DISRUPTORS MOVE FAST, BUT LACK EXPERIENCE AND POWER
Artificial intelligence change business models. Most Boards have set digital road maps. But do Boards use enough time on where the company should be in 3-5 years, and who might be their biggest competitors?
The potential for increased margins is substantial as a consequence of automation, digitalization and robotics. But the most important factor for change is not digitizing the existing business – but customer demands accelerated by the fast growing a) all things get’s connected to internet, and b) the development of artificial intelligence.
In 5 years it is expected that artificial intelligence will lay on top of every business process. At that time it will become clear that “the lucky early movers” were not just lucky, they were more strategic. Artificial intelligence enables new and better business and enables change in the way we work with customers, employees and vendors.
Two futuristic examples within “smart cities”:
Example 1 – Building and health sector
Hospital buildings will be delivered with roof top solar panels and a flexible and dynamic connection to – and exchange between – the best suitable energy source measured in real time (water, sun, wind, wave, nuclear, nano, oil, gas). Innovative battery storage secure environmentally friendly load balancing of excess energy at the right time during the day and night. The building is delivered with data infrastructure that meets the usage planned for the building. This includes data storage locally, centrally and in the cloud, wireless communication and intelligent sensors. The specifications (API’s etc.) for the building enables vendors of patient solutions and equipment to easily deliver public tenders on the contrary as of today.
The data gets aggregated according to the GDPR regulation and the system get’s authorized to deliver data on standards that makes it easy for 3rd party vendors to deliver solutions for artificial intelligence. The goal for the learning algorithms of artificial intelligence could be: more accurate patient treatment, preventive treatment of risk groups, predictability of hospital competence and capacity, asset/equipment management and energy efficiency – as some examples.
Example 2 – Transportation industry in smart city’s including value added services
The car/transportation industry has become software, sensors and internet of things, the-intelligent-vehicle. Let’s imagine a scenario were the transportation sector apply for, or source, 5G mobile licenses to handle the smart city’s requirements to need based transportation. The algorithms will collect from sensors and other sources making predictive, consumption and experience based analysis as detailed sales volumes and cargo needs in shops, weather and road conditions. The only transportation allowed in urban areas is demand based public transportation, cargo and waste handling. In 1-2 year time the data collected and the adaption to intelligent sensors, solutions for authentication, biometric sensors and 2-ways communication is sufficient to deliver insurance and security solutions.
The transport industry moves towards electrification,
with considerable requirements to grid capacity, energy balancing and battery
storage, disruptive-vehicle-will-drive-innovation-in-electricity-grids. Requirements to data processing, storage, security
and artificial intelligence is considerable.
For some this might seem a bit distant, but many of the solutions are already in place. For the transportation industry, car industry, building, bank, retail, insurance and telecom/IT they will have no choice than to take active decision towards their strategy for the future.
The decisions will require the right competence on Board that understands the future business models, the ownership of information and artificial intelligence.