December means holiday parties, New Year’s resolutions, and a blizzard of technology industry predictions. You’ll see a ton of AI-related calls as we approach 2019. The artificial intelligence hype machine is already roaring.
We decided to focus on the trends that matter most urgently to IT leaders – you don’t need another “AI is taking over the world” story; you need concrete insights for your team and business.
[ How can IT teams prepare for AI? Read Artificial intelligence: The king of disruptors. ]
So let’s dig into the key trends in AI – as well as overlapping fields such as machine learning – that IT leaders should keep tabs on in 2019.
1. AI powers the next phases of digital transformation
“Unlike most of the predictions and discussions about how autonomous vehicles and robots will eventually affect the job market – this is true but will take time due to institutional, political, and social reasons – I contend that the biggest trend in AI will be an acceleration in the digital transformation, making existing business systems smarter,” says Dr. Tung Bui, professor and chair of the department of information technology at the Shidler College of Business, University of Hawaii.
Bui even has a word for this trend: “smartization,” and predicts that it will be powered increasingly by AI. Bui, who also chairs the Hawaii International Conference in System Sciences, points to everything from airline and hotel booking systems to web applications, healthcare systems, and more as examples of areas where digital transformation initiatives to this point have effectively been a dry run for the AI-fueled transformations to come in 2019 and beyond.
“I predict we’ll witness a silent revolution similar to an undersea tidal wave,” Bui says. “The impact will be a shift of competitiveness among those who effectively adopt AI into their business systems.”
At least one survey suggests some organizations are in need of a wakeup call here. RELX Group similarly predicts that AI and machine learning adoption will be crucial for both public and private organizations to remain competitive as the age of digital transformation evolves. Yet in a recent poll, the firm found that only 18 percent of executives have tangible plans to increase their investments in AI and machine learning technologies.
2. Meet the new talent gap: AI skills
There’s another teensy little problem: AI skills (as well as related areas such as machine learning) are in short supply today.
"Most organizations want to embrace AI as part of their digital transformation but do not have the developers, AI experts, and linguists to develop their own or to even train the engines of pre-built solutions to deliver on the promise,” says Pat Calhoun, founder and CEO at Espressive.
Vendors like Calhoun’s firm, which makes a virtual support agent (sometimes called a chatbot) for IT service desks, are betting on developing AI-powered tools that don’t require copious amounts of technical expertise to deploy and manage.
But the full potential scope of AI in the enterprise – Bui’s undersea tidal wave – will most definitely require human talent to achieve, including in the early phases of implementation.
“With so many ‘AI-powered’ solutions available to address a myriad of business concerns, it’s time enterprises get smarter about what’s happening within the ‘black box’ of their AI solutions,” says Rahul Kashyap, CEO of Awake Security. “The way in which AI algorithms are trained, structured, or informed can lead to significant differences in output. The right equation for one company won’t be the right equation for another.”
3. Invest in developing AI skills internally
Jeff Reihl, EVP and CTO at LexisNexis Legal and Professional, says that forward-thinking IT leaders aren’t going to wait around for the AI talent pipeline to fill up; in 2019, they’re going to invest in developing the necessary skills in their existing teams.
Much like the data scientist hiring wars, the AI hiring landscape is a story of scarcity – which means those who are on the market can command outsized compensation packages. Good for them, but not always realistic for you. But if you wait around for the labor market to adjust, you might be DOA.
“Companies will get serious about training for advanced technologies – like AI, ML, etc.,” Reihl says. “Smart companies will look to in-house experts and partner with universities to teach the tech they value. Companies that train in advanced technologies will have the edge in talent retention and recruitment.”
4. AI will change, not replace, existing teams
One of the prevailing AI boogeymen is the notion that it will put us all out of jobs – bow down to your robot overlords and all that. That’s not entirely baseless; as Bui notes above, AI and related technologies will almost certainly have significant impacts on a wide range of jobs in the future. But right now, AI is more likely to change or augment existing roles and teams than to replace them wholesale.
“The biggest trend to watch in 2019 is the adoption of AI solutions that enable your existing team,” says Noah Horton, CEO of Unsupervised.com. Horton points to data engineering and management as an example; it’s an increasingly unwieldy choice for a team with finite resources, and AI can help (we’ll get back to that in a minute).
Indeed, savvy IT leaders aren’t really looking to AI to replace people; they’re looking to AI help solve their critical goals and challenges, especially when they don’t have enough people in the first place.
“AI isn’t a silver bullet for closing the skills gap, but it is an important part of the solution to some of our most complex and resource-intensive challenges,” says Kashyap of Awake Security. “I expect to see organizations that embrace this balance between human and machine – either internally or as part of their customer-facing products – achieve the most success with AI in the year ahead.”
The RELX Group survey mentioned above supports this vision of AI as an enabler rather than a job-eliminating monster in IT departments or elsewhere in the company.
According to the poll’s findings, the three most popular uses for AI and machine learning are to increase efficiencies or worker productivity (51 percent), to inform future business decisions (41 percent), and to streamline processes (39 percent).
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