Artificial intelligence, quantum computing, and the automation of everything is finally coming of age. Like it or not, these new technologies will inevitably infiltrate your enterprise. Does your IT department have the six critical skills needed to support these technologies?
What’s Driving Tomorrow’s Skillset
Tomorrow’s enterprise is indeed a strange place; a place very different from what we deem the norm of today. I envision the future IT department not as a functional silo, but as a center of common, next-generation shared services. Yet before I dig into the details of the services, we need to understand the technological impetus driving us to this destination.
Automation has been around for some time, but what is awe-inspiring is the scale of today’s automation. We build virtual data centers, navigate driverless cars, and watch military robots intercept missile strikes all without one ounce of human intervention.
Of course the things we automate need to be networked together. New standards are erupting within the Internet of Things (IoT) space like jurassic-era volcanos; each standard spewing its own fountain of data that must be managed and secured. Additionally, these real-world “things” can be augmented with virtual appendages; digital accessories we’ve come to know as virtual reality.
Finally, our financial institutions– perhaps like the dinosaurs of yesterday– may be living out their final days as the meteor of blockchain ominously looms uncomfortably close; plotting its inevitable impact crater on Wall St.
The good news, however, is that many of tomorrow’s technologies rely on a core set of reusable skills. No need to hire ultra-specialists or create unicorn-like job descriptions. The core set of supporting skills are shown graphically in the figure below:
The bad news is that the IT department cannot afford to sit on the sidelines and “wait for the technology to mature” before it can be officially supported within the enterprise. These new technologies will invariably follow the same trajectory as cloud computing and consumerization of end-user devices in that they can either be embraced early on, or they can be resisted and forced unto the reluctant IT department later. History has taught us that the late adopters do not fare well this game. Just ask any business unit who yearns to leverage these new technologies for competitive advantage.
New Functions and Roles for IT
I possess no crystal ball, nor can I see the future teams of IT with crystal-clear clarity. However, I can predict nascent formations of IT groups to support these new technological areas. I don’t believe it’s far-fetched to see IT divisions such as:
- Cloud Operations – Engineering teams develop software, and run that software on infrastructure. R&D does the same, and so do other teams. Wouldn’t it be nice if IT assumed the role of providing a set of shared services that balanced centralized cloud management and engineering autonomy? While engineering focuses on their core development, IT can handle things like billing, monitoring, optimization, and security. The same paradigm holds true for SaaS computing on the business side. Every business unit has a significant SaaS footprint, and each SaaS solution has monitoring, security, and general management needs. Plenty of opportunity for IT to shine.
- Enterprise Data Services – One-stop shopping for operational and analytical data needs across the organization. This group would holistically support traditional business intelligence needs as well as data services for predictive analytics and machine learning operations.
- AlgOps – Picture a scruffy-haired data scientist who’s been up all night hacking on a data model and finally hits predictive paid dirt. She proudly opens her laptop, and amongst a dizzying array of terminal screens, shows off a new data model that’s actually pretty awesome. Cool, except for when you’re the one who must figure out how that rats nest of code and libraries need to be operationalized across an otherwise stable production platform. This particular developer likes containers; another likes full-fledged virtual machines, and still another prefers software packages. IT should be driving those frameworks, and managing the care-and-feeding of these algorithms in day-to-day operations so that the data scientists can move on to the next challenge.
- Specialized Projects Computing – We’ve been riding the Intel/AMD x86 CPU architecture since 1981. Sure, the CPUs have gotten increasingly faster, and cores counts have steadily increased over time. Yet today’s computing challenges in the machine learning and blockchain spaces require something entirely new. I’m talking about grids of graphics processing units (GPUs) and potentially quantum computers. Unless you’ve got a staff that currently knows how to keep a quantum computer humming along at a cool -273 degrees Celsius, you may need to source some new people.
Along with these new functions also comes new roles. There may also be some interesting new job titles in the near future, including:
- Automation Auditor – If humans delegate tasks to machines, shouldn’t someone be watching the machines? Even if machines are trusted to perform tasks really, really well, there’s still potential for error and malicious human obstruction; especially in areas such as financial transactions. Moreover, government regulations in the financial and healthcare spaces aren’t going away anytime soon, so automation will certainly require human monitoring into the foreseeable future.
- Director of AI Ethics – Fifteen years ago, if someone told us there would be “social media managers” in the workforce, we probably would have scratched our heads and wondered what that even meant. Today such positions are the norm, and so too will be AI ethics positions. These will be the folks who decide if algorithms are discriminating against humans, and if machines themselves are being treated fairly. I know it sounds funny today, but just wait and see!
- Sr Manager of Specialized Computing – Many infrastructure experts of today rarely touch a piece of hardware directly. Infrastructure as a service is delivered via the cloud (private, public, or hybrid) and is controlled and automated through APIs and web interfaces. While IaaS companies like Amazon, Google, and Microsoft may get more skin in the specialized computing game by providing quantum computers and making GPUs more affordable, I believe the “cutting edge” enterprises and especially IoT firms will absolutely need hardware gurus with backgrounds in electrical engineering in order to remain competitive.
So, why these roles and not others? The prediction is that these functions will be relatively common in tomorrow’s enterprise, and will thus have the potential for duplication/redundancy throughout the various enterprise departments. If an information asset is ubiquitous and can be provided through a centralized entity which leverages key skills and economies of scale, such a capability should at least be analyzed.
Expediting IT/Business Convergence
Technological change occurs relatively quickly, yet there’s always time to evolve existing skillsets toward a trajectory of alignment with the next generation of IT. It’s true that at least some outside expertise is warranted, but providing training and “R&D time” for existing IT staffers will help in their transition. Likewise, keeping existing IT staff will ensure business continuity as this new technology is adopted.