Business spending on cognitive systems will jump an estimated 54% in 2018. Companies continue to invest in artificial intelligence (AI). Doing so means they could boost revenues by 38% within five years.
This would also raise employment by 10 percent. By 2030, AI could bump up the global GDP by $15.7 trillion, or a 14% increase. According to PwC, "This makes [AI] the biggest commercial opportunity in today's fast-changing economy."
Despite this projection, AI remains a misunderstood technology. It carries the burden of several myths. Thus, business leaders are wary of exploring the options of this exciting technology.
This article contains insights into artificial intelligence. It also dispels some of the negative AI hype. Finally, it discusses the almost limitless potential of AI in business.
What is Artificial Intelligence?
AI refers to machines that perform tasks that we call "intelligent." In other words, machines simulates human cognitive function. Note that simulating human cognition is not the same as replicating it.
Cognitive computing is another concept altogether, where the application replicates human thinking. Cognitive computing has not come to fruition, nor is it used in any industry.
Alan Turing was the pioneer and AI theorist who advanced AI research in the 1950s. Turing created the Turing Test to examine the question of whether machines can think. For this test, a person poses written questions to a machine and a human. The machine passes the test if the person asking the questions can't tell the human's answers from the computer's.
To this day, very few machines pass Turing's test. Machines cannot interact the way people do. AI assistants can emulate this interaction. However, they rely on complex programming to enable them to function.
The science behind all this is complex. Few business leaders understand it well enough to explore the potential of AI.
Myth: AI Will Take Away Human Jobs
A long-running belief is that AI will replace the need for human workers. In reality, it's no different from any other technology in the workforce. When you call a customer service line, the automated system directs you to the proper area. You no longer talk to an operator for that task.
These technologies add efficiencies. Human workers no longer need to do the simple tasks. And adding AI creates more jobs that need different skills.
Also, the need for human interaction increases as the use of virtual agents increases. The customer service rep is still vital. A chatbot cannot handle a situation that calls for critical thinking with the customer.
Many people feel that incorporating AI means that the jobs left for humans will be menial. As you can see, the opposite is true. The jobs that need the human element are those that need sophisticated skills.
Myth: AI Generates Knowledge
Any AI-powered program depends on algorithms for its intelligence. These programs are dependent on good data to create meaningful information. They don't generate new knowledge.
While "good data" is a fuzzy term, it does mean that the AI algorithm needs to be able to digest the data in to use it. So the data must be clean to exclude any outliers.
It also must be high quality and relevant to the analysis within the algorithm. Otherwise, it has no value.
Myth: Artificial Intelligence And Machine Learning (ML) Are Interchangeable
Artificial intelligence machines show humanlike intelligence while carrying out complicated tasks. One example includes identifying objects within images. Others include responding to natural language and solving complex problems with variables.
Machine learning is more or less a subset of artificial intelligence. Over time, the algorithm improves because it uses more training data. It "learns" by spotting and evaluating patterns in the data.
Thus, ML is one of several approaches to creating AI in algorithms and in the applications that use them.
Benefits Of AI In Business
AI is delivering benefits to companies like Amazon, Baidu and Google. All these companies invested in the technology. In 2016, U.S.-based companies held 66% of all investments into AI companies. China came in second at 17%, though that number will increase. Both countries have financiers and entrepreneurs who have issued national strategic plans.
Those plans place significant emphasis on AI. The United Kingdom and South Korea have similar strategic plans. Other countries will join soon enough.
For example, digital retailers use AI-powered robots to run the warehouses. The robots can even order stock as inventory runs low. Utility companies use AI to predict electricity demand. Automakers are embedding the technology into self-driving cars.
Support for technological developments is driving this explosion of AI technology. As computer power grows, AI models and algorithms are getting more sophisticated.
The world is generating enormous fuel for AI, which is data. Network devices like web browsers and turbine sensors collect billions of gigabytes daily.
Using AI For Core Functions
AI in business and industry delivers real value to companies that are willing to invest in it and put it to use to gain competitive advantages. Further, these companies can use AI across all operations -- including their core functions -- to increase efficiency and reduce costs.
Telecommunications and financial services companies are leading the charge with ambitious AI investment plans. They are using AI technologies across functions. Or, they are using AI at the core of their business processes.
For instance, automakers use AI to improve operations. They also use it to develop their self-driving vehicles. Financial services companies use AI in the customer service systems.
Catching Up To AI In Business And Industry
Despite the benefits and innovations, not all companies invest in AI as much as they could. The benefits of AI in business are evident despite the myths that surround the technology.
Some companies realize the need to catch up to their competitors in this area. Those who invested early on are in a better position. They can better align their digital assets with AI to deploy AI applications in business.
source: Forbes
Коментарі