AI: 5 reasons why
The adoption of Artificial Intelligence (AI) is rapidly growing and find seamless ways into our daily life. Think about virtual personal assistants like Siri and Cortana, video games that learn your behaviors, the advent of smart cars, or online customer service powered by advancing natural language processing. Companies like Google, Microsoft, IBM and Amazon have all adopted and fully committed to AI and provided these services to customers. Users have gotten acquainted to these services and make use of them on a daily base, often unaware of the technology that powers the experience. In a way, AI already has become mainstream, even before it has fully matured. Customer expectations are high, not because of its wow-effect, but because the technology acts so natural. This is the paradoxical challenge enterprises currently face to respond to.
38% of enterprises are already using AI technologies and 62% will use AI technologies by 2018
Artificial Intelligence technologies is a broad term that includes a set of different technologies and tools, some well-tested, others relatively new and in development. According to the recently published Forrester’s TechRadar report, it currently includes the following top 10 technologies: Natural language generation, speech recognition, virtual agents, machine learning platforms, AI-optimized hardware, decision management, deep learning platforms, biometrics, robotic processes automation, and text analysis & natural language processing.
AI thrives on large volumes of data. And what is the value of having more data if not in new business insights? A current report from Narrative Science, conducted by the National Business Research Institute, sheds light on the use of AI in enterprises today and in the future and concludes that 38% of enterprises are already using AI technologies and 62% will use AI technologies by 2018. it is not surprise that from the wide range of applications, predictive analysis scores high and that innovative enterprises strive to apply Artificial Intelligence to their data to solve business problems or to generate new insights.
Diving into the subject in greater detail and thinking about practical applications, here are five business reasons why considering using AI technologies in your enterprise:
1. Improve insight into your core business and business domain
Data are becoming critical business assets. Increasingly sophisticated analytics tools make it possible to detect patterns, insights and opportunities that otherwise might be buried deep in the data stores. AI technologies becoming an important component of these analytical efforts. Pulling insights from those data sets and automatically surface and visualize them as recommended actions is a way to gain different or new insights into your business. This corresponds with a survey conducted last year by MIT Technology Review Custom and Google Cloud that queried early adopters of Artificial intelligence. What surfaced is that the top 1 of reasons to apply AI indeed is to seek more data analysis and insight.
2. Improve customer service
Chatbots are frequently used in customer service, especially in banking, retail and hospitality. They direct customers to relevant resources and products at any hour, any day of the week without having to hold the line in wait for the service. With the improvements that Natural Language Processing (NLP), an area of artificial intelligence has seen in recent years, more effective and intuitive chatbots are in the make. Especially in the service context where users have high expectations and little patience, chatbots not only need to understand what’s being said or written, but also have to do that in comprehensive ways. This includes such demanding tasks as contextualize content and relationships, disambiguate meaning and decipher ambiguities in language. Cognitive technologies enable a deeper understanding of human communication and thus serve better in customer service.
3. Satisfy customers by inviting play and fun experiences
How to get in touch with customers and how to understand what kind of products and services they really want? If customer satisfaction is taken as a key indicator of operational and financial performance, specifically in the retail industry, then the overall experience or collective impression a customer takes should be considered. Of course, overall satisfaction is a complex metric and an interplay between rationality and emotions. Experiential and sensory qualities thereby play an important factor when it comes to forming relationships like trust and perception. Machine intelligence is specifically good at presenting facts to customers and to provide them with real-time feedback. It might be evenly good in involving customers in fun experiences, play and sophisticated interaction that satisfy their experiential taste-buds.
4. Gain a competitive advantage for business on demand
An attractive reason to apply AI technologies is the increased speed of analysis and speed of inside into business opportunities. The ability to consume data in real-time and to get immediate information for example about order status, allow for business on demand and smarter marketing targeting.
5. Reduce operations costs and act proactively
Embedded operational intelligence and predictive analysis can support IT teams to work more proactively to prevent enterprise performance issues such as performance alerts or worse case system breakdown. Using data science algorithms that iteratively learn from historical patterns helps finding insights within the performance data to predict when systems are behaving abnormally and allow to take corrective actions before the case.
Last but not least
A more general, but no-less important aspect of using AI technologies in enterprise is that it creates a momentum for creative solutions and fresh thinking. Over the last few years, AI reached into industries such as healthcare, finance and retail. Think about intelligent personal healthcare apps, or the detection of abnormalities in X-rays or MRI’s. It has been picked up by small companies to solve specific problems such as automatizing repetitive tasks, and is entering now the field of creative industries. The questions and problems AI techniques are applied to are diverse and rapidly growing. What they share is the challenge to approach the problem at hand from a fresh perspective. AI technologies invites thinking in terms of statistical models, neural networks and the processing of non-linear relationships between inputs and outputs. Or to put it differently: AI wires our creativity to look differently at a known problem.
Successful application of AI technologies in the enterprise means to make a sharp decision when and how to make use of it. Not all problems are solved best with AI technologies as algorithmically clean problems differ from problems that hinge on prediction. Knowing the potential of AI helps to distinguish how to make effective use of it and how to set up a solid strategy plan for its implementation. The question how to truly drive value from it within a specific business environment and in tandem with other software tools and human skills are key factors to consider.
A good way to start with AI is setting up small experiments. This is an easy approach for every company to start building this new capability.