Search engine Google is one of the best examples of how intelligent systems impact our private and professional everyday life and of how disruptive AI technologies can be. However, we also use semi-autonomous systems while driving, and even while flying we trust the artificial intelligence of the autopilot.
Artificial intelligence has long since ceased to be science fiction. AI is a fundamental part of our daily lives now: facial recognition at borders, assistants like Alexa or Cortana, semi-autonomous driving, online trade, chatbots in customer service and predictive maintenance.
The digitalisation of processes and documents, the surge in computing power, especially in the cloud, and the cut in prices for computing capacities and processor performance is contributing to ever new use cases and specific business models based on AI technologies.
Moreover, platforms like Amazon Web Services, IBM, Google Cloud Platform or Microsoft Azure provide technologically advanced AI tools with which business models and solutions for communication and process automation can be developed.
Where are medium-sized businesses on their journey to AI? Is it already a reality or still science fiction? Luenendonk tried to answer this question together with Lufthansa Industry Solutions in the summer of 2018.
Together, they conducted a survey and asked more than 130 CDOs, CIOs and IT managers working at major companies about AI technologies in their enterprise. 53 percent of respondents work in companies with revenue of more than a billion euros.
The survey shows that almost all of the surveyed companies are already convinced of the various possibilities of artificial intelligence. Nine out of ten manager believe that the use of AI will fundamentally change their company.
Only two percent of responding managers think that AI will not be relevant for their company. The remaining 8 percent are still evaluating the benefits and risks of the technology and therefore do not have a final opinion on its potential for their company just yet.
Especially in the banking (95 percent), logistics (95 percent) and insurance (100 percent) industries, respondents believe that AI can fundamentally change their business models. Manufacturing companies also see the disruptive potential of AI (83 percent), but 17 percent of them are still in the exploration phase and do not have a conclusive opinion yet.
Tried and tested use cases which have the potential to disrupt business processes already exist: digital asset managers (robotic advisors) in the financial industry, semi-autonomous driving, machine learning for personalizing the (online) retail experience of customers or for detecting errors in machines or systems with drones through image recognition.
AI projects with machine learning are especially popular at the moment, for example for predictive plant maintenance, but also for automation of routine tasks. In this area, a lot of tangible projects and use cases are being implemented.
Artificial intelligence as part of digitalisation strategies
Almost every second company has already adjusted their strategy to accommodate AI technologies in the future.
This leads to the conclusion that these companies already have a concrete vision of their digitalisation strategy and the necessary changes (which is not always the case). Especially banks are including AI concepts in their business strategy (70 percent).
What’s interesting is that only a third of manufacturing companies has already adjusted their business strategy to the possibilities of artificial intelligence. However, 65 percent of CDOs and IT managers of this very industry stated that they are already using AI technology.
This goes to show that AI in many major companies is still a field of experimentation which is slowly developing because of use cases and first prototypes. Contrary, major manufacturing companies are already using AI very strategically in their daily business processes.
The survey also shows that most companies want to leave the experimental phase behind in the upcoming years and make artificial intelligence strategically important. 75 percent of respondents expect AI technology to substantially contribute to business strategy.
The banking (86 percent), logistics (84 percent) and telecommunications (83 percent) industries are the most optimistic about AI’s contribution to business success.
Number of AI rollouts is increasing
For a more detailed analysis of the current state of AI, let’s take a look at the market of IT service providers and the projects they are currently overseeing.
According to a Luenendonk survey titled “The market of IT consultancy and IT service in Germany“, in 2017, leading German IT providers had a high demand for support with projects closely connected to AI, like the automation of business processes, digital customer experience services and big data analytics.
However, the number of projects specifically dealing with robotic process automation (RPA) and artificial intelligence was not very high. 24 percent of the surveyed IT service providers stated that RPA was a driving factor of their business success, while 37 percent said that they had a high demand for support with projects involving artificial intelligence.
The leading 25 IT service providers in Germany report much higher numbers, which leads to the conclusion that especially major companies are dealing with these topics while mid-sized businesses are still waiting on more use cases.
More IoT projects
Furthermore, the surveyed IT service providers said that IoT projects lead to a high demand for external support. In the upcoming years, two out of three IT service providers expect a surge in demand in this area.
With the increasing number of IoT projects and the corresponding data, the base for effectively and efficiently implemented AI system can be created. Consequently, the importance of AI is increasing with the number of IoT projects.
The cues that IT service providers are picking up from their customers lead to the conclusion that a wave of rollout projects will be coming in the next two years.
As a result, 66 percent of respondents are adjusting their portfolio accordingly and towards the development and deployment of AI use cases and IoT. At the same time, more and more IT service providers are looking into the RPA trend and invest in corresponding skills and capacities (34 percent).
AI technology offers various benefits for businesses. However, it is still facing a lot of challenges, making it hard to use AI tools in daily processes.
The number one reason why AI technology has not been implemented yet is the protection of sensitive customer data. 68 percent of respondents said that they see challenges regarding the combination of data protection and AI tools. Especially the trade and logistics industries seem to be concerned about the effect of AI on data protection. 77 percent of respondents from these industries stated that the biggest challenge is handling sensitive customer data.
In this context, 22 percent of interviewees fear that there will be new IT security vulnerabilities because of the implementation of AI technology. Respondents of the trade and insurance industries were more likely to raise concerns about new IT security leaks caused by AI. This is an indication of vulnerable legacy IT systems.
12 percent believe that their companies are not ready for the implementation of AI. Especially trade businesses do not think that their IT systems can cope with this new technology.
When asked about AI in analytics, 60 percent of respondents stated that the quality of data is not yet enough for AI solutions to analyze it. To ensure the quality of data is especially challenging for organizations in the trade and communications industries.
The quality of the data in this context is largely dependent on the integration capability of the various information silos, a much needed ability in digitalisation projects and the upcoming use of increasingly different data formats.
Conclusion: Ethical questions have to be addressed
The possibilities of AI technology are endless, ranging from practical, for example machines doing monotonous tasks instead of humans or intelligent assistants, to debatable, for example replacing humans in critical fields like healthcare or traffic.
How big a part does AI play in our lives, and on what ethical grounds does it base its decisions? The possibilities are endless, but so is the need for an ethical, legal framework to deal with the questions of what AI is and is not allowed to do, as well as where its independence should stop, and human oversight should start. These questions have to be addressed and answered.
It is not just about ethics and morals, however. Unions and HR managers also have to address the question of which tasks should be handled by machines and which tasks are better suited for human workers. Training courses and headcount planning have to be adjusted accordingly.