first time they start writing. The craft takes time. Even when a first novel is an outstanding success, it is the result of years of training and previous writing experience.
AI does the same thing, only faster and on a much larger scale. It’s not surprising then, that AI is starting to make strong in-roads into being creative – and successfully so. We already have AI creating better-designed PowerPoint slides, writing better email headers to increase open rate and writing effective content. In fact, an AI written novel almost won a literary prize (it was in the final short list).
While AI ha mainly been used to solve problems, analyze data or handle repetitive tasks such as organizing meetings, creative agencies should be looking toward AI for augmenting their work.
4. AI-Powered Predictions Will Run in More Medical Devices
Just as we get AI-powered predictions on our phone or computers, we will now be getting these built into more and more medical devices. AI is already being used to improve the life and safety of patients with Type 1 Diabetes. It analyzes data from thousands of continuous glucose monitors and insulin pumps and self-adjusts the insulin level to whatever is required.
The same thing can be done with Asthma and COPD with smart inhalers. This will start to become integrated in more and more different device types.
There are many useful AI-powered applications that will gain traction in pharmaceutical marketing in 2020 (if I have anything to do with it!). Alongside that some of the advancements will have implications for privacy, security, and ethics and these will be discussed in Part 2 of this post.
For more information on any of the topics contained here, please contact the author ,Dr Andree Bates, at Eularis www.eularis.com or sign up for our one day 2020 masterclass (date to be determined) on Innovating with AI in Pharma Sales and Marketing in London, UK.