The use of artificial intelligence in industries has increased at a rapid speed and will increase the speed of adopting AI in the industries with every passing day. While most companies are already deep into the use of AI some are only starting with the use of AI for their companies, but the questions that rises with this technology is how is one supposed to run a technology that they might not understand. According to IDC, global spending on AI and cognitive technologies will reach $19.1 billion in 2018, up 54.2 percent compared to a year ago. By 2021, AI and cognitive spending will hit $52.2 billion. If you're not spending on AI, you may need some computer-assisted help to set your budget. AI is still a relatively new technology and new word for most of the population; most are still falling into thinking AI with more algorithms is better and that thoughts can be outsourced to these models.
What are the some AI things that could make it hard to manage it?
Some companies have a data science team that can put a following AI according to their use; most of the companies donâ??t even have that luxury. There is already a lack of data scientist that can kick the tires on models and algorithms. In response to this demand, cloud providers such as AWS, Microsoft, and Google are starting to package AI services to address horizontal functions such as recommendations, contact centre and HR recruiting. Those moves will make AI easier to consume. The leaders of the companies need a strategy to have these AI and machine learning for their business. The business schools university have already started adding the data science programs for the students, but this will take time for these students to be good at c level executives. Technology buyers are trained to buy black boxes that will fix the problem and find the solutions to them. Models that are being sold have little transparency. IBM Researchers recently proposed an effort to add the equivalent of a UL rating to AI services.
There are a lot of issues due to issues in management, slouch algorithms and the hype created by the vendors.
Gartner's Emerging Technology Hype Cycle has AI all over it. Gartner is betting that AI technologies such as AI platform as a service (PaaS), Artificial General Intelligence, autonomous driving, conversational AI platform, deep neural nets, and virtual assistants will be common in the next two to five years. According to Gartner, AI technology will be "virtually everywhere over the next 10 years." As far as marketing goes, AI is already everywhere. The trick will be figuring out how everyone from mid-level managers to C-level execs are going to use this AI and manage what they aren't likely to fully understand. The real fun is just starting.