AI Everywhere, Should You Believe the Hype?

Even if you’re living under a rock, the deafening noise of AI must have reached you by now. There are a lot of opinions going around about AI development, its use cases, and the risks it poses to society. But not all of it is true or complete facts. AI hype is here and it’s important to look past the smoke to find the real deal. In this article, let’s discuss everything you need to know about AI in today’s tech climate and what it means for the job market. 

But first, what is AI?

In a nutshell, artificial intelligence (AI) is the ability of machines to perform tasks that would normally require human intelligence. AI is achieved through the development of algorithms and machine learning models that can learn from data, adapt to new situations, and improve over time. It tries to mimic human analytical processes and refine them to reach goals faster. 

Before the AI bandwagon reached crescendo early this year, we were already using sophisticated AI platforms across industries. 

Popular AI use cases in 2023

AI, armored with natural language processing (NLP) is revolutionizing a lot of industries. But some applications have gained more fans than others. Here are a few of the most popular AI use cases today:

AI chatbots for customer experience (CX)

Customer experience automation is a tricky part of a business that often decides a company’s fate. Executives always look to improve CX and retention strategies and automating these services with AI seems to be the way forward. AI apps such as Salesforce Einstein, Intercom, Replika, Drift, Zendesk, and Netomi are a few companies utilizing AI in CRM. 

AI in healthcare

AI in healthcare removes human errors and builds on years of concrete information to diagnose diseases and help doctors decipher conditions. In healthcare, AI is used to analyze medical images and develop personalized treatment plans based on patient data. On top of that, it can also help in equipment sourcing and supply chain. Companies such as Butterfly Network, Cleerly, Enlitic, and Arterys are already revolutionizing healthcare.

Generative AI 

The most popular (and hotly debated) AI application in recent times—generative AI is a disruptive force in corporate, creative, and technical fields. Generative AI apps such as Midjourney, Aiva, Synthesia, Genei, Anthropic,, GitHub Copilot, Google Bard, and OpenAI’s ChatGPT use large language models (LLMs) to generate texts, codes, images, and videos quickly. 

AI in financial services

Industries that deal with a lot of volatility and require decades of data to find objective outcomes will find AI to be a game-changer. Financial services and fintech companies use AI to summarize trends, predict market movements, detect fraud, and improve real-time decision-making. Companies like Alphasense, SAP, Signifyd, and Kensho are being used by banks and consumers to get better at finances.

AI-human collaborations

A lot of AI technologies are purpose-built to work with human operators to achieve maximum efficiency. The collaboration takes the best of both worlds and helps companies hit KPIs faster. This type of application is visible in supply chains, heavy machinery, drone management, and warehousing. 

AI cybersecurity

With the rise of AI, the cybersecurity landscape has taken a different turn. Vulnerability management, threat mitigation, and building comprehensive security infrastructures are all part of AI use cases. Companies such as Tessian, Fortinet, Palo Alto Networks, Webroot, and Cylance are already doing great work in this field.

AI at work: is it a threat?

With the growing ubiquitous nature of AI, it’s time to ask the question: is AI going to steal jobs? 

On the surface, AI does seem to handle a lot of work that’d require humans more time and effort to achieve similar results. But that’s not the whole story. AI, at its current stage, is built on outdated datasets and is prone to biases it’s trained on. On top of that, the generative AI apps are often confident liars—they generate results that “feel” right, which is often not correct. Someone who’s eager to accept the results of the AI might gloss over the glaring inconsistencies and lack of coherent data and end up accepting flawed results. That’s why human oversight is so important—it not only helps AI offer better results but also develops accountability. 

AI fares best in terms of scalability but companies must develop policies to use human creativity to reach shared goals. As such, a lot of traditional jobs will be modified but they won’t necessarily become obsolete. A very popular saying regarding this is “AI will not take your job, but the person using AI will”. Jobs that require high accuracy but limited creativity such as underwriting, data entry, and manufacturing will have faster AI adoption and the employees will become experts who oversee the AI tools and verify the work. 

On the other hand, AI has visible weaknesses, especially in terms of strategic planning, infusing empathy in work, and works dealing with hand-eye coordination and abstract or unknown ideas. Humans will continue to lead the change in these fields and might see their professions evolving into something else. But the worst, that is the fear of losing jobs, is not a concern for employees who keep upskilling and reinventing themselves in a highly evolving job market. 

AI’s potential to create new jobs

More than the anxiety of an AI takeover, a more productive outlook is the vast swathe of new jobs that’ll be created because of it. According to a report by the World Economic Forum, 97 million new jobs will be created by 2025 because of AI advancement. I’ve already talked about professionals becoming consultants and strategists in the future but the biggest leap is still not known to any of us. But we can predict what the future might look like. 

For instance, Apple’s AIML team was recently looking for an Annotation Analyst to bring active listening skills and empathy to the AI/ML development, while BNP Paribas was looking for an AI Product Owner to improve the overall development of its data science tools and integrate accountability. There could be AI prompt engineers and AI trainers to refine existing models and help employees make the best of these tools, digital health coaches who’d collaborate with AI to develop health plans, robotics technicians to repair and maintain AI machines, and AI ethicists to explore the developing state of AI. The last one is particularly important for an AI-powered future. 

However, employees that start upskilling today will be prepared for disruptions. Skills that’ll separate successful employees are superior communication and writing skills, creativity, critical thinking, basic knowledge of coding and programming languages, emotional intelligence, especially in tricky situations, and people management. 

AI responsibilities

AI is a powerful tool that’s still at a nascent stage. But with great power comes great responsibility. Since the models are still a few years from reaching artificial general intelligence (AGI) and sentience, questions of ethics and responsibilities are bound to crop up. 

Unsurprisingly, the rogue use of AI, particularly in creating ransomware and other malware has forced administrations to look into regulations. Another risk is ownership. If an AI model generates something, then the question of copyrights can make legal proceedings murkier. So far, most AI-generated content cannot be copyrighted because it’s hard to pinpoint the required level of human involvement in creating them. On top of that, several AI companies have been accused of using copyrighted content to train their models without permission, which may soon open Pandora’s box. Italy has already banned ChatGPT and is looking to seek public opinion and regulations before it allows AI tools into the market. 

The bottom line is that AI at its current stage has a long way to go before it threatens businesses and professions. Lack of regulations and legal frameworks, inaccurate and outdated output, and discriminatory results are only a few of the many challenges companies need to address before AI can go mainstream.

The hype we’re seeing today is based on the fear of missing out (FOMO) and the future potential of such tools. The decision-making algorithms need more time to develop but even if it ever archives AGI, humans will be better prepared to address that. 

Bottom line

AI today is both a buzzword in the tech world and an amorphous fear amongst the general public. But the truth is, it’s nowhere near any of that. The future applications of AI will vastly improve healthcare, transport, manufacturing, and creative fields. It will also eat into a lot of jobs, but not before creating many times more new jobs. Tech evolution is inevitable and just like the industrial revolution, we’ll learn to live with it, and for the better. 


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