Everyone’s talking about artificial intelligence (AI), and how it can execute tasks in a fraction of the time it takes humans — learning as it goes. And while AI technology will likely usurp a number of jobs, it’s also expected to be a jobs creator, as more companies need AI expertise. Does your organisation have the AI talent it needs?
AI analyses data and then automates learning and actions. It is already moving into the mainstream; autonomous vehicles use AI, as do voice-activated devices such as Google Assistant. In the business world, AI’s potential to solve problems is virtually limitless. For example, it can be used to identify potential supply chain irregularities based on weather forecasts, as well as proactively plan and execute contingencies to ensure there’s no delay in moving goods. Or, it can be used to power predictive analytics tools that can make accurate calculations about future cash flows, price fluctuations or customer demand.
At the recent Mobile World Congress 2018 in Barcelona, a panel of executives told attendees they believe AI will create more jobs than it eliminates. A recent study by the Indeed Hiring Lab illustrates AI’s impact. Demand for workers with AI talent has more than doubled over the past 3 years, with the number of AI-related job postings as a share of all job postings up about 119 percent.
It is important to note that the study looked at job postings that included skills such as “artificial intelligence” and “machine learning” in the job description. Many of those are data scientists, engineers, etc., and the jobs will go to IT pros who’ve added AI expertise to their resumes.
So, what kinds of skills do IT pros need to lend their hand to AI initiatives? A firm grasp of data analytics, especially predictive data analytics, will be critical. AI learns as it goes, so first iterations may not be successful. IT pros must be able to examine and understand the underlying data, build algorithms that crunch that data, and then test them to find and fix problems. Iteration is the name of the game. And since AI needs to focus on business outcomes, the IT pros working on AI projects need to have domain and business skills that complement their technical skills.
A solid foundation of programming skills is another key to successful AI. An article on tech career hub Dice provides a fantastic overview of the kinds of tech skills needed for AI and machine learning.
Of course, not all enterprises have the resources to staff AI experts. An excellent way for organisations to get the most current skills as soon as possible is to work with a partner that is deeply familiar with AI, machine learning and analytics and can offer advanced intelligence in its services.
There’s another reason why it makes sense to work with partners on your AI initiatives. For AI projects to succeed, AI has to be embedded within business processes and associated enterprise applications. Deciding on the right infrastructure is also critical — should AI run on-premises or in the cloud? Working with the right partner can help navigate these challenges.
For more on this topic, download the paper, “With AI and analytics, one size does not fit all.”