How to choose a career in AI? | AI in business #54

A career in AI offers not only the prospect of attractive salaries but also the opportunity to help shape the modern world. Companies across industries are increasingly adopting AI-based solutions, creating a strong demand for specialists. This is a fast-growing field where there is something for everyone, from engineering to AI ethics. A career in AI is therefore not tied to one business sector: it opens doors to creative industries, finance, and IT. So how to choose the right career field in AI? Read our article and find out.

A career in AI – what opportunities does it offer?

Artificial intelligence is present in virtually every aspect of business today, from automating manufacturing processes to personalizing online store offerings to analyzing large amounts of data. Although the situation is very dynamic, there are several major career paths in AI:

1. Engineering. AI and machine learning engineers have analytical minds and a passion for solving complex problems.
2. Data. Data science, the analysis and interpretation of data, is the foundation of any AI project. Without systems to collect and process raw data, it would be impossible to use it effectively.
3. Applied AI. According to McKinsey’s “Technology Trends Outlook 2023” report, applied AI is one of the fastest-growing technology sectors. It includes business implementations of machine learning (ML), image recognition (Computer Vision), and natural language processing (NLP). An important part of it is the application of AI to marketing and sales.
4. AI ethics. A career in AI as an ethics officer is one of the emerging professions focusing on creating AI policies for organizations and ensuring compliance with the law.

In what sectors is there a demand for AI specialists?

According to the US Bureau of Labor Statistics, technological advancements are driving the demand for artificial intelligence experts, which is expected to increase by 23 percent from 2022 to 2032. That’s much faster than in other industries. Here are the key players:

1. Finances — banks and investment firms use big data and predictive algorithms to maximize profits and improve fraud detection.
2. Agriculture — intelligent systems make it possible to optimize crop management and improve yields – this is where agrotechnologists come in. Thanks to their work, it is possible to minimize the use of fertilizers and pesticides, use robots, and precisely target and destroy pests.
3. Healthcare — AI is changing the face of medicine by improving diagnostics and supporting telemedicine – jobs like “health data analyst” are emerging. AI is also being used extensively in research to develop new drugs and treatments.

Source: DALL·E 3, prompt: Marta M. Kania

What skills are necessary to start a career as an AI engineer?

AI engineer jobs are for people who are fascinated by technology and have programming skills. For example, AI engineers who develop personalized recommendations for platforms like Netflix and Spotify are responsible for developing algorithms that match content to users’ preferences.

Data Science — what competencies do you need?

To be an effective data analyst, it is essential to have technical skills, such as knowledge of programming languages used in data analysis, for example, Python or R, and data visualization tools (such as Tableau or Power BI). It is also important to be able to work with large data sets, which requires knowledge of databases and SQL queries.

Apart from technical skills, statistical and mathematical skills are the foundation of data analysis. They allow for correct interpretation and conclusions. In addition, an analyst must have communication skills to effectively present analysis results and recommendations. Critical thinking and problem-solving skills are also useful in generating valuable business insights.

A career in applied AI

AI-powered marketing is no longer the future but an everyday reality. Using customer data, companies can tailor communications and products to individual users’ needs.Specialists will need to be able to configure sales chatbots or recommendation systems to help personalize online store offers. It will also be important to be able to use generative artificial intelligence, that is to say:

• chatbots like ChatGPT or Bard that can help with marketing strategies and content,
• Midjourney or DALL·E 3 for creating images, and
• Runway or Kaiber for video content.

Source: Kaiber (https://kaiber.ai/dashboard)

AI ethics

Ethics specialists deal with an important aspect of technology: challenges to privacy and the impartiality of algorithms. Their job is to ensure that systems based on artificial intelligence are used responsibly and according to the company’s values and the law.

AI platforms for training –where to gain knowledge?

The plethora of online learning platforms allows for flexible training in artificial intelligence and self-preparation for a career in AI. Here are a few recommended options:

• IBM AI Engineering Professional Certificate (https://www.coursera.org/professional-certificates/applied-artifical-intelligence-ibm-watson-ai) – a 9-month program covering machine learning, neural networks, image processing, and computer vision,
• Deeplearning.ai (https://www.deeplearning.ai/) – a 3-month program from one of the leading experts in AI, Andrej Karparthy,
• Coursera (https://coursera.org/)– a wide range of courses, specializations, and professional certifications in AI, machine learning, data science, and related fields. Programs created in cooperation with Stanford University and IBM are available,
• Introduction to generative AI from Google (https://www.cloudskillsboost.google/paths/118 ) – a set of introductory courses on generative AI, Large Language Models (LLMs), and their applications.

Regardless of the chosen platform, the key is to combine learning theory with practice in the form of sample projects and solve real business and social problems using AI and data science.

Source: Coursera (https://www.coursera.org/professional-certificates/applied-artifical-intelligence-ibm-watson-ai)

What soft skills are valued in the AI industry?

Despite the rapid evolution of technology, certain qualities will remain the same. To develop a career in AI, creativity or problem-solving skills will come in handy. The ability to work in a team is also considered an important asset when working on AI projects.

Summary

Going through the maze of career opportunities in the field of artificial intelligence requires a thorough understanding of both the needs of the job market and your own aptitudes. Understanding the specifics of different roles and their requirements will allow you to accurately choose a career in AI, chart an educational path, and focus on developing the most valuable soft skills. Artificial intelligence is evolving at an unprecedented rate. Adapting your career path to it will require flexibility, courage, and out-of-the-box thinking. But it may prove to be the key to professional success.

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AI in business:

1. Threats and opportunities of AI in business (part 1)
2. Threats and opportunities of AI in business (part 2)
3. AI applications in business - overview
4. AI-assisted text chatbots
5. Business NLP today and tomorrow
6. The role of AI in business decision-making
7. Scheduling social media posts. How can AI help?
8. Automated social media posts
9. New services and products operating with AI
10. What are the weaknesses of my business idea? A brainstorming session with ChatGPT
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12. Synthetic actors. Top 3 AI video generators
13. 3 useful AI graphic design tools. Generative AI in business
14. 3 awesome AI writers you must try out today
15. Exploring the power of AI in music creation
16. Navigating new business opportunities with ChatGPT-4
17. AI tools for the manager
18. 6 awesome ChatGTP plugins that will make your life easier
19. 3 grafików AI. Generatywna sztuczna inteligencja dla biznesu
20. What is the future of AI according to McKinsey Global Institute?
21. Artificial intelligence in business - Introduction
22. What is NLP, or natural language processing in business
23. Automatic document processing
24. Google Translate vs DeepL. 5 applications of machine translation for business
25. The operation and business applications of voicebots
26. Virtual assistant technology, or how to talk to AI?
27. What is Business Intelligence?
28. Will artificial intelligence replace business analysts?
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30. AI and social media – what do they say about us?
31. Artificial intelligence in content management
32. Creative AI of today and tomorrow
33. Multimodal AI and its applications in business
34. New interactions. How is AI changing the way we operate devices?
35. RPA and APIs in a digital company
36. The future job market and upcoming professions
37. AI in EdTech. 3 examples of companies that used the potential of artificial intelligence
38. Artificial intelligence and the environment. 3 AI solutions to help you build a sustainable business
39. AI content detectors. Are they worth it?
40. ChatGPT vs Bard vs Bing. Which AI chatbot is leading the race?
41. Is chatbot AI a competitor to Google search?
42. Effective ChatGPT Prompts for HR and Recruitment
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44. AI Mockup generator. Top 4 tools
45. AI and what else? Top technology trends for business in 2024
46. AI and business ethics. Why you should invest in ethical solutions
47. Meta AI. What should you know about Facebook and Instagram's AI-supported features?
48. AI regulation. What do you need to know as an entrepreneur?
49. 5 new uses of AI in business
50. AI products and projects - how are they different from others?
51. AI-assisted process automation. Where to start?
52. How do you match an AI solution to a business problem?
53. AI as an expert on your team
54. AI team vs. division of roles
55. How to choose a career field in AI?
56. Is it always worth it to add artificial intelligence to the product development process?
57. AI in HR: How recruitment automation affects HR and team development
58. 6 most interesting AI tools in 2023
59. 6 biggest business mishaps caused by AI
60. What is the company's AI maturity analysis?
61. AI for B2B personalization
62. ChatGPT use cases. 18 examples of how to improve your business with ChatGPT in 2024
63. Microlearning. A quick way to get new skills
64. The most interesting AI implementations in companies in 2024
65. What do artificial intelligence specialists do?
66. What challenges does the AI project bring?
67. Top 8 AI tools for business in 2024
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73. How much does using AI increase the productivity of your team?
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79. Artificial intelligence in the media
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81. AI in the travel industry
82. How AI is fostering the birth of new technologies
83. The revolution of AI in social media
84. AI in e-commerce. Overview of global leaders
85. Top 4 AI image creation tools
86. Top 5 AI tools for data analysis
87. AI strategy in your company - how to build it?
88. Best AI courses – 6 awesome recommendations
89. Optimizing social media listening with AI tools
90. IoT + AI, or how to reduce energy costs in a company
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95. What is the cost of implementing AI in a company?
96. How can AI help in a freelancer’s career?
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99. Building a website with AI
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110. AI voice cloning for business. How to create personalized voice messages with AI?
111. Fact-checking and AI hallucinations
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115. How is AI changing influencer marketing?
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