What Does Quantum Computing Mean for IT?
Although quantum computing is relatively new and far from mainstream adoption, the hype for this emerging technology is building. If companies hope to capitalize on it, though, they must move past this excitement and look at its specific, practical implications.
Effective implementation of any technology requires understanding what it can do for businesses and the obstacles they may face in using it. The journey begins with asking what quantum computing means for IT professionals as a whole as well as individual teams.
What is quantum computing?
Quantum computing operates on the quantum principles of superposition and entanglement. Whereas classical computers calculate with transistors representing either 1 or 0, quantum machines use qubits, which can represent both simultaneously. This lets them perform calculations in minutes that would take classical computers millennia to complete.
The superposition of qubits—being both 0 and 1 at once—lets quantum machines weigh far more possibilities simultaneously. They also become exponentially more powerful with more qubits, whereas classical computing power has a one-to-one relationship with transistor numbers.
While quantum computers are faster and more powerful, they have some unique downsides, too. Notably, they yield higher error rates thanks to their complexity. They also demand operating temperatures near absolute zerowhich requires extensive cooling infrastructure.
What does quantum computing mean for IT professionals?
Seeing through the quantum computing hype means understanding how IT professionals must adapt to these machines’ unique needs. Here are a few of the most significant implications, both positive and negative, of quantum computing for IT.
1. New machine learning possibilities
Since quantum computers can solve complex problems far faster than classical devices, they’re ideal for machine learning. If IT professionals apply quantum computing to machine learning, they could bring the technology to new heights, simulate more complex challenges, and find solutions faster.
Even relatively simple quantum chips can learn 63 percent faster than a classical computer. This could lead to exponential increases in machine learning power.
Consequently, IT departments can use this technology in areas where today’s machine learning struggles, such as understanding contextual meaning or generalizing knowledge. Optimization and analysis tasks could become far faster and, as a result, more cost-effective.
Related: What is Quantum Machine Learning? Beginner’s Guide to QML
2. Automation opportunities
Similarly, quantum computing could let us automate more processes than before. Since these machines are so much better at machine learning and complex thinking, they can bring automation to areas where it was previously unfeasible.
This could reduce IT workloads, but it’ll also likely impact the role employees play in IT. With quantum computing, IT work will involve far less repetitive, analytical, and administrative tasks and focus more on nuanced responsibilities and human connections within the business.
Considering that 73 percent of IT leaders currently struggle to fill tech positions, quantum-enabled automation could have considerable workforce implications. IT departments may finally move past these obstacles, but it’ll mean reorganizing how their workforces operate.
3. Implementation considerations
Businesses should also consider various implementation methods for quantum computing. Capitalizing on this technology doesn’t necessarily mean IT teams need to build their own quantum computers. Quantum computing as a service (QCaaS) has emerged in the past few years to give businesses a more accessible option.
Building and managing a custom quantum machine comes with significant cost, expertise, and technical requirements, but it may produce better results. Alternatively, QCaaS may be more cost-effective, but it may offer more limited use cases and slower results. IT departments must review their resources and goals to determine which path will offer the most benefits.
4. Higher data demands
One factor that the quantum computing hype often glosses over is these machines’ higher data demands. Quantum machines have considerable potential for improving other technologies, like bringing the metaverse to healthcare, but these applications will require massive amounts of data. Even on their own, quantum computers need massive data sets to reach their full analytic potential.
Consequently, implementing quantum computing will require larger, cleaner, more consolidated databases. Some IT departments may have to invest more in data collection and management to ensure they can support these technologies and their ideal use cases. Managing and cleaning data will also become a more important part of IT work.
5. Different required skills
Since quantum systems work differently than classical computers, they require different skills to manage. This, along with an increasing abundance of automation that comes with the technology, means IT teams will likely have to reskill workers and attract different talents.
today, 76 percent of the global workforce doesn’t feel confident in their digital skills, resulting in a massive skills gap. As quantum computing grows, the digital skills companies need will shift. This could potentially create another, wider gap.
Businesses must anticipate these shifting demands to make sure they have the workforce needed to apply quantum computing effectively.
Related: Hiring Crunch Hits IT
See beyond the quantum computing hype
Quantum computing has substantial potential, but its distinction from classical computing will change how IT departments operate. Businesses will be required to adapt and understand the unique implementation considerations to make the most of quantum computing.
Seeing past the hype and addressing quantum computing’s obstacles is crucial for a solid return on investment. Businesses that can understand this technology and prepare to implement it effectively, will be able to enjoy its full benefits with minimal disruption.
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