Alex Dale looks at where we are with AI and how it might help pharma sales

Research into artificial intelligence (AI) started in the 1950s but the technology has only recently been put to use by industry. In fact, this time last year, just 15% of businesses were using AI and 31% planned to use it within a year. According to Veeva, the technology could transform pharmaceutical sales in 2019.

Put simply, AI is the development of ‘intelligent’ computers that can perform a number of human-like tasks. The technology should develop traits, such as reasoning, problem-solving, perception and planning, and learn from past experiences. Overall, AI should think and behave rationally, in a way that is similar to humans.

Another buzzword in the area is machine learning – a branch of AI. In contrast to AI, which mimics human capabilities, machine learning trains computers using huge quantities of data in order to recognise patterns and make decisions without direction. Machine learning algorithms have been around for a while, but a recent development is that they can now be rapidly applied to big data. Netflix is currently using the technology to tell you which film to watch or series to binge on next.

AI has come a long way and is now integrated into our everyday lives, as we’ve seen with Apple’s Siri and Amazon’s Alexa. However, these systems are considered ‘weak’, meaning they perform specific tasks very well but require direction. The goal is to develop so-called ‘strong artificial intelligence’, which would make its own decisions and intelligently handle various situations.

Some are fearful of the technology. The late Stephen Hawking once said: “The development of full artificial intelligence could spell the end of the human race… who are limited by slow biological evolution.” However, others are keen to explore the impact it could have across a range of industries.

AI remains a work in progress; however, the technology has already reached, or is getting close to, a number of industries.

For example, banks are using AI to cut costs, up their efficiency and increase security. Improved voice and chatbots offer an alternative to human customer services and could save the industry up to $450 billion by 2030. Internal processes such as IT requests could also be automated, allowing banks to focus on making money. Meanwhile, the pattern recognition capabilities of AI and machine learning mean the technology can be trained to spot fraudulent activity in real time, making it an asset in the fight against cybercrime.

AI has also made self-driving cars a genuine possibility, with Tesla leading the way with its ‘Autopilot’ hardware. Tesla’s co-founder and chief executive Elon Musk believes we will see a fully self-driving car by the end of the year. Similarly, Japanese shipping companies want to develop self-navigating vessels, which would use AI to calculate the safest and most fuel-efficient route to their destinations.

Moving closer to the world of pharmaceuticals, healthcare could also benefit from AI. In 2018, cancer caused 9.6 million deaths worldwide, but the technology makes earlier diagnosis and safer treatment possible. It allows fast and accurate biopsy analysis, reducing error and the need for repeat tests. Additionally, an algorithm is being developed to identify lower, tumour-shrinking doses of drugs that provide effective treatment with reduced toxicity.

What could it do for pharmaceutical sales?

AI has already proved itself as an effective tool to support the research carried out by pharmaceutical companies. However, as companies begin to invest heavily in the technology, they would be wise to explore the impact it could have commercially.

In January, Paul Shawah, senior vice president of Veeva Commercial Cloud, backed AI to make a big impact on the life sciences industry in 2019, noting “we will move towards an AI-driven workforce as artificial intelligence becomes a standard capability across enterprise commercial applications”.

He went on to say: “AI will not only continue to improve sales force effectiveness with suggestions on their next best actions… it will [also] automate claims-reference linking in content management for marketing operations.”

According to Accenture, AI could help workers to use their time more efficiently, increasing labour productivity by up to 40% – just the sort of boost that sales reps need.

The impact of AI on pharmaceutical sales can start before the sales rep meets a customer. Machine learning can separate customers into highly specific segments, allowing sales teams to personalise their activity to greater degree. For example, in addition to therapy area, doctors can be segmented based on factors including interest in new drugs, location and availability.

In addition, AI can recommend materials based on a sales rep’s previous meetings with a customer and makes them easy to access. For example, if a doctor has expressed an interest in drugs for diabetes and cardiovascular disease before, the sales rep can be told to come equipped with information about relevant drugs. This ensures that personalised, impactful messages are shared, and less time is wasted while the sales rep searches for materials during the meeting.

Going one step further, Novartis is using AI to tell its sales reps what to say during meetings. Novartis’ pharma chief executive, Paul Hudson, told FiercePharma that the company’s ‘virtual assistant’ will make sure his sales team are “talking about the things that the healthcare professional is absolutely interested in.” Elsewhere, Pfizer Australia teamed up with AI provider, Complexica, back in 2017 to simulate sales and marketing strategies and resolve tricky ‘what-if’ scenarios.

During meetings, AI could transform the way inventories are taken at pharmacies. Currently, sales reps do this manually; however, this is associated with human error and reduces the time they have to engage their customer. Instead, images of the pharmacy’s shelves could be taken and analysed using AI to provide useful data about a company’s own drugs, as well as those of their competitors.

After a meeting, the sales rep logs their actions in a customer relationship management system. This, along with customer prescribing and browsing information, is a huge amount of data that, at the moment, sales reps cannot use. However, if data is continuously fed into an AI system, it could help pharmaceutical companies to target the right customers, personalise messaging, and determine the most appropriate type and frequency of interaction.

We’ve seen that AI has the potential to increase the efficiency of sales reps throughout the sales process. Tasks, for example, sourcing relevant materials for the customer, may sound simple, however, many reps are struggling to do this. By putting AI in control of some of the responsibilities that currently lie with sales reps, they will go into meetings better prepared and equipped with targeted resources, giving them the power and confidence to close more deals and boost sales.