29 apr The impact of artificial intelligence in professional services.
How is Artificial Intelligence Used in Professional Services?
We have received this question several times from our clients. To give a bit of guidance on this topic we decided to write an article specifically dedicated to give insight on this topic.
There has been much hype over the last decade as to how artificial intelligence ( or AI in short) is going to augment or replace roles in blue-collar sectors such as construction and manufacturing. This comes with automated machinery and robotics that will most probably see humans replaced or move into new knowledge-centric roles like data and analytics.
However, AI is also playing a big role within professional white-collar industries like law and medicine. Developers are building models that can take over vast amounts of work and bring with them the potential to transform even the highest status of jobs in those fields.
In this article, we will have a closer look at exactly what we mean when talking about AI and why it is disrupting professional service sectors.
What is AI?
People often hear about AI and jump straight to an apocalyptic world as a bunch of Terminators come along to destroy us all. This is quite a common misconception. Ultimately, AI is whatever humans want it to be. For now at least, machines are fed rules to give it an idea of how it needs to behave, known as training data and from there on in, AI algorithms can learn and start to function independently.
The key to AI is data. It will do what it is told to do via data and rules, whether they are built correctly or not. Companies need a strong foundation of data before they can begin to use AI technology. One of the strengths of AI technology is the ability to teach itself how to understand the world around it.
Back to our Terminator example. In the movie, the robot goes through the phone book to work out which Sarah Connor it needs to target. It does this because the training data was not sufficient to let the robot know the location. Data is key to successful AI.
In professional services, when we talk about AI, it generally refers to the use of vast amounts of data to create incredibly smart tools and algorithms that can then learn for themselves. These machines will then be able to either augment or replace tasks that previously need human intervention.
AI in professional services
There are numerous ways which AI is impacting professional services through automation. We will look at some of the key applications.
In sectors like law, finance and healthcare, workers can get bogged down in huge numbers of documents that hit their desk every day. This doesn’t just include paper documents but also emails, web forms and anything else that a customer or client sends into a business for review.
AI technology is the perfect solution for augmenting document review processes. If you think about a law professional, they will receive documents, images, videos and audio about a specific case. Instead of having to work through all these items, AI technology could tag the important elements and provide instant insights.
For example, let’s say there was a motor accident being investigated. AI applications of machine learning and computer vision could take an image of a vehicle, instantly acknowledge the damage and assess then tag the image. If the case were being handled by email, AI can take the communications, tag the important information and apply it directly to the applicable parts of a legal or claim case.
Professional services firms are using AI technology to draft confirmation letters and send reminders to customers before deploying machine learning models to detect any fraudulent invoices which they can do at 97% accuracy. AI technology has been used by companies to read 80 million pages per second.
Professional service firms will often use their data to analyse accounts and provide profit and loss sheets. However, AI applications help them to look forward rather than always looking back. Let’s face it, you cannot change the past. Machine learning algorithms will consider all the past data in the business. In some firms this could be vast. For example, a law firm would have thousands of cases available. The data models can take this information and predict the best course of action for a new case based on those that have already happened.
At a simpler level, an accounting team could bring all historical transactions into a model and use that to predict what the likely position of the business will be in forthcoming months. Any business actions that are taken can be backed by data rather than relying on “gut feeling.”
There are several off the shelf solutions which provide predictive analytics to the healthcare sector. One example of a AI solution in the healthcare is the use to prevent infections by predicting the likelihood of patients susceptible to central line associated bloodstream complications.
The remit of predictive analytics is vast and can serve any firm with data.
Firms are deploying machine learning algorithms to review mass volumes of transactions for potential errors. Anything they find can then be passed to a human for review. This can save a lot of time as compared to processes fully carried out by human labour.
In time, these systems could replace the need for human auditing, once they have enough data to understand every possible situation. This could prove tricky with some activities like filing a tax return where a degree of human understanding is still needed with some transactions.
Risk and Fraud
The majority of professional services will be dealing with money. With that, they have a high risk of fraud and other malicious activities such as money laundering. Machine learning algorithms can be trained to spot patterns in data. When there are anomalies in behaviour, the models will send alerts to the relevant parties for review. This is fundamental to the processes in banks and other financial service environments. For example, if there were suddenly a spike in transactions across a specific account, these would be picked up by AI.
A similar set of rules can be created for compliance and regulation. With so many data protection laws and regulation, it is important that firms validate their data given the risk of hefty fines with the likes of General Data Protection Regulation (GDPR) in the EU.
There are many ways that professional services firms can make best use of AI that go above and beyond this article. Many are using it to automate content and marketing as well as their digital efforts. Others are now able to better predict workforce needs and automate processing of repetitive tasks. Whatever the use case, AI can bring substantial benefits to professional services and now is the time to invest, else risk falling behind the competition.