Upskilling in AI: The technical, business and managerial aspects of the job
Artificial intelligence (AI) is set to send ripples of change in the world of work, and its importance is only projected to grow in the coming years, which makes upskilling in AI a good consideration for professionals in any stage of their careers.
According to LinkedIn’s 2020 Emerging Jobs Report, Artificial Intelligence Specialists are the top emerging jobs in the US with a 74% growth. It said AI and machine learning have both become synonymous with innovation, adding that their data shows “that’s more than just buzz”.
“Hiring growth for this role has grown 74% annually in the past four years and encompasses a few different titles within the space that all have a very specific set of skills despite being spread across industries, including AI and machine learning engineer,” it said.
Meanwhile, PwC notes in their report, 2020 AI Predictions: Rethink upskilling, that “companies can see remarkable savings from (for example) using AI to extract information from tax forms, bills of lading, invoices and other documents that typically require long and tedious hours of human work”.
Apart from automating tasks, AI has a lot to offer in terms of improving how people work and augmenting complex processes, including in managing risk, fraud, and cybersecurity, supporting decision-making and gathering forward-looking intelligence, said the report.
Careers in AI are spiking
Job site Indeed said jobs in AI have spiked, with a steady hike over the last five years. The report notes that AI job postings have gone up consistently over the past two years, with a 46% hike between 2018-2019, and a 51% spike between 2019-2020.
This hasn’t gone unnoticed by job seekers. AI-related job searches have increased by 20% between March 2020 and July 2020 alone, while job searches in AI have seen a significant spike of 106% between June 2019 to July 2020.
There are plenty of AI-related career opportunities, be it in the technical, business analysis, or managerial aspects of the job.
Some of the technical skills in AI include learning how to manage and configure AI application programming interfaces (APIs) and deep neural networks (DNNs), advanced analytics, as well as data science skills.
Meanwhile, some of the business analysis skills to consider include process reengineering, business case development, the experience of DevOps and agile delivery, as well as vendor selection and management.
Some AI roles require managerial skills which include data literacy, governance, ethics, AI architect skills, as well as experience managing IP rights between customers and vendors.
There are many upskilling options for professionals in the field. edX, for instance, offers AI for Leaders, which teaches learners how platform business models and AI technologies complement each other, where to look for data and what data is valuable to your business and AI, how to get started, and the five steps for success (PIVOT), to name a few.
For technical aspects of AI, Coursera offers Neural Networks and Deep Learning, which will expose you to the foundations of deep learning. Upon completion, you can expect to understand major technology trends driving deep learning, be able to build, train, and apply fully connected deep neural networks, know how to implement efficient (vectorised) neural networks, and understand the key parameters in a neural network’s architecture.
If you’re looking to gain some business skills, some consultancies and universities offer related courses in the field.
Project management consultancy pm-partners, for example, offers Vendor & Supplier Management Course, which is designed to equip participants with the skills and techniques required to establish more successful commercial relationships with vendors who provide the products and services required to successfully deliver an organisation’s programmes and projects.
Regardless of which area you choose to upskill in, AI will prove to be a promising field with ample career opportunities.