Artificial intelligence is loosely defined as a broad set of technologies that think and act like people. These intelligent machines can understand, interpret, reason and engage people in a natural way, as a human would do. It’s clear from working with clients across several industries that there are different AI maturity levels. AI maturity isn’t just about the technology you use; it’s also determined by the people you have in place and the supporting business processes. Understanding what you’re doing today gives you a clear starting point, so you know where to focus your efforts.
Finding the ROI in AI
In the market, there is variety in the number and types of problems that AI can solve, and it will be rare that an organization will buy or even build one AI product that will be able to solve all its problems. Instead, companies will be able to better maximize their ROI by applying different AI technologies to their existing specific business problems. Today, we see several companies finding the biggest ROI with the combination of automation and cognitive service technologies.
For example, Avanade has been working with an insurance company that began by automating rote, manual processes to prioritize claims and assign them to workflows. The company took the next step by adding cognitive services that could read all customer query tickets and understand the customer’s intent. The queries were then categorized and assigned to the right workflow. By using AI to answer more standard tickets, the company liberated people to answer more complex questions, resulting in up to 60 percent gains in efficiency and resolution time.
This example shows that you don’t need to take big steps to see positive results from AI implementations. Simply find the right process, get started and then evolve your approach to deliver business results.
Solve the problem first, then apply the right technology
While it’s easy to view AI as a single technology, it is in fact various technologies that range from automating with cognitive services, all the way to advanced analytics and deep learning to proactively solve problems.
Today, many organizations begin their AI implementation with automation, in areas with lots of manual and repeatable tasks like call centers or back office process like finance and accounting. It’s important to understand the human processes and behaviors that are driving your business and decide how AI can augment them, not replace them. Think less in terms of the technology, and more about the impact that you want AI to have on the people connected to your business – both customers and employees. This is human-centered AI – an approach that focuses on augmenting the workforce to improve customer and employee experiences.
For example, a financial services company in Europe was finding that they were losing a significant number of customers to their competitors. They engaged with Avanade to create machine learning models to better predict customer churn. Looking over a 3-month period and over 100 factors as inputs, the model was able to predict which customers were most likely to churn, and the financial services firm was able to take appropriate action and targeted messages in their next marketing campaigns, reducing the numbers of customers likely to churn by 50 percent.
Shifting to AI-first
Across almost every industry, we are seeing significant ROI for those organizations applying strategic AI technologies. Some of that is quantitative, while others are more qualitative, such as better customer and employee experiences, tracked through net promoter scores and other similar engagement measures. And while benefits are being realized, the true leading companies are beginning to determine how to apply AI more holistically outside of the siloed projects running within specific business units throughout their company.
These leaders are recognizing how to bake AI into their business, across all core functions. Stitch Fix, a leading online and personal shopping subscription service, is a great example of a model-driven company that sold almost $1B of clothing in 2017. You can see just how pervasive the models are in every element of their business. But it’s not all automation, as it’s truly a great example of human-centered AI. Their stylists were able to utilize the data and alter or override the styling the algorithm delivered. This is important because neither the person nor the algorithm can be perfect.
Every business looking to embrace AI should be clear about what data is being used and for what purposes. According to Avanade and Wakefield’s research, 89 percent of IT decision-makers say they have encountered an ethical dilemma at work caused by the increased use of smart technologies and digital automation, with 87 percent admitting they are not fully prepared to address the ethical concerns that exist in this new era. We encourage any organization working to implement AI to create a digital ethics framework that sets out how you will manage the bias that can be inherent in any AI algorithm. This includes internally built applications and purchased solutions. To help address this, Avanade recently created an ethics task force that is developing a digital ethics framework to help us internally and to guide our clients.
Leading companies that take a holistic, AI-first approach, driven by strategic business needs, will see significant ROI in their bottom line and for their shareholders.