Tech Trends Right Out of Science Fiction

Long before the novel coronavirus caused a tech hiring slowdown, jobs calling for machine learning or AI skills were a hot trend. The pandemic has done nothing to change that.

If anything, COVID-19 is likely to increase the demand for AI professionals, says IDC analyst Ritu Jyoti.

“Because of the pandemic, IDC believes that AI spending and employment will increase among healthcare providers, education, insurance, pharmaceutical companies and federal governments,” she said, estimating the increase could be as high as 16%.

CIO.com did a survey to see what the emerging AI jobs are likely to be. Among the nine the magazine turned up were some familiar titles – data scientist, for example — and at least one that isn’t a job title but a description of skills. Familiar or emerging, all of the jobs have this in common: They not only require AI skills, but also a good grasp of business essentials.

Chief data scientist, a job that already exists at many companies in and out of the tech sector, is one of those familiar titles that is evolving from statistician to more of a business technologist. Increasingly, the job will require a basic understanding of the underlying technology as well as an appreciation of business needs.

“Data scientists know what data to use and what algorithms to deploy to get the best results, working with data engineers and software developers to turn this know-how into working applications — and with business units to ensure the technology meets business needs,” says CIO.com.

Data alone may yield interesting intelligence, but to wrest actionable value companies have long employed analysts. Emerging now is a category of analyst who works directly with data scientists and engineers and with the business side. These analysts not only must have an intimate knowledge of the operation, CIO.com says they also must be able to speak the AI technical language.

If this job sounds similar to the emerging chief data scientist role, it is — to a degree. These analysts will serve more as translators. They may not need to be fluent in data science, but they will need a higher level of technical expertise and a high degree of business acumen.

Finding and hiring professionals with these skills will not be easy. Anand Rao, partner and global AI leader at PricewaterhouseCoopers, told CIO.com that because schools are training for entry-level technical jobs, “The business and executive jobs need to be grown and cultivated within the firm and will pose a significant challenge to fill.”

One job with a familiar title that will be radically different on an AI team is quality assurance manager. Unlike traditional QA roles, an AI quality assurance specialist will be less concerned with the quality of the code than the quality of the data.

In an AI setting, quality assurance will be concerned with “incomplete, out of date, or biased training data sets,” says CIO.com. Though companies have yet to advertise AI quality assurance jobs, that’s coming. “Biased data is a particularly thorny problem that can lead not only to bad results, but also regulatory implications, bad publicity, fines, or lawsuits.”

Finally, notes the CIO article, are the emerging “citizen data scientists.” More a job description than a job title, these professionals will be skilled in using off-the-shelf tools to perform AI-related data tasks. As these AI analytics tools become increasingly easier to use, workers reskilled for AI and machine learning will take over from the highly trained – and expensive – data scientists who now do the job.

Photo by Michael Dziedzic on Unsplash

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Before the coronavirus crisis, digital priorities were so much at the top of organizational priorities that “digital transformation” had achieved the status of business buzzword.

IT departments were busy with initiatives to, as Salesforce once explained, “create new — or modify existing — business processes, culture, and customer experiences to meet changing business and market requirements.”

Despite the high visibility businesses gave to digital transformation, the process was slow. CIO.com says, “Most organizations aren’t the digital entities they seek to be.”

“Experts say organizations and their teams need to think of transformation not as a program or project with a start or end date, but rather a new way of operating,” says CIO.com in an article the website for tech leaders entitled “Does digital transformation ever end?”

Jeff Thomas, CTO and acting co-CIO of Sentara Healthcare, offers an answer, “I don’t think the journey ends.”

His view is reflected in the findings of multiple surveys all echoing similar results: Corporate leaders declare themselves fully invested in digital transformation, but struggle to achieve the success they are looking for.

PwC provided an explanation of why. In 2020 Global Digital IQ, PwC said that of the 2,380 executives it surveyed around the world it “discovered a group of companies that consistently generate payback and get significant value on their digital investments in every area we assess — from growth and profits to innovation, customer experience, people and more.”

Those companies – 5% of the companies surveyed – succeed because, PwC says, “Transformation never ends… Their cultural DNA empowers them to navigate change and be prepared for anything.”

“Digital is their corporate strategy, not a line item or ‘special effort’.”

Commenting on the report, PwC Global Chief Experience Officer David Clarke tells CIO.com writer Mary K. Pratt, “We look at companies doing well and find that they’re committed to constant change… Digital transformation is more of a DNA thing, it’s more of how you operate, it’s the idea that you’ll never be finished, because you never know what the next great idea or technology will be.”

While the entire C-suite needs to be committed to digital transformation, “the CIO is the person best suited to take that on,” maintains Arthur M. Langer, academic director of the Executive MS in Tech Management program at Columbia University.

“Successful CIOs are not only focused on the technology but also on the strategy and how to work with the business units to assimilate new ways in which people will work, how they use technologies, how to predict obsolescence of products and how to advise boards.”

As companies slowly reopen their doors and initiatives put on hold during the pandemic are revisited, successful digital transformation will come not from successive major projects, but from small steps.

“Change fatigue is very real,” Trent Mayberry, chief digital officer at UST Global tells CIO.com. “The idea that I’m going to do Program A and then B and then C and I’m never going to stop that change, then that’s exhausting.”

Instead, “Build an organization that can change incrementally every day, where every day you’re getting better. That’s how business should work, where transformation is constant minor degrees of change.”

Photo by NeONBRAND on Unsplash

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