Digital transformation initiatives are rapidly changing businesses, and it only makes sense that job descriptions for IT teams are also shifting. With new skill requirements, the day-to-day activities of enterprise technology professionals must evolve too as technologies like artificial intelligence (AI) and machine learning becoming prevalent in the workplace.
AI is no longer a distant possibility; organizations are adopting it in earnest as use cases and applications materialize quickly. According to a 2017 survey by Forrester Research, 70% of enterprises expect to implement AI in 2018. An additional 20% said they would deploy AI to help them make decisions. Research by IDC predicts that global spending on cognitive and AI systems will grow nearly 55% this year to $19.1 billion and that 75% of enterprise applications will use AI by 2021.
Organizations need to have a clear vision of how AI can benefit their businesses and what that means in terms of people, processes and tools. All of that takes time to implement, and the path forward isn't always clear. With this in mind, it's important that organizations develop detailed implementation plans and invest in supporting infrastructure to develop AI applications and provide the speed and performance needed.
When it comes to enterprise networks, network managers are able to complete more value added tasks such as data mining, algorithm development and cybersecurity management with the help of AI-powered solutions. This slideshow will provide an overview of the top four qualifications needed to be a successful network manager as new technologies emerge and IT jobs evolve.
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Data mining
30 billion connected IoT devices are expected to be in use by 2020, according to Statista. All of these connected devices and sensors will be producing data that needs to be collected, analyzed and interpreted. This will be done in part with AI-enabled platforms and predictive analytics, but data mining will be a skill high in demand for businesses to gain insight beyond statistical analysis.
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Algorithm development
All businesses with connected devices are looking to gather more data, and they need expertise not just in extracting the data, but also in building algorithms to derive insights and analytics out of that data. With more machine learning-powered tools coming to market, network managers with skills in algorithm development will see themselves at an advantage to feed machine learning and AI tools.
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Security engineering
Every device connected to a network creates risk, and when personal, business and IoT devices are all connected at once, it adds a level of complexity to data privacy and security. Security skills, and specifically network edge and endpoint security are critical to manage today’s enterprise networks. To help mitigate against increasing security risks, companies are investing in security engineering and seeking skills in vulnerability assessment to identify threats to networks and determine the risk at the device level.
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Adaptability
The IT landscape is evolving rapidly, and there may be skills needed 10 years down the line that we aren’t even aware of yet. That’s why arguably one of the most important skills of a successful network manager is the willingness to learn and keep evolving. This is absolutely essential to staying relevant in a constantly evolving business.
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