Society has been through several changes from the industrial through to the information revolution. And with each comes the inevitable question: “Are we putting ourselves out of a job?” With artificial intelligence (AI) technologies taking step-change leaps in capabilities and accuracy, there is a lot of talk about whether AI is the next “job killer.” So, will AI automate everything we do? Will we have jobs in the future? Like so many of these questions, the answer lies somewhere in the middle, and it largely depends on the type of work that is being performed.
Organisations are increasingly faced with a dual imperative: improve the customer experience whilst driving productivity and cost savings. Automation and AI technologies are a viable option to help meet both challenges simultaneously. However, AI, like any other business strategy, also needs to align with the organisation’s go-to-market strategy. Some organisations have a deliberate high-touch/high-service approach, which may relegate the application of AI to the back office. For others, AI will be a viable option — in both the front and back office — to drive a specific customer experience.
The information revolution created a challenge for most organisations. Faced with a tsunami of data, organisations grappled with how they could best leverage the insight to reduce risk and see new opportunities — without creating inefficiencies that affect their market competitiveness. Previous technology iterations, like robotic process automation (RPA) and business process management (BPM), required us to understand our processes and create rules based on known repetitive execution paths. Machine learning, a subset of AI, creates a new approach enabling us to look at past behaviour (data sets) and use a probabilistic approach to predict the future. This is why AI is transformative – we are closer to not only mimicking human decision patterns, but also in some ways surpassing it, as machines don’t suffer from data fatigue.
Case in point: An insurance claims process can be automated by leveraging the insight in past claim decisions. AI is used to examine structured and unstructured information, and decide whether to approve or reject a claim. Claims that don’t meet a “confidence threshold” would be referred to a claims agent for review and manual decision. The result would then be fed back into the model to improve automation in the future. As a result, insurance claims agents would spend more time working on complex and uncommon claims, and engaging directly with customers and providers to manage the claims process and deliver a superior customer experience.
AI can also be applied in the front office for customer service. Chatbots (powered by natural language processing) enable us to automate first touch, and even complex, interactions with customers. Depending on the organisation’s strategy, chatbots can be used either as a triage before speaking to a real person or for transactions — enabling end-to-end execution. Building on the insurance example above, chatbots could be used to gather the initial information from a customer to support a claim and even to communicate updates proactively throughout the process.
Thinking back to where we started, will AI automate everything we do? Based on current technology maturity, the answer is no. However, it will bring the next wave of automation and productivity into business processes and customer interactions. The organisations that will thrive in the future will see AI as not just a cost reduction, but rather how people can be redeployed to drive a superior customer experience and differentiate their go-to-market strategy. Organisational change managers and leaders will also be a key consideration for organisations to successfully embed a hybrid-style workforce.
And, to bring some balance to the debate, let’s not forget that AI will create new jobs. Beyond the job creation in AI technology companies, AI will create jobs in other organisations to build and maintain the technology. In the work we do with customers advising on AI, we see a range of new organisational skills and roles being required, like AI Model Curators, Conversation Designers and Customer Chat Experience Managers. Fundamental to AI is line-of-business knowledge, and this results in roles being created in the business rather than just technology functions. AI technologies need to be watered, maintained and enhanced to ensure they continue to deliver an experience aligned with the organisation’s strategy.
Good luck with your AI journey!
This article is the third of a series about AI from Focus the Way Forward. Watch out for our next fortnightly instalment!