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Artificial intelligence has revolutionized many industries, especially those connected to tech. With AI advancing at an unprecedented rate, certain professions may face a substantial threat to their existence. 

TripleTen looked at the professions that are vulnerable to being replaced by AI tools and came to a groundbreaking conclusion: learning data will help you stay AI-proof.

How can Data Analytics and Data Science insulate workers from this risk? Let’s take a deeper look. 

What Is AI?

AI is a branch of computer science that involves the development of intelligent machines that can automate manual tasks such as visual perception, speech recognition, and decision-making.

Whenever there's a job that’s repetitive or less creative, AI can execute it in minutes. A recent report from Goldman Sachs found that approximately two-thirds of US jobs can be automated by AI, and roughly a quarter to a half of their workload can be automated entirely.

What Professions Are First in Line for Automation?

The jobs vulnerable to AI replacement focus on monotonous, manual tasks. They don’t require the creativity and problem-solving that come naturally to human specialists. They can be divided into two categories: those related to data input/processing and those related to customer service.

Data Input

Some of these jobs are defined by manual data entry and basic analysis. Only ten years ago, data entry had minimal automation, while nowadays, many tools can parse, copy, and paste information from various sources. With modern AI and optical character recognition, most of the initial data gathering and processing cycles can be automated.

Here are some examples of the jobs that are predicted to disappear from the market:

  • Data entry clerks: Tools that convert voice to text or scan, recognize, and convert written sources to text are replacing specialists that used to work in industries with lots of paperwork.
  • Bookkeeping and accounting: Cloud accounting and automation tools can handle routine tasks such as data entry, reconciliations, and reporting. Big accounting firms have invested a lot in developing technologies to stay ahead of the curve. Those investing the most are now looking for cognitive and social skills in tech-savvy candidates.
  • Insurance underwriters: All insurance has to calculate underlying risk to make it affordable for the insured and secure for the insurer. AI technologies can analyze vast data and accurately predict risks, premiums, and claims.
  • Paralegals: One recent study by Princeton University showed that the legal industry will be the one most affected by AI. AI-powered legal technologies can handle routine tasks such as document review, contract management, and legal research. 

Customer Service

Early customer assistance is ripe for automation. Companies are developing chatbots and robots that can accept many customer inquiries simultaneously and decide whether human attention is needed. Retailers, airlines, medical services, banks, and other customer-related businesses implement automation to reduce the workload on their employees.

Due to this, some professions may experience a decrease in demand:

  • Customer service representatives: Traditionally, most customer inquiries were handled by humans. However, with the rise of AI and automation tools like chatbots and voice assistants, customer service representatives are at risk of displacement.
  • Telemarketers: Previously, telemarketing was widely used for lead generation, customer service, and sales in many companies. However, telemarketing jobs are declining rapidly with the increased use of chatbots, voice assistants, and automated calling systems. Wherever humans work with scripts, AI systems are faster and more accurate.
  • Travel agents: AI technologies are already adopted by and familiar to the travel industry. Expedia has been using them for ages to personalize recommendations. Generative AI like ChatGPT is the next step in travel. The ability to create a complete travel itinerary via chatbot is just around the corner.

What Can These Professionals do?

People working in these fields can shift their attention to higher-value services that AI cannot provide. While AI tools can outcompete on the initial process of data gathering, entry, and processing and take over monotonous tasks like paperwork and recording claims, human specialists can contribute with their knowledge and experience in rapidly growing fields like Data Analytics and Data Science.

Data Analytics

Data Analytics is a growing area focusing on understanding data and creating valuable business insights. Every company uses data, whether it’s customer data, sales data, or web analytics data, to make decisions based on facts rather than assumptions.

For specialists that have worked with data entry before, switching to Data Analytics would be a logical step. It will help them stay ahead of the AI curve while also raising their paycheckData Analyst Salary: $90K a Year Is Not a Limit. If you’d like to know more about what a Data Analyst does, read our articleData Analysis Career Guide for 2023: Tasks, Skills, and How to Become a Data Analyst.

Data Science

Data Science is a diverse field that incorporates math, statistics, programming, advanced analytics, machine learning, artificial intelligence, and neural networks. The job of a Data Scientist is to learn from data and to make programs learn from it. They create algorithms that automate many processes for companies, manipulating big numbers and gathering valuable insights from data. Finally, they train AI models like chatbots to take the strain off fellow human specialists.

With experience in accounting, legal work, or customer management, you can contribute to developing innovative AI models. Former telemarketers and customer service representatives can help build chatbots' decision trees. Legal professionals can incorporate their knowledge to help shape advanced algorithms to sort through dense legalese.

If you’re interested in knowing more about the day-in-the-life of a Data Scientist, read more in this articleWhat Do Data Scientists Do?. If you’re curious about the core differences between Data Science and Data Analytics, check out this storyData Science vs. Data Analytics: Which Path Is Right For You?.

At TripleTen bootcamps, you can study for a new career that will allow you to work in an in-demand and well-paid field. In less than a year, you will get a new specialization and land a tech job with the extensive help of our tutors and the TripleTen career team.

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