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HomeSOFTWAREDeep learning with TensorflowGenerative AI is changing your technology career path. What to know

Generative AI is changing your technology career path. What to know

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Getty Images/Yana Iskayeva

At least 80% of all jobs — especially those requiring college education — will be influenced or augmented by generative AI, according to a prediction in a recent paper by a team of researchers from OpenAI, OpenResearch, and the University of Pennsylvania. What does this rise in automation mean for people engaged in or pursuing careers in IT development or operations?

AI — and generative AI, which creates content from training data — will impact technology careers in two ways. As a tool, AI will boost professionals’ productivity and capabilities. At a business level, the growth in automation means increased demand for AI-specific skills to design, build, and maintain such systems.

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Developers and IT professionals “will become more efficient and more effective as they incorporate AI into their toolsets,” says Jesse Reiss, CTO of Hummingbird. “While the technology isn’t yet capable of writing apps on its own, it provides assistance to developers and should accelerate development. It can answer technical questions and quickly outline steps to build a new feature. It can also rapidly output common, simple, boilerplate code that can be tedious to produce alone.”

The increased use of generative AI in technology jobs dovetails with the rise of the low- and no-code movement. “With generative AI, developers can leverage, customize and train algorithms to create new code and solutions, which can save time and effort compared to writing AI and ML code from scratch,” says Diane Gutiw, vice president of analytics, AI, and machine learning for CGI.

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“Generative AI is also certainly making it easier to create low- and no-code environments, which allow non-technical users to build and deploy apps without having to necessarily learn how to write code, although it is still an important skill to have. The risk of this low-code technology is that the developers, designers and users lose transparency into how the models work and how the outputs gather intel/data are generate answers to requests.”

Importantly, the tools of automation should not be seen as a replacement for talented IT professionals. Gutiw says generative AI, for example, will not usurp the functions of skilled developers: “While generative AI can automate certain aspects of app development, responsible AI development still requires developers to oversee and refine the output of these algorithms.”

Therefore, generative AI should not be seen as a magic solution to all development problems: “It is important to have a deep understanding of programming and design principles, and to validate the outputs are accurate and not infringing on any IP.”

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However, AI and its associated tools will have an impact on technology work. Gutiw says the good news for IT professionals is that the growth of AI and automation should mean IT professionals spend more time on higher-value activities and that they will play an increasingly strategic role in organizations.

“They will be responsible for overseeing the automated processes and ensuring that they align with business objectives. They will also be responsible for integrating automated systems with legacy systems and ensuring that the automated systems are scalable, reliable, and secure.”

It should be noted that blending real-world skills with AI technologies will be far from straightforward. Reiss says the key challenge for IT professionals, as with the introduction of any new technology, will be to work out how to apply AI and automation effectively to solve problems.

“For generative AI, IT and domain experts will need to understand the AI interface and help other sides of the business leverage this technology to better support their operations or workflows. IT pros need to deeply understand the challenges of the business, learn how AI can be used, and find ways to bring the two together.”

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The level of change is such that some experts believe the building and sustaining of AI-based systems might require the recalibration of career paths to embrace AI and machine-learning development. “IT pros wishing to work as data scientists or in AI must focus on a domain, specialize in becoming an expert on how data becomes data in that domain, and then apply tools to achieve desired outcomes,” says Raleen Gagnon, vice president and general manager at Magnit.

Along with important technical skills, such as research, data analysis, Python, R, SQL, Statistics, machine learning, and MATLAB, he says they’ll also require softer capabilities, including “creativity, curiosity, and ability to work with both business and technical resources.”

This blend of hard and soft skills is also recognised by Gutiw. She says tech professionals looking to move towards the management of AI systems need to be able to work with large datasets, understand models, and develop algorithms that can process and analyze data effectively. Gutiw says IT professionals also need to have expertise in AI frameworks and programming languages, such as Python, R, and TensorFlow.

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“In addition to technical skills, IT professionals need to have effective communication and collaboration skills to work effectively with cross-functional teams that may include data scientists, designers, and business analysts, who traditionally do not have as much experience with coding or automation technologies,” Gutiw adds.

“This helps ensure that the data and outputs are not being interpreted in a bubble without the insights of the business and data subject matter experts who can provide better interpretation on results. They need to be able to explain technical concepts in non-technical terms and work with stakeholders to identify and prioritize business objectives.”

Reiss predicts the IT profession will divide into two camps as AI proliferates. “One group will focus more and more on AI development,” he says. “They will be the ones that build, train, scale, and maintain AI systems. Being in this group will require knowledge of complex computer science concepts and a deep understanding of the core math used in AI, namely linear algebra. Folks interested in this path should focus on learning how AI systems work and how to read AI white papers to stay abreast of the cutting-edge developments coming out nearly daily.”

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The second camp will see other IT professionals “focus on incorporating AI into product solutions,” Reiss continues: “They will focus on building empathy with their customers, understanding their pain points, and developing solutions that meet these needs. For this group, combining understanding of AI systems with strong communication skills, design insights, and creativity will be the path to success.”

Technology professionals will also be engaged with tasks that cannot be easily automated — such as strategic planning, innovation, and collaboration. “They will need to work with other departments to identify areas where automation can be most effective and to develop strategies for implementing automated systems in a way that maximizes their benefits,” says Gutiw. “IT professionals will need to continually adapt and develop new skills to succeed in this rapidly evolving landscape.”

The upshot of the growing use of AI is that radical change is on the horizon for all IT professionals. Reiss said every developer, product manager, and designer should be thinking about how to incorporate AI technology into their products.

“Regardless of the audience or solution, the latest generations of AI present an unprecedented opportunity to augment existing toolsets. I expect to see applications incorporating AI in interesting and creative ways.”

 

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