Tech
Using generative AI for business growth
Will generative AI replace jobs traditionally done by humans?
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Artificial intelligence (AI) is a revolutionary technology disrupting virtually every sector of the economy, from manufacturing and retail to sports and entertainment.
The average consumer may not know that AI is all around them.
Companies can use AI to curate users’ social media feeds, make new drug discoveries, power digital voice assistants, and allow smartphone owners to unlock their phones with facial recognition.
One specific type of AI – generative AI – is an advancement in AI that holds great promise.
Take a deeper look at generative AI, examples of its common applications, and how it can drive growth for businesses of all types and sizes.
What is generative AI, and how does it differ from conventional AI?
In conventional AI models, algorithms classify, organize, or reason about the data it receives.
On the other hand, generative AI algorithms can create data using models from the real world to synthesize text, code, photos, videos, and sounds that often look highly realistic to the average person.
A generative AI model can detect the original pattern entered into the input and generate creative, authentic results highlighting training data features.
After the model identifies the fundamental properties of the input data, it uses a generative adversarial network (GAN), a variational autoencoder (VAE), or a transformer to produce the most accurate outcomes.
Generative AI models create synthetic personalities or presences, which must pass the Turing test.
This assessment determines whether a machine can engage in conversation with a human without being recognized as a machine.
If data from a generative AI model passes the Turing test, it demonstrates human intelligence.
Generative AI use cases
Generative AI is often associated with deep fakes, popular on social media and other online platforms. However, it’s playing an increasingly important role in various industrial applications.
Most of the time, generative models support various content creation activities. For example, movie makers could use generative AI for a few reasons, including filling narrative gaps in the plot or even carrying the entire storyline.
News organizations also use generative AI models to create stories about current events and financial or sports reports.
Not all generative artificial intelligence has to do with content creation, though. Some algorithms can improve a user interface or provide audio descriptions for people who are blind or have vision loss.
For example, companies use it to automate repetitive digital image or audio correction processes.
Organizations are also experimenting with generative AI in manufacturing, as it could be an essential tool for rapid prototyping.
It can improve data augmentation for robotics process automation (RPA), also known as software robotics.
How generative AI fuels business growth
Because generative AI is still evolving, experts suggest the market will witness significant growth and create new business opportunities by 2028.
Below are some ways organizations can use generative AI to fuel business growth in a fiercely competitive business landscape.
Overcomes labor shortages
Finding the right talent during recruiting and hiring is a major challenge many businesses face, particularly in nations or industries with severe labor shortages.
Recent research shows that approximately 88% of CFOs consider talent attraction and employee retention a primary concern for their companies.
How can generative AI help with labor shortages, talent acquisition, and retention?
Generative artificial intelligence can be a boon to companies because it can take over some creative tasks typically performed by human employees.
When generative AI is used for content creation, organizations can hire fewer employees to handle the responsibilities of publishing, broadcasting, or communications-related tasks.
Helps businesses meet market demand
Every sector wants to leverage new and emerging technologies to improve its operations. For example, manufacturers use robotics to speed up the production process.
In contrast, healthcare facilities use secure video conferencing to meet with patients remotely.
When companies offer generative artificial intelligence solutions and garner clients, they’re better positioned to meet market demand and help organizations further their business.
This can lead to positive business relationships, and potential growth as a generative AI company gains more clients.
Enhances product design and drives innovation
Businesses also use generative AI to support product design and development. According to McKinsey, organizations apply generative design to products with specific weight and material considerations.
For example, companies that produce sports equipment, vehicles, aircraft, and handheld tools can use generative design and cut costs significantly.
Saving on these costs can help companies make better investments and grow.
Supports personalization
Modern customers want personalized products, services, and advertising. Therefore, companies must create customized items to meet customer needs and expectations.
For instance, Replikr is a New Zealand startup using generative AI to create intelligent avatars for healthcare patients seeking customer support services.
Replikr’s AI-based avatars are lifelike, help personify the company’s brand to customers, and provide next-level customer service experiences, which are becoming increasingly important today.
Expect generative AI to become increasingly prevalent
The generative AI market will grow in the next few years, causing some members of the global workforce to become concerned about job security.
Will generative AI replace jobs traditionally done by humans? The simple answer is most likely no.
Experts suggest that AI works best alongside human employees. As a result, some professionals will have to learn the ins and outs of generative artificial intelligence to succeed in their roles.
Still, this technology will not replace humans entirely. It’ll be interesting to see how generative AI evolves and more use cases emerge.
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