How tech professionals can survive and thrive at work in the time of AI

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    Despite all the new headlines about technology layoffs, opportunities abound for technology professionals. It's important to adapt to the convergence of new technology and constant business requirements. Overall employment of software developers, quality assurance analysts, and testers is projected to grow by 25% from 2022 to 2032, he said, “much faster than the average for all occupations.” I am. analysis From the U.S. Bureau of Labor Statistics, September 2023.

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    According to a statement from the BLS, “Increased demand for software developers, software quality assurance analysts, and testers is driven by the continued expansion of software development for artificial intelligence, Internet of Things, robotics, and other automation applications.” It is said that

    But the possibility amount The rise in technology opportunities is only one side of the story. What is really persuasive is quality In the near future, we will see jobs related to technology. Technologies such as AI and low-code and no-code platforms can eliminate manual labor in favor of more advanced tasks. Even those currently working in AI will be in a position to expand their skill base.

    Changes in skill requirements are supported by the following research: Economic Graph Institute on LinkedIn. “We are in an era of rapid and continuous change in the skills needed to perform jobs,” he says. Dan Brodnitz, Global Head of Content Strategy at LinkedIn Learning. Insights from LinkedIn's data show that “More than half of LinkedIn members work in jobs that could be disrupted or enhanced by AI, and the skills our jobs will need by 2030. suggests a change of up to 65%.

    With the introduction of artificial intelligence and machine learning in daily work, “some technology-related skills are facing a paradigm shift,” he says. Hershul Asnani, President, Enterprise Technology, Tech Mahindra. These include “repetitive, rules-based tasks that have traditionally been handled by humans, such as basic data entry, routine coding of standard applications, and even some rudimentary data analysis. Aspects of the department are also automated by AI algorithms.”

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    Additionally, over time, “skills such as code abstraction, code transformation, creating visual artifacts from coding, and basic code testing and QA are likely to become less relevant,” Asnani said. predicts.

    This, he continues, necessarily means that such skills are “not eliminated, but rather transformed.” Tech experts “need to focus and adapt to more complex, creative, and strategic tasks that AI cannot easily reproduce.”

    Tech-related skills that will be at the forefront include “machine learning, data structures, and natural language processing,” Brodnitz said. “These technical proficiencies form the backbone of AI applications and are essential for efficient data processing, learning algorithms, and language-based AI interactions. It is important to build and strengthen the skills of

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    “Technology professionals who think bigger and understand how to apply AI to advance toward strategic goals are well-positioned to succeed,” he says. jo bradley, Chief Scientist at Live Person. “For example, customer service, sales, and marketing functions are increasingly supported by AI, which is the customer's first point of contact and staffs the digital front door. In the same way, customer-facing AI is a goal for service, sales, and marketing leaders to continually improve customer-facing AI.”

    Key tools and platforms for designing, building, and managing 2020s solutions include “GitHub, Slack, Hugging Face, Reddit, and other existing open source collaboration platforms,” ​​Asnani said. “These resources will help you accelerate your learning by leveraging the technical knowledge and code contributions of others.”

    In addition to designing and building AI, there is a growing demand for human oversight to ensure the technology delivers reliable and meaningful results for the business. “Fundamentally, AI and ML technologies deal with data, which puts a high demand on people with data management and science skills,” he says. Srini Kadiyala, OvalEdge's Chief Technology Officer. “People need to cherry-pick the specific datasets and sources they need to power their AI algorithms and learning models.”

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    Data preparation is “currently one of the most important requirements for efficient execution and output of AI modules,” Kadiyala said. “While there is some autonomy in that AI can complete data preparation tasks to ensure accuracy and compliance, it is still essential that trained professionals take the reins in this area.”

    It's all about the increasing “democratization of both learning and technology development,” Asnani said. “Professionals must develop the ability to learn, forget, and relearn quickly. Their scope of learning must also include data structures and algorithms, data analysis, mathematics, and software engineering.”

    Websites, mobile apps and social media have already revolutionized the work of technology professionals, Bradley said. “They will change again and be reshaped by people who know where AI is most effective and where humans need to take the reins.”

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    With the demand for skills, new types of roles are also emerging. Brodnitz says the LinkedIn platform is seeing “an increase in AI-related titles.” “For example, over the past five years, the number of companies with a dedicated ‘Head of AI’ has more than tripled, reflecting the growing awareness of the importance of AI within organizations.” It shows.”

    Additional new roles include “AI ethics specialist, smart contract architect, blockchain network implementer, quantum computing engineer, and VR experience designer,” Asnani said. “With the increased focus on data security and privacy regulations, the need for data privacy managers is also increasing.”

    As organizations place greater emphasis on technology talent to deliver business outcomes and growth, we can expect to see a further shift away from programming and technical roles with their heads down. As part of this trend, low-code and no-code platforms will define technology work in the year ahead. The growth of these technologies “will accelerate dramatically with advances in AI and machine learning,” Asnan says.

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    The move means “IT professionals will be freed from the tasks of writing basic code, testing code, and performing quality assurance.” Asnani says. “Instead, their focus will shift to validating the results of the code and ensuring that the code meets the desired objectives and results. This shift will include a deeper understanding of the specific domain and We need to strengthen our functional knowledge.”

    Future success in technology jobs will depend on “intellectual fearlessness and curiosity,” Bradley said. “Don't get stuck in one way of thinking. Look for different approaches and perspectives. Whatever your expertise, don't worry about whether it fully applies to your chosen field; rather, explore it deeply. Dig in, practice, and have fun.”

    Even if you're proficient in AI development, there's still a lot to learn, he continues. For example, “You are an expert in machine learning. Take a challenging course in product marketing. Don't cede absolute authority to other experts. Be knowledgeable and curious. Ask them questions.”


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