The field of artificial intelligence (AI) has proven to be a disruptive force in the age of information and digital transformation. Along with its sub-categories machine learning and deep learning, AI has taken multiple industries and internal business processes by storm. A recent Harvard Business Review (HBR) survey reported that 30 percent of respondents predict that AI will be the biggest disruptor to their industry in the next five years. AI is influencing many of the foundations that empower digital transformation, and that makes AI and machine learning expertise invaluable for technology teams that hope to stay at the forefront of industry change. 

Here are some of the key trends that are impacting AI upskilling in the enterprise:

Investments in AI Reach New Thresholds

It was only a few years ago that companies were just dipping their toes in the AI sector. Now corporate investment in AI technologies is predicted to become a $100 billion market by 2025 according to the HBR survey. But even this anticipated growth is only the beginning. Deloitte’s Technology, Media and Telecommunications Predictions 2018 report shows developments in machine learning growing at a phenomenal pace this year, but noted that the pace of advancement will be so rapid that in 50 years, today's developments would be considered "baby steps." As companies up their investments in AI technology, the companies that produce it and utilize it in their organizations will experience a vital skills gap unless they can upskill their teams to squeeze every ounce out of AI’s amazing power. 

AI Will Be a Boon for Customer-facing Activities

Nothing matters more to today’s customer-service driven companies than being able to efficiently target, sell to, and service their customer bases and keep them engaged with their brand. 87 percent of current AI adopters said they were using or considering using AI for sales forecasting and for improving e-mail marketing. AI turbocharges data science in the marketing field to determine which email messages should be tailored for which audiences, and the sales organization can generate more accurate sales forecasts by using AI to evaluate changing numbers on customer and regional trends, delivery capabilities and anticipated product or service renewals. And when it comes to customer relations, 44 percent of consumers now prefer online chatbots to humans, providing ample opportunity to companies to employ AI to improve customer loyalty, satisfaction and retention in a way that is faster and far more efficient. 

Smarter Back-office and Operations

Companies are taking a truly deep look at AI to add intelligence to everything from production operations to IT, finance and even human resources. Just over half of AI leaders in another HBR study predicted that by 2020, AI will have its biggest internal impact on their back-office functions of IT and finance/accounting. Even in less technical domains, AI is doing its part: Glassdoor reports that the HR business is using AI to craft job descriptions that are free of biased language, manage repetitive tasks such as scheduling candidate interviews and match candidates with open positions. A new generation of robotic processing automation (RPA) is also putting advanced AI to work, using software-driven robots to capture and interpret existing applications for processing transactions, manipulating data, triggering responses and communicating with other digital systems. The global market for RPA software and services is expected to grow to $1.2 billion by 2021 at a compound annual growth rate of 36 percent. RPA bots can automate easy tasks and make broad data sources accessible to AI, which in turn learns to mimic and improve the processes based on data received from the RPA. 

AI Jobs Will Be Plentiful

From AI to machine learning to deep learning, there will be consistent growth in jobs that leverage these vital technologies in their day-to-day operations. Forbes reported that jobs requiring AI skills have been increasing 4.5x in the last five years. The impact will be felt heaviest in the data science field: 80 percent of data scientists will have deep learning in their toolkits this year, according to Gartner. There is already a growing demand for (and online upskilling programs designed for) AI engineers who can create practical applications using a wide range of intelligent agents, including knowledge-base systems and agent decision-making functions; machine learning experts who can manage mathematical and heuristic techniques and hands-on modeling to develop machine learning algorithms; and deep learning experts who can master TensorFlow, the open-source software library designed to conduct machine learning and deep neural network research. 

As Google’s CEO Sundar Pichai put it earlier this year, “AI is probably the most important thing humanity has ever worked on. I think of it as something more profound than electricity or fire." Those are words that every AI technologist and data scientist should remember as they consider the next steps in their career development.

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