We are on the eve of a new artificial intelligence era. All those self-driving cars and smart fridges are great. But what good is AI to you in your day-to-day business? On the basis of 3 concrete applications, we will show the huge potential of artificial intelligence for businesses.
With the massive explosion of data, greatly increased computing power and improved machine learning algorithms, we are entering a new era. An era in which AI applications will be appearing in every aspect of our daily lives and in almost all business processes.
At the moment, it still costs most businesses too much money and time to implement AI solutions. However, now that both big corporates and innovative start-ups are coming up with new applications on a daily basis, the investments required are rapidly decreasing. And that’s good news.
Automate routine tasks and take better decisions
The AI revolution is unlocking a huge business potential for businesses. Machine learning technologies are taking over more – and more complex – routine tasks from employees. Will this enable them to shift their attention to non-routine, analytical and creative tasks? That’s when AI gets the most out of human capabilities.
Moreover, as a business you can distil unique insights from large datasets, including unstructured ones. This puts you in a position to carry out complex analyses, which are steadily improving thanks to machine learning. Self-learning machines also give predictive analytics a boost, so that you can predict the future more and more accurately based on patterns from the past. This means that, as a business, you can not only work more efficiently, but also more effectively. After all, you take better decisions.
In our white paper ‘Artificial intelligence: 5 applications and 6 trends for companies’ we set out five concrete AI applications, on which we will briefly elaborate in this article.
1. Less manual work and automatic decisions in ERPs
One thing’s for sure: AI aspects in ERPs are going to have a fundamental impact on your day-to-day business processes. A large number of human tasks can be automated, including decision-making. For the tasks that remain, many workflow improvements are possible.
The decisions that still have to be made manually will be of a higher quality. Firstly because employees can focus more on the analytical and creative aspects of their work. Another aspect is that AI in your ERP system can verify decisions based on historical data.
Examples (borrowed from SAP S/4HANA) of AI solutions that are already being applied in ERP include:
- Inventories are dynamically managed on the basis of current demand, historical lead times and the business context.
- Automatic cost forecasting for the planning and execution of future projects based on historical project data/li>
- Fewer clicks and typed commands thanks to a conversational user experience.
2. Saving time in recruitment and onboarding
HR departments are complex, labor-intensive and highly data-dependent, and therefore traditionally lag behind in terms of automation. AI can turn things around. The judgement of HR professionals will probably always be necessary. But thanks to AI solutions, they will have better information and more time, capacity and budget to reach those judgements.
In recruitment, an AI application can analyze terabytes of CVs, social media accounts, covering letters and other sources in no time in its search for suitable candidates. Additional advantage: AI can judge objectively – and thus without prejudice. Although there is a danger in machine learning that prejudices from the past are adopted by the machine.
AI can also free up a lot of time for HR staff during onboarding. New employees often overload HR with questions about pay and conditions, for example. AI chatbots can take this over just fine. The new employees benefit from this because they get answers much more quickly..
Other applications of AI in HR include:
- Predicting absenteeism
- Monitoring employee performance through analysis of various data sources and indicators
- Predict which employees are planning to leave based on their computer activities.
3. Chatbots conduct conversations faster (and independently)
The stormy evolution in the field of natural language processing and language recognition is taking us to the point where it is difficult to say whether we are communicating with a human or a chatbot. Such a bot is a piece of software that can conduct conversations with people via text or speech. These machines can keep learning about customer behavior, patterns in general, and the preferences of specific customers.
About 40% of the large companies already work with chatbots, or want to do so soon. They are widely used, particularly in e-commerce, online marketing, travel, hospitality and financial services.
Bots are a cheap alternative to staff, but there has to be an added value for customers or employees who chat with them. And that is still a bottleneck: while chatbots are certainly much faster than an employee, they are usually not better.
Uses for chatbots include:
- Contact with customers, especially for summary answers to questions about products, services and technical problems
- Collaborative work environments such as Slack, where chatbots monitor conversations and provide relevant facts, statistics and recommendations
- Assistance with training.
That AI investments can deliver a good return on investments has been demonstrated by a great many cases. A good example is TravelBird, whose machine learning chatbot handles customer requests completely independently. After just a few months, the bot had taken over two-thirds of requests, with 90% customer satisfaction and a 30% reduction in average processing time.
